CN109615150A - A kind of method and system of determining rice Meteorological Output - Google Patents

A kind of method and system of determining rice Meteorological Output Download PDF

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CN109615150A
CN109615150A CN201811646262.XA CN201811646262A CN109615150A CN 109615150 A CN109615150 A CN 109615150A CN 201811646262 A CN201811646262 A CN 201811646262A CN 109615150 A CN109615150 A CN 109615150A
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刘申
张彧豪
张虎成
彭远
董婷婷
张东晖
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Aisino Corp
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Abstract

The present invention provides a kind of method and system of determining rice Meteorological Output.Described method and system is according to the main meteorological indication information for influencing plant growth when preceding crop region, main includes the data of historical data and current year known time, pass through meteorological index prediction model, predict current year rice meteorological index information, the meteorological biomass for predicting rice current year each growthdevelopmental stage by meteorological index-meteorology biomass prediction model again, predicts current year rice Meteorological Output by meteorological biomass-Meteorological Output prediction model.The method and system of determining rice Meteorological Output of the present invention is by establishing meteorological index-meteorology biomass prediction model of each growthdevelopmental stage of rice, it can be realized the meteorological biomass prediction of each growthdevelopmental stage of rice, to increase the accuracy of rice Meteorological Output prediction, the dynamic release of rice Meteorological Output is realized, to ensure that the rice market supply and demand balance in China provides technical support.

Description

A kind of method and system of determining rice Meteorological Output
Technical field
The present invention relates to yield of commercial crops to predict field, and more particularly, to a kind of determining rice Meteorological Output Method and system.
Background technique
Rice yield is generally divided into biological yield and economic flow rate.Biological yield abbreviation biomass, refers to rice each By photosynthesis and absorption in breeding cycle, i.e., produces and accumulate various organic by the conversion of matter and energy The total amount of object does not usually include root system when calculating biomass.Economic flow rate refers to the harvest yield of rice grain required for cultivation purpose, I.e. general signified yield.In general, the height of economic flow rate is directly proportional to biomass height.
The length of growth period duration of rice, in addition to the heredity for depending mainly on rice, due also to the weather conditions in cultivation area With the factors such as cultivation technique and it is variant.Because temperature is low when such as autumn sowing, winter sowing, growth and development is slow, and breeding time is longer;Sow in spring, Because of temperature height when summer sowing, growth and development is fast, and breeding time is shorter.Same kind is planted in different latitude area, due to temperature, illumination Difference, breeding time also changes therewith.
Since prolonged output fluctuation is not only related with meteorological index, also updated with rice varieties, socioeconomic transition Etc. closely related, so in the crop yield of long-term sequence and the observation statistical research of meteorological index relationship, generally water The yield of rice is decomposed into 3 part of trend yield, Meteorological Output and random error, and trend yield is reflecting history period productivity hair Horizontal long period yield component is opened up, also referred to as technical production, Meteorological Output are the variation of short period based on climate element The fluctuating yield component that the factor (based on agroclimate disaster) influences.Therefore rice Meteorological Output is the weight in Rice Yield Prediction Point.
The full breeding cycle weather conditions for only accounting for rice to the prediction of rice Meteorological Output in the prior art change, so And requirement of the rice in different growth and development processes to weather conditions is different, different geographical influences the pass of crop growth Key period and meteorologic factor are also different, only consider influence of the full breeding cycle weather conditions to rice Meteorological Output can not and When, rice Meteorological Output fluctuates under Accurate Prediction weather conditions.
Therefore, it is necessary to a kind of technology, can according to the influence of the different growthdevelopmental stage climate condition of rice and caused by The difference of meteorological biomass determines the Meteorological Output of rice by each growthdevelopmental stage meteorology biomass variety of rice.
Summary of the invention
It can not in order to solve the influence only considered in the prior art full breeding cycle weather conditions to rice Meteorological Output In time, the technical issues of rice Meteorological Output fluctuates under Accurate Prediction weather conditions, it is meteorological that the present invention provides a kind of determining rice The method of yield, which comprises
The data of data and current year known time based on the meteorological index past n for influencing rice growth, according to setting Meteorological index prediction model, determine the data of the meteorological index of rice current year each growthdevelopmental stage, wherein the meteorological index Including mean daily temperature, Daily minimum temperature, max. daily temperature and rice field day water layer height;
The data of meteorological index based on rice current year each growthdevelopmental stage, refer to according to the meteorology of each growthdevelopmental stage of rice Mark-meteorology biomass prediction model determines the meteorological biomass of rice current year each growthdevelopmental stage;
Based on the meteorological biomass of rice current year each growthdevelopmental stage, predicted according to rice meteorology biomass-Meteorological Output Model determines the Meteorological Output of rice current year.
Further, the method is gone over known to data and the current year of n based on the meteorological index for influencing rice growth The data of time determine the number of the meteorological index of rice current year each growthdevelopmental stage according to the meteorological index prediction model of setting According to before further include:
According to the fertility feature of rice, the growth stage of rice is divided into several growthdevelopmental stages;
Acquisition influences data, each fertility of the data and current year known time of the meteorological index past n of rice growth The data of biomass past n, the data of economic flow rate past n and rice each growthdevelopmental stage beginning and ending time in period Historical data;
The beginning and ending time of current year each growthdevelopmental stage is determined according to the historical data of rice each growthdevelopmental stage beginning and ending time;
Determine that the meteorology of each growthdevelopmental stage of rice is raw based on the data of the biomass past n of each growthdevelopmental stage of rice The data of object amount past n;
The data of meteorological index past n based on each growthdevelopmental stage of rice and the data of meteorological biomass past n Determine meteorological index-meteorology biomass prediction model of each growthdevelopmental stage of rice;
The data of rice Meteorological Output past n are determined based on the data of rice economic flow rate past n;
The data and rice Meteorological Output of meteorological biomass past n based on each growthdevelopmental stage of rice go over n's Data determine meteorological biomass-Meteorological Output prediction model of rice.
Further, the data of data and current year known time based on the meteorological index past n for influencing rice growth, According to the meteorological index prediction model of setting, determine that the meteorological index data of rice current year each growthdevelopmental stage include:
Based on the data for the meteorological index past n for influencing rice growth, according to the meteorological index prediction model of setting, really The meteorological index data of settled unknown time in year, in which:
The calculation formula of mean daily temperature prediction model are as follows:
When the max. daily temperature standard deviation determined according to certain day max. daily temperature in past n is greater than or equal to according to certain When the Daily minimum temperature standard deviation that the Daily minimum temperature of its past n determines:
When the max. daily temperature standard deviation determined according to certain day max. daily temperature in past n is less than to be gone over according to certain day When the Daily minimum temperature standard deviation that the Daily minimum temperature of n determines:
In formula, TnaveIt is certain day mean daily temperature in the current year unknown time, ThminIt is certain day in the current year unknown time Minimum value in the Daily minimum temperature of past n, ThmaxIt is certain day day highest temperature in past n in the current year unknown time Maximum value in degree, μminBe where certain day in unknown time current year month the Daily minimum temperature in past n mean value, μmax Be where certain day in unknown time current year month the max. daily temperature in past n mean value, μaveIt is in the current year unknown time Certain day where month mean value in the mean daily temperature of past n, σminIt is to exist in month where certain day in unknown time current year The standard deviation of the Daily minimum temperature of past n, σmaxMonth where certain day in unknown time current year past n day most The standard deviation of high-temperature, σaveBe where certain day in unknown time current year month the mean daily temperature in past n standard Difference, χ is the daily standard normal deviation generated, according to two random number rnd1And rnd2It obtains;
The calculation formula of Daily minimum temperature prediction model are as follows:
When the max. daily temperature standard deviation determined according to certain day max. daily temperature in past n is greater than or equal to according to certain It is in the Daily minimum temperature standard deviation that the Daily minimum temperature of past n determines:
Tn minminmin×χ
When the max. daily temperature standard deviation determined according to certain day max. daily temperature in past n is less than according to certain day in mistake When the Daily minimum temperature standard deviation for going the Daily minimum temperature of n to determine:
In formula, Tn minIt is certain day Daily minimum temperature in the current year unknown time, Th maxIt is certain in the current year unknown time Its maximum value in the max. daily temperature of past n, μminIt is month where certain day in the current year unknown time in past n Daily minimum temperature mean value, μmaxMonth where certain day in unknown time current year past n max. daily temperature it is equal Value, σminBe where certain day in unknown time current year month the Daily minimum temperature in past n standard deviation, σmaxBe current year not Month where knowing certain day in the time, χ was that the daily standard normal of generation is inclined in the standard deviation of the max. daily temperature of past n Difference, according to two random number rnd1And rnd2It obtains;
The calculation formula of max. daily temperature prediction model are as follows:
When the max. daily temperature standard deviation determined according to certain day max. daily temperature in past n is greater than or equal to according to certain It is in the Daily minimum temperature standard deviation that the Daily minimum temperature of past n determines:
When the max. daily temperature standard deviation determined according to certain day max. daily temperature in past n is less than according to certain day in mistake When the Daily minimum temperature standard deviation for going the Daily minimum temperature of n to determine:
Tn maxmaxmax×χ
In formula, Tn maxIt is certain day max. daily temperature in the current year unknown time, Th minIt is certain in the current year unknown time Its minimum value in the Daily minimum temperature of past n, μminIt is month where certain day in the current year unknown time in past n Daily minimum temperature mean value, μmaxMonth where certain day in unknown time current year past n max. daily temperature it is equal Value, σminBe where certain day in unknown time current year month the Daily minimum temperature in past n standard deviation, σmaxBe current year not Month where knowing certain day in the time, χ was that the daily standard normal of generation is inclined in the standard deviation of the max. daily temperature of past n Difference, according to two random number rnd1And rnd2It obtains;
The calculation formula of rice field day water layer Height Prediction model are as follows:
H=μHH×χ
In formula, H is certain day rice field day water layer height in the current year unknown time, μHIt is certain day in the current year unknown time Place month the mean value in the rice field day water layer height of past n, σGMonth is in past n where certain day in the unknown time for the year The standard deviation of the rice field day water layer height in year, χ are the daily standard normal deviations of generation according to two random number rnd1And rnd2? It arrives;
By the meteorological index data of current year known time and the current year unknown time determining by meteorological index prediction model Meteorological index data divided according to the beginning and ending time of each growthdevelopmental stage of rice to get to each growthdevelopmental stage of rice Meteorological index data.
Further, the data of the biomass past n based on each growthdevelopmental stage of rice determine each life of rice Educate period meteorological biomass past n data include:
The data of the biomass past n of each growthdevelopmental stage of rice are generated into biomass sequence data in chronological order;
Using i as sliding step, with the linear slide method of average to the biomass of every i of each growthdevelopmental stage of rice into Row statistical regression analysis obtains j group unary linear regression equation, wherein 1≤i≤n, 1≤j≤i, i, j and n are natural numbers;
The analogue value of j annual biomass of each growthdevelopmental stage of rice is determined based on j group unary linear regression equation;
The analogue value of annual biomass is determined according to the analogue value of j annual biomass of each growthdevelopmental stage of rice Average value, and the trend biomass annual as each growthdevelopmental stage of rice;
The annual biomass of each growthdevelopmental stage of rice and trend biomass are subtracted each other as each growthdevelopmental stage of rice Annual meteorological biomass.
Further, the data of the meteorological index past n based on each growthdevelopmental stage of rice and meteorological biomass The data of past n determine that meteorological index-meteorology biomass prediction model of each growthdevelopmental stage of rice includes:
The data of meteorological index past n based on each growthdevelopmental stage of rice and the data of meteorological biomass past n It determines kernel function, the weight of each kernel function of each meteorological index and meteorological biomass, and is sought according to kernel function determination The deviation of meteorological biomass;
Kernel function, the weight of each kernel function and deviation based on each meteorological index and meteorological biomass determine The meteorological index of each growthdevelopmental stage of rice-meteorology biomass prediction model, its calculation formula is:
In formula, yiIt is the meteorological biomass of rice i-th of growthdevelopmental stage of current year,It is rice i-th of growthdevelopmental stage of current year The kernel function of j-th of meteorological index, ωijIt is the weight of the kernel function of rice current year i-th of growthdevelopmental stage, j-th of meteorological index, biIt is according to kernel functionDetermine the deviation of the meteorological biomass of rice i-th of growthdevelopmental stage of current year.
Further, the data based on rice economic flow rate past n determine the number of rice Meteorological Output past n According to including:
The data of rice economic flow rate past n are generated into economic flow rate sequence data in chronological order;
Using i as sliding step, statistical regression point is carried out with the economic flow rate of linear slide method of average i every to rice Analysis, obtains j group unary linear regression equation, wherein 1≤i≤n, 1≤j≤i, i, j and n are natural numbers;
The analogue value of j annual economic flow rate of rice is determined based on j group unary linear regression equation;
The average value of the analogue value of annual economic flow rate is determined according to the analogue value of j annual economic flow rate of rice, And the trend economic flow rate annual as rice;
The annual economic flow rate of rice and trend economic flow rate are subtracted each other to the Meteorological Output annual as rice.
Further, the data and rice Meteorological Output of the meteorological biomass past n based on each growthdevelopmental stage of rice The data of past n determine that rice meteorology biomass-Meteorological Output prediction model includes:
The data and rice Meteorological Output of meteorological biomass past n based on each growthdevelopmental stage of rice go over n's Data determine the meteorological biomass of each growthdevelopmental stage and the kernel function of Meteorological Output, the weight of each kernel function, and according to Kernel function determines the deviation for seeking Meteorological Output;
Kernel function, the weight of each kernel function of meteorological biomass and Meteorological Output based on each growthdevelopmental stage of rice, And deviation determines rice meteorology biomass-Meteorological Output prediction model, its calculation formula is:
In formula, y is the Meteorological Output of rice current year,It is the core letter of rice i-th of growthdevelopmental stage meteorology biomass of current year Number, ωiIt is the weight of the kernel function of rice i-th of growthdevelopmental stage of current year, b is according to kernel functionDetermine the meteorology of rice current year The deviation of yield.
According to another aspect of the present invention, the present invention provides a kind of system of determining rice Meteorological Output, the system packet It includes:
Rice meteorological index unit is used for data and the current year of the meteorological index past n based on rice growth is influenced The data of known time determine the meteorological index of rice current year each growthdevelopmental stage according to the meteorological index prediction model of setting Data, wherein the meteorological index includes mean daily temperature, Daily minimum temperature, max. daily temperature and rice field day water layer height;
Rice meteorology biomass unit is used for the data of the meteorological index based on rice current year each growthdevelopmental stage, root According to meteorological index-meteorology biomass prediction model of each growthdevelopmental stage of rice, the gas of rice current year each growthdevelopmental stage is determined As biomass;
Rice Meteorological Output unit is used for the meteorological biomass based on rice current year each growthdevelopmental stage, according to rice Meteorological biomass-Meteorological Output prediction model, determines the Meteorological Output of rice current year.
Further, system further include:
Growth period duration of rice division unit is used for the fertility feature according to rice, if the growth stage of rice is divided into Dry growthdevelopmental stage;
Data acquisition unit was used to acquire known to the data for influencing the meteorological index past n of rice growth and current year The data of time, the data of biomass past n of each growthdevelopmental stage, the data of economic flow rate past n and rice are every The historical data of a growthdevelopmental stage beginning and ending time;
Time breeding time determination unit is used to be worked as according to the determination of the historical data of rice each growthdevelopmental stage beginning and ending time The beginning and ending time of year each growthdevelopmental stage;
First data cell is used to determine rice based on the data of the biomass past n of each growthdevelopmental stage of rice The data of the meteorological biomass past n of each growthdevelopmental stage;
First model unit is used for the data and meteorology of the meteorological index past n based on each growthdevelopmental stage of rice The data of biomass past n determine meteorological index-meteorology biomass prediction model of each growthdevelopmental stage of rice;
Second data cell is used to determine that rice Meteorological Output goes over n based on the data that rice economic flow rate goes over n The data in year;
Second model unit is used for the data and water of the meteorological biomass past n based on each growthdevelopmental stage of rice The data of rice Meteorological Output past n determine meteorological biomass-Meteorological Output prediction model of rice.
Further, the rice meteorological index unit includes:
Unknown meteorological index unit is used for the data based on the meteorological index past n for influencing rice growth, according to setting The meteorological index prediction model set determines the meteorological index data of current year unknown time, wherein the mean daily temperature, The calculation formula of Daily minimum temperature, max. daily temperature and rice field day water layer Height Prediction model and the side for determining rice Meteorological Output Identical in method, details are not described herein again.
Index determination unit is used for by the meteorological index data of current year known time and by meteorological index prediction model The meteorological index data of determining current year unknown time were divided to arrive according to the beginning and ending time of each growthdevelopmental stage of rice The meteorological index data of each growthdevelopmental stage of rice.
Further, first data cell includes:
First ray unit is used for the data of the biomass past n of each growthdevelopmental stage of rice in chronological order Generate biomass sequence data;
First equation group unit is used for using i as sliding step, with the linear slide method of average to each fertility of rice The biomass of every i in period carries out statistical regression analysis, obtains j group unary linear regression equation, wherein 1≤i≤n, 1≤j ≤ i, i, j and n are natural numbers;
First simulation value cell, is used to determine that each growthdevelopmental stage of rice is annual based on j group unary linear regression equation J biomass the analogue value;
First trend value cell is used to be determined according to the analogue value of j annual biomass of each growthdevelopmental stage of rice The average value of the analogue value of annual biomass, and the trend biomass annual as each growthdevelopmental stage of rice;
First result unit is used to subtract each other the annual biomass of each growthdevelopmental stage of rice and trend biomass i.e. For the annual meteorological biomass of each growthdevelopmental stage of rice.
Further, first model unit includes:
First parameters unit is used for the data and meteorology of the meteorological index past n based on each growthdevelopmental stage of rice The data of biomass past n determine kernel function, the weight of each kernel function of each meteorological index and meteorological biomass, and The deviation for seeking meteorological biomass is determined according to kernel function;
First formula cells are used for kernel function based on each meteorological index and meteorological biomass, each kernel function Weight and deviation determine meteorological index-meteorology biomass prediction model of each growthdevelopmental stage of rice, calculation formula Are as follows:
In formula, yiIt is the meteorological biomass of rice i-th of growthdevelopmental stage of current year,It is rice i-th of growthdevelopmental stage of current year The kernel function of j-th of meteorological index, ωijIt is the weight of the kernel function of rice current year i-th of growthdevelopmental stage, j-th of meteorological index, biIt is according to kernel functionDetermine the deviation of the meteorological biomass of rice i-th of growthdevelopmental stage of current year.
Further, second data cell includes:
Second sequence units, the data for being used to pass by rice economic flow rate n generate economic flow rate in chronological order Sequence data;
Second equation group unit is used for using i as sliding step, with linear slide method of average i's every to rice Economic flow rate carries out statistical regression analysis, obtains j group unary linear regression equation, wherein 1≤i≤n, 1≤j≤i, i, j and n It is natural number;
Second simulation value cell, is used to determine j annual economic flow rate of rice based on j group unary linear regression equation The analogue value;
Second trend value cell is used to determine annual economy according to the analogue value of j annual economic flow rate of rice The average value of the analogue value of yield, and the trend economic flow rate annual as rice;
The annual economic flow rate of rice and trend economic flow rate are subtracted each other the meteorology annual as rice by the second result unit Yield.
Further, second model unit includes:
Second parameters unit is used for the data and water of the meteorological biomass past n based on each growthdevelopmental stage of rice The rice Meteorological Output past data of n determine the meteorological biomass of each growthdevelopmental stage and kernel function, the Mei Gehe of Meteorological Output The weight of function, and the deviation for seeking Meteorological Output is determined according to kernel function;
Second formula cells are used for the core letter of meteorological biomass and Meteorological Output based on each growthdevelopmental stage of rice The weight and deviation of several, each kernel function determine rice meteorology biomass-Meteorological Output prediction model, calculation formula Are as follows:
In formula, y is the Meteorological Output of rice current year,It is the core letter of rice i-th of growthdevelopmental stage meteorology biomass of current year Number, ωiIt is the weight of the kernel function of rice i-th of growthdevelopmental stage of current year, b is according to kernel functionDetermine the meteorology of rice current year The deviation of yield.
The method and system for the determination rice Meteorological Output that technical solution of the present invention provides is special according to fertility by rice first Sign, is divided into several growthdevelopmental stages, and the meteorological index letter of major influence factors in history is combined in different growthdevelopmental stages Breath, establishes meteorological index-meteorology biomass prediction model with the biomass of identical growthdevelopmental stage in history respectively, and secondly application is gone through The biomass of identical growthdevelopmental stage and historical Meteorological Output establish meteorological biomass-Meteorological Output prediction model in history;It connects , it mainly include historical data and current year according to the main meteorological indication information for influencing plant growth when preceding crop region The data of known time are predicted current year rice meteorological index information, are referred to finally by meteorology by meteorological index prediction model Mark-meteorology biomass prediction model predicts the meteorological biomass of rice current year each growthdevelopmental stage, passes through meteorological biomass-gas As Production Forecast Models predict current year rice Meteorological Output.The method and system of determining rice Meteorological Output of the present invention It has the following beneficial effects:
1, by establishing meteorological index-meteorology biomass prediction model of each growthdevelopmental stage of rice, it can be realized rice The meteorological biomass of each growthdevelopmental stage is predicted, to increase the accuracy of rice Meteorological Output prediction;
2, can be according to the real-time update of the data such as the weather information of current year rice and meteorological biomass, dynamic adjusts meteorological The knot of index prediction model, meteorological index-meteorology biomass prediction model and meteorological biomass-Meteorological Output prediction model Fruit realizes the dynamic release of rice Meteorological Output;
3, can comprehensively, system, in time provide China's rice Meteorological Output wave process, intuitive and accurate rice is provided Meteorological Output prediction result, to ensure that the rice market supply and demand balance in China provides technical support.
Detailed description of the invention
By reference to the following drawings, exemplary embodiments of the present invention can be more fully understood by:
Fig. 1 is the flow chart according to the method for the determination rice Meteorological Output of the preferred embodiment for the present invention;
Fig. 2 is the structural schematic diagram according to the system of the determination rice Meteorological Output of the preferred embodiment for the present invention.
Specific embodiment
Exemplary embodiments of the present invention are introduced referring now to the drawings, however, the present invention can use many different shapes Formula is implemented, and is not limited to the embodiment described herein, and to provide these embodiments be at large and fully disclose The present invention, and the scope of the present invention is sufficiently conveyed to person of ordinary skill in the field.Show for what is be illustrated in the accompanying drawings Term in example property embodiment is not limitation of the invention.In the accompanying drawings, identical cells/elements use identical attached Icon note.
Unless otherwise indicated, term (including scientific and technical terminology) used herein has person of ordinary skill in the field It is common to understand meaning.Further it will be understood that with the term that usually used dictionary limits, should be understood as and its The context of related fields has consistent meaning, and is not construed as Utopian or too formal meaning.
Fig. 1 is the flow chart according to the method for the determination rice Meteorological Output of the preferred embodiment for the present invention.Such as Fig. 1 institute Show, the method 100 of determination rice Meteorological Output is since step 101 according to this preferred embodiment.
In step 101, according to the fertility feature of rice, the growth stage of rice is divided into several growthdevelopmental stages.? In this preferred embodiment, the growth stage of rice is divided into the insemination and emergence phase, transplanting time, hair tiller phase, boot stage, heading are opened 6 growthdevelopmental stages of florescence and pustulation period.
In step 102, acquisition influences the data of the meteorological index past n of rice growth and the number of current year known time When going over the data and each fertility of rice of n according to the data of the biomass past n of, each growthdevelopmental stage, economic flow rate The historical data of beginning and ending time phase.
In the preferred embodiment, historical data is mainly obtained from the database of major crop monitoring platform, current year The data of known time are mainly monitored by sensor and are obtained, wherein temperature is monitored by temperature sensor and obtained, and is calculated Every mean daily temperature, rice field day water layer height are obtained by monitoring in rice field surface layer placement force sensor.In practice, the water Rice biomass refers to the constant weight that rice is reached in the upgrowth of each growthdevelopmental stage with low temperature drying.
In step 103, current year each growthdevelopmental stage is determined according to the historical data of rice each growthdevelopmental stage beginning and ending time Beginning and ending time.In the preferred embodiment, number most time is fetched water in rice each growthdevelopmental stage beginning and ending time as working as The beginning and ending time of annual growing period.When there are two or more than two date number it is identical when, randomly choose one of them date.
In step 104, when determining each fertility of rice based on the data of the biomass past n of each growthdevelopmental stage of rice The data of the meteorological biomass past n of phase.
In step 105, the data of the meteorological index past n based on each growthdevelopmental stage of rice and meteorological biomass are gone over The data of n determine meteorological index-meteorology biomass prediction model of each growthdevelopmental stage of rice.
In step 106, the data of rice Meteorological Output past n are determined based on the data of rice economic flow rate past n. In practice, the rice economic flow rate refers to the dry matter weight of the major product rice harvested according to the cultivation purpose of rice.
In step 107, the data and rice Meteorological Output of the meteorological biomass past n based on each growthdevelopmental stage of rice The data of past n determine meteorological biomass-Meteorological Output prediction model of rice.
In step 108, the number of data and current year known time based on the meteorological index past n for influencing rice growth According to determining the data of the meteorological index of rice current year each growthdevelopmental stage according to the meteorological index prediction model of setting, wherein The meteorological index includes mean daily temperature, Daily minimum temperature, max. daily temperature and rice field day water layer height.
In step 109, the data of the meteorological index based on rice current year each growthdevelopmental stage, when fertility each according to rice The meteorological index of phase-meteorology biomass prediction model determines the meteorological biomass of rice current year each growthdevelopmental stage.
In step 110, based on the meteorological biomass of rice current year each growthdevelopmental stage, according to rice meteorology biomass-gas As Production Forecast Models, the Meteorological Output of rice current year is determined.
It is preferably based on the data of the data and current year known time that influence the meteorological index past n of rice growth, root According to the meteorological index prediction model of setting, determine that the meteorological index data of rice current year each growthdevelopmental stage include:
Based on the data for the meteorological index past n for influencing rice growth, according to the meteorological index prediction model of setting, really The meteorological index data of settled unknown time in year, in which:
The calculation formula of mean daily temperature prediction model are as follows:
When the max. daily temperature standard deviation determined according to the max. daily temperature of past certain day n is greater than or equal to according to certain day When the Daily minimum temperature standard deviation that the Daily minimum temperature of past n determines:
N is gone over according to certain day when the max. daily temperature standard deviation determined according to the max. daily temperature of past certain day n is less than When the Daily minimum temperature standard deviation that the Daily minimum temperature in year determines:
In formula, Tn aveIt is certain day mean daily temperature in the current year unknown time, Th minIt is certain in the current year unknown time Its minimum value in the Daily minimum temperature of past n, Th maxIt is certain day day highest in past n in the current year unknown time Maximum value in temperature, μminBe where certain day in unknown time current year month the Daily minimum temperature in past n mean value, μmaxBe where certain day in unknown time current year month the max. daily temperature in past n mean value, μaveWhen being unknown for the year Between in certain day where month mean value in the mean daily temperature of past n, σminIt is the moon where certain day in the current year unknown time Standard deviation of the part in the Daily minimum temperature of past n, σmaxIt is month where certain day in the current year unknown time in past n The standard deviation of max. daily temperature, σaveBe where certain day in unknown time current year month the mean daily temperature in past n mark Quasi- poor, χ is the daily standard normal deviation generated, according to two random number rnd1And rnd2It obtains;
The calculation formula of Daily minimum temperature prediction model are as follows:
When the max. daily temperature standard deviation determined according to certain day max. daily temperature in past n is greater than or equal to according to certain It is in the Daily minimum temperature standard deviation that the Daily minimum temperature of past n determines:
Tn minminmin×χ
When the max. daily temperature standard deviation determined according to certain day max. daily temperature in past n is less than according to certain day in mistake When the Daily minimum temperature standard deviation for going the Daily minimum temperature of n to determine:
In formula, Tn minIt is certain day Daily minimum temperature in the current year unknown time, Th maxIt is certain in the current year unknown time Its maximum value in the max. daily temperature of past n, μminIt is month where certain day in the current year unknown time in past n Daily minimum temperature mean value, μmaxMonth where certain day in unknown time current year past n max. daily temperature it is equal Value, σminBe where certain day in unknown time current year month the Daily minimum temperature in past n standard deviation, σmaxBe current year not Month where knowing certain day in the time, χ was that the daily standard normal of generation is inclined in the standard deviation of the max. daily temperature of past n Difference, according to two random number rnd1And rnd2It obtains;
The calculation formula of max. daily temperature prediction model are as follows:
When the max. daily temperature standard deviation determined according to certain day max. daily temperature in past n is greater than or equal to according to certain It is in the Daily minimum temperature standard deviation that the Daily minimum temperature of past n determines:
When the max. daily temperature standard deviation determined according to certain day max. daily temperature in past n is less than according to certain day in mistake When the Daily minimum temperature standard deviation for going the Daily minimum temperature of n to determine:
Tn maxmaxmax×χ
In formula, Tn maxIt is certain day max. daily temperature in the current year unknown time, Th minIt is certain in the current year unknown time Its minimum value in the Daily minimum temperature of past n, μminIt is month where certain day in the current year unknown time in past n Daily minimum temperature mean value, μmaxMonth where certain day in unknown time current year past n max. daily temperature it is equal Value, σminBe where certain day in unknown time current year month the Daily minimum temperature in past n standard deviation, σmaxBe current year not Month where knowing certain day in the time, χ was that the daily standard normal of generation is inclined in the standard deviation of the max. daily temperature of past n Difference, according to two random number rnd1And rnd2It obtains;
The calculation formula of rice field day water layer Height Prediction model are as follows:
H=μ+σH×χ
In formula, H is certain day rice field day water layer height in the current year unknown time, μHIt is certain day in the current year unknown time Place month the mean value in the rice field day water layer height of past n, σGMonth is in past n where certain day in the unknown time for the year The standard deviation of the rice field day water layer height in year, χ are the daily standard normal deviations of generation according to two random number rnd1And rnd2? It arrives;
By the meteorological index data of current year known time and the current year unknown time determining by meteorological index prediction model Meteorological index data divided according to the beginning and ending time of each growthdevelopmental stage of rice to get to each growthdevelopmental stage of rice Meteorological index data.
Preferably, the data of the biomass past n based on each growthdevelopmental stage of rice determine each fertility of rice Period meteorological biomass past n data include:
The data of the biomass past n of each growthdevelopmental stage of rice are generated into biomass sequence data in chronological order;
Using i as sliding step, with the linear slide method of average to the biomass of every i of each growthdevelopmental stage of rice into Row statistical regression analysis obtains j group unary linear regression equation, wherein 1≤i≤n, 1≤j≤i, i, j and n are natural numbers;
The analogue value of j annual biomass of each growthdevelopmental stage of rice is determined based on j group unary linear regression equation;
The analogue value of annual biomass is determined according to the analogue value of j annual biomass of each growthdevelopmental stage of rice Average value, and the trend biomass annual as each growthdevelopmental stage of rice;
The annual biomass of each growthdevelopmental stage of rice and trend biomass are subtracted each other as each growthdevelopmental stage of rice Annual meteorological biomass.
Preferably, the data and meteorological biomass mistake of the meteorological index past n based on each growthdevelopmental stage of rice Meteorological index-meteorology biomass the prediction model for going the data of n to determine each growthdevelopmental stage of rice includes:
The data of meteorological index past n based on each growthdevelopmental stage of rice and the data of meteorological biomass past n It determines kernel function, the weight of each kernel function of each meteorological index and meteorological biomass, and is sought according to kernel function determination The deviation of meteorological biomass;
Kernel function, the weight of each kernel function and deviation based on each meteorological index and meteorological biomass determine The meteorological index of each growthdevelopmental stage of rice-meteorology biomass prediction model, its calculation formula is:
In formula, yiIt is the meteorological biomass of rice i-th of growthdevelopmental stage of current year,It is rice i-th of growthdevelopmental stage of current year The kernel function of j-th of meteorological index, ωijIt is the weight of the kernel function of rice current year i-th of growthdevelopmental stage, j-th of meteorological index, biIt is according to kernel functionDetermine the deviation of the meteorological biomass of rice i-th of growthdevelopmental stage of current year.
In the preferred embodiment, the growth stage of rice be divided into the insemination and emergence phase, transplanting time, hair the tiller phase, boot stage, 6 growthdevelopmental stages of full heading time and pustulation period.In order to make meteorological index-meteorology biomass prediction model of each growthdevelopmental stage It is more accurate, for the lowest temperature angle value and maximum temperature value, mean daily temperature value and rice field day being arranged according to historical experience Water layer height has all carried out more specifically interval division, specifically:
The meteorological index in rice growing seeding stage-biomass prediction model calculation formula are as follows:
In formula, ybcFor insemination and emergence phase meteorology biomass, BCTDLRespectively sow out The kernel function weight of number of days of the Daily minimum temperature less than 10 DEG C, the kernel function of the meteorological index and the meteorological index in seedling stage, BCTDMNumber of days of the Daily minimum temperature between 10 DEG C -12 DEG C respectively in the insemination and emergence phase, should The kernel function weight of the kernel function of meteorological index and the meteorological index, BCTSLRespectively broadcast Number of days, the kernel function of the meteorological index and the core of the meteorological index of the mean daily temperature between 12 DEG C -20 DEG C in the kind seeding stage Function weight, BCTSMMean daily temperature is between 20 DEG C -23 DEG C respectively in the insemination and emergence phase Number of days, the kernel function of the meteorological index and the kernel function weight of the meteorological index, BCTSHNumber of days of the mean daily temperature between 23 DEG C -40 DEG C, the meteorology refer to respectively in the insemination and emergence phase The kernel function weight of target kernel function and the meteorological index, BCTGM Respectively insemination and emergence In phase max. daily temperature 40 DEG C of number of days, the kernel function of the meteorological index and the meteorological index kernel function weight, BCTGHNumber of days of the max. daily temperature greater than 40 DEG C, the meteorology respectively in the insemination and emergence phase The kernel function weight of the kernel function of index and the meteorological index, BCSCLRespectively sow out Rice field day water layer height is lower than number of days, the kernel function of the meteorological index and the core of the meteorological index of shoaling layer threshold value in seedling stage Function weight, BCSCMRice field day water layer height is in shoaling layer height respectively in the insemination and emergence phase Spend number of days, the kernel function of the meteorological index and the kernel function power of the meteorological index between threshold value and wettable layer height threshold Weight, BCSCHRice field day water layer height is greater than wet layer height threshold respectively in the insemination and emergence phase The kernel function weight of the number of days of value, the kernel function of the meteorological index and the meteorological index, bbcFor deviation.
The meteorological index of rice transplanting phase-biomass prediction model calculation formula are as follows:
In formula, yyzFor transplanting time meteorology biomass, YZTDLRespectively day in transplanting time The kernel function weight of number of days of the minimum temperature less than 13 DEG C, the kernel function of the meteorological index and the meteorological index, YZTDMNumber of days of the Daily minimum temperature between 13 DEG C -15 DEG C respectively in transplanting time, the meteorological index The kernel function weight of kernel function and the meteorological index, YZTSLRespectively transplanting time Nei Ping Equal number of days, the kernel function of the meteorological index and the kernel function weight of the meteorological index of the temperature between 15 DEG C -25 DEG C, YZTSM The core of number of days of the mean daily temperature between 25 DEG C -30 DEG C respectively in transplanting time, the meteorological index The kernel function weight of function and the meteorological index, YZTSHIt is respectively per day in transplanting time Number of days, the kernel function of the meteorological index and the kernel function weight of the meteorological index of the temperature between 30 DEG C -35 DEG C, YZTGMMax. daily temperature is in 35 DEG C of number of days, the kernel function of the meteorological index respectively in transplanting time And the kernel function weight of the meteorological index, YZTGHRespectively max. daily temperature in transplanting time The kernel function of number of days, the meteorological index greater than 40 DEG C and the kernel function weight of the meteorological index, YZSCLRice field day water layer height refers to lower than the number of days of shoaling layer threshold value, the meteorology respectively in transplanting time The kernel function weight of target kernel function and the meteorological index, YZSCM Respectively in transplanting time Number of days of the rice field day water layer height between shoaling layer height threshold and wettable layer height threshold, the meteorological index kernel function with And the kernel function weight of the meteorological index, YZSCHRice field day water layer is high respectively in transplanting time Degree is greater than number of days, the kernel function of the meteorological index and the kernel function weight of the meteorological index of wettable layer height threshold, byzFor Deviation.
The meteorological index of rice plant of tillering stage-biomass prediction model calculation formula are as follows:
In formula, yfnFor tillering period meteorology biomass, FNTDLRespectively day in tillering period The kernel function weight of number of days of the minimum temperature less than 15 DEG C, the kernel function of the meteorological index and the meteorological index, FNTDMNumber of days of the Daily minimum temperature between 15 DEG C -16 DEG C, the meteorological index respectively in tillering period Kernel function and the meteorological index kernel function weight, FNTSLRespectively day in tillering period Number of days, the kernel function of the meteorological index and the kernel function weight of the meteorological index of the mean temperature between 16 DEG C -23 DEG C, FNTSM Number of days of the mean daily temperature between 23 DEG C -32 DEG C, the meteorology refer to respectively in tillering period The kernel function weight of target kernel function and the meteorological index, FNTSHRespectively in tillering period Number of days, the kernel function of the meteorological index and the kernel function weight of the meteorological index of the mean daily temperature between 32 DEG C -38 DEG C, FNTGMRespectively in tillering period max. daily temperature 38 DEG C -50 DEG C number of days, the meteorology refers to The kernel function weight of target kernel function and the meteorological index, FNTGHRespectively tillering period Interior max. daily temperature is greater than 50 DEG C of number of days, the kernel function of the meteorological index and the kernel function weight of the meteorological index, FNSCM Rice field day water layer height is in shoaling layer height threshold and wettable layer respectively in tillering period The kernel function of number of days, the meteorological index between height threshold and the kernel function weight of the meteorological index, bfnFor deviation.
The meteorological index of Rise's boot period-biomass prediction model calculation formula are as follows:
In formula, yyzFor boot stage meteorology biomass, YSTDLRespectively day in boot stage The kernel function weight of number of days of the minimum temperature less than 15 DEG C, the kernel function of the meteorological index and the meteorological index, YSTDMDaily minimum temperature is in 15 DEG C of number of days, the kernel function of the meteorological index respectively in boot stage And the kernel function weight of the meteorological index, YSTSLRespectively mean daily temperature in boot stage The kernel function of number of days, the meteorological index between 15 DEG C -25 DEG C and the kernel function weight of the meteorological index, YSTSMNumber of days of the mean daily temperature between 25 DEG C -30 DEG C respectively in boot stage, the meteorological index The kernel function weight of kernel function and the meteorological index, YSTSHRespectively boot stage Nei Ping Equal number of days, the kernel function of the meteorological index and the kernel function weight of the meteorological index of the temperature between 30 DEG C -40 DEG C, YSTGMMax. daily temperature is in 40 DEG C of number of days, the kernel function of the meteorological index respectively in boot stage And the kernel function weight of the meteorological index, YSTGHRespectively max. daily temperature in boot stage The kernel function of number of days, the meteorological index greater than 40 DEG C and the kernel function weight of the meteorological index, YSSCLRice field day water layer height refers to lower than the number of days of shoaling layer threshold value, the meteorology respectively in boot stage The kernel function weight of target kernel function and the meteorological index, YSSCMRespectively in boot stage Number of days of the rice field day water layer height between shoaling layer height threshold and wettable layer height threshold, the meteorological index kernel function with And the kernel function weight of the meteorological index, YSSCHRice field day water layer height respectively in boot stage Greater than the kernel function weight of the number of days of wettable layer height threshold, the kernel function of the meteorological index and the meteorological index, bycIt is inclined Difference.
The meteorological index in Rice Heading florescence-biomass prediction model calculation formula are as follows:
In formula, yckFor full heading time meteorology biomass, CKTDLRespectively heading is opened The kernel function weight of number of days of the Daily minimum temperature less than 12 DEG C, the kernel function of the meteorological index and the meteorological index in florescence, CKTDMNumber of days, the gas of Daily minimum temperature at 12 DEG C -15 DEG C respectively in full heading time As the kernel function of index and the kernel function weight of the meteorological index, CKTSLRespectively heading is opened Number of days, the kernel function of the meteorological index and the kernel function of the meteorological index of the mean daily temperature between 15 DEG C -25 DEG C in florescence Weight, CKTSMDay of the mean daily temperature between 25 DEG C -32 DEG C respectively in full heading time The kernel function weight of number, the kernel function of the meteorological index and the meteorological index, CKTSHPoint Number of days of the mean daily temperature between 32 DEG C -40 DEG C, the kernel function of the meteorological index and the meteorology it Wei not refer in full heading time Target kernel function weight, CKTGM Respectively in full heading time max. daily temperature 40 DEG C- The kernel function weight of 45 DEG C of number of days, the kernel function of the meteorological index and the meteorological index, CKTGHNumber of days of the max. daily temperature greater than 45 DEG C, the meteorological index respectively in full heading time The kernel function weight of kernel function and the meteorological index, CKSCLRespectively in full heading time Kernel function power of the rice field day water layer height lower than the number of days of shoaling layer threshold value, the kernel function of the meteorological index and the meteorological index Weight, CKSCMRice field day water layer height is in shoaling layer height threshold respectively in full heading time The kernel function of number of days, the meteorological index between wettable layer height threshold and the kernel function weight of the meteorological index, CKSCHRice field day water layer height is greater than wettable layer height threshold respectively in full heading time Number of days, the kernel function of the meteorological index and the kernel function weight of the meteorological index, bckFor deviation.
The meteorological index of Grain Filling-biomass prediction model calculation formula are as follows:
In formula, ygjFor pustulation period meteorology biomass, GJTDLDay is most respectively in the pustulation period The kernel function weight of number of days of the low temperature less than 18 DEG C, the kernel function of the meteorological index and the meteorological index, GJTDMRespectively in the pustulation period Daily minimum temperature 18 DEG C number of days, the meteorological index kernel function with And the kernel function weight of the meteorological index, GJTSLRespectively mean daily temperature exists in the pustulation period The kernel function of number of days, the meteorological index between 18 DEG C -22 DEG C and the kernel function weight of the meteorological index, GJTSMThe core of number of days of the mean daily temperature between 22 DEG C -28 DEG C respectively in the pustulation period, the meteorological index The kernel function weight of function and the meteorological index, GJTSHIt is respectively per day in the pustulation period Number of days, the kernel function of the meteorological index and the kernel function weight of the meteorological index of the temperature between 28 DEG C -35 DEG C, GJTGMRespectively in the pustulation period max. daily temperature 35 DEG C number of days, the meteorological index kernel function with And the kernel function weight of the meteorological index, GJTGHGJ(YSTGH)、Max. daily temperature is greater than 35 respectively in the pustulation period DEG C number of days, the kernel function of the meteorological index and the kernel function weight of the meteorological index, GJSCMRice field day water layer height is in shoaling layer height threshold and wet layer height respectively in the pustulation period The kernel function of number of days, the meteorological index between threshold value and the kernel function weight of the meteorological index, bgjFor deviation.
Preferably, the data based on rice economic flow rate past n determine the data of rice Meteorological Output past n Include:
The data of rice economic flow rate past n are generated into economic flow rate sequence data in chronological order;
Using i as sliding step, statistical regression point is carried out with the economic flow rate of linear slide method of average i every to rice Analysis, obtains j group unary linear regression equation, wherein 1≤i≤n, 1≤j≤i, i, j and n are natural numbers;
The analogue value of j annual economic flow rate of rice is determined based on j group unary linear regression equation;
The average value of the analogue value of annual economic flow rate is determined according to the analogue value of j annual economic flow rate of rice, And the trend economic flow rate annual as rice;
The annual economic flow rate of rice and trend economic flow rate are subtracted each other to the Meteorological Output annual as rice.
It is preferably based on the data and rice Meteorological Output mistake of the meteorological biomass past n of each growthdevelopmental stage of rice The data of n are gone to determine that rice meteorology biomass-Meteorological Output prediction model includes:
The data and rice Meteorological Output of meteorological biomass past n based on each growthdevelopmental stage of rice go over n's Data determine the meteorological biomass of each growthdevelopmental stage and the kernel function of Meteorological Output, the weight of each kernel function, and according to Kernel function determines the deviation for seeking Meteorological Output;
Kernel function, the weight of each kernel function of meteorological biomass and Meteorological Output based on each growthdevelopmental stage of rice, And deviation determines rice meteorology biomass-Meteorological Output prediction model, its calculation formula is:
In formula, y is the Meteorological Output of rice current year,It is the core letter of rice i-th of growthdevelopmental stage meteorology biomass of current year Number, ωiIt is the weight of the kernel function of rice i-th of growthdevelopmental stage of current year, b is according to kernel functionDetermine the meteorology of rice current year The deviation of yield.
In the preferred embodiment, the growth stage of rice is divided into sowing time, seedling stage, jointing-booting stage, heading are bloomed 5 phase, grouting parameter growthdevelopmental stages.It corresponds, the meteorological biomass of each growthdevelopmental stage of rice and meteorological production The calculation formula of the prediction model of amount are as follows:
In formula, z is rice Meteorological Output, ybcRespectively rice growing seeding stage biomass, rice Insemination and emergence phase biomass kernel function and kernel function weight, yyzRespectively rice transplanting phase biomass, water Rice transplanting time biomass kernel function and kernel function weight, yfnwfnRespectively rice plant of tillering stage biomass, rice point Tiller phase biomass kernel function and kernel function weight, yysRespectively Rise's boot period biomass, rice booting Phase biomass kernel function and kernel function weight, yckRespectively Rice Heading florescence biomass, rice are taken out Tassel blossom phase biomass kernel function and kernel function weight, ygjRespectively Grain Filling biomass, rice Pustulation period biomass kernel function and kernel function weight, b are deviation.
Fig. 2 is the structural schematic diagram according to the system of the determination rice Meteorological Output of the preferred embodiment for the present invention.Such as Fig. 2 Shown, the system 200 of determination rice Meteorological Output described in this preferred embodiment includes:
Growth period duration of rice division unit 201 is used for the fertility feature according to rice, the growth stage of rice is divided into Several growthdevelopmental stages;
Time breeding time determination unit 202 is used for true according to the historical data of rice each growthdevelopmental stage beginning and ending time The beginning and ending time of settled year each growthdevelopmental stage.
Data acquisition unit 203 has been used to acquire the data for influencing the meteorological index past n of rice growth and current year Know the data of the data of time, the data of the biomass past n of each growthdevelopmental stage and economic flow rate past n.
First data cell 204 is used to determine water based on the data of the biomass past n of each growthdevelopmental stage of rice The data of the meteorological biomass past n of each growthdevelopmental stage of rice.
First model unit 205, the data for being used for the meteorological index past n based on each growthdevelopmental stage of rice are gentle As the data of biomass past n determine meteorological index-meteorology biomass prediction model of each growthdevelopmental stage of rice.
Second data cell 206, the data for being used to go over based on rice economic flow rate n determine rice Meteorological Output mistake Go the data of n.
Second model unit 207, be used for based on each growthdevelopmental stage of rice meteorological biomass past n data with The data of rice Meteorological Output past n determine meteorological biomass-Meteorological Output prediction model of rice.
Rice meteorological index unit 208 is used for the data based on the meteorological index past n for influencing rice growth and works as The data of year known time determine that the meteorology of rice current year each growthdevelopmental stage refers to according to the meteorological index prediction model of setting Target data, wherein the meteorological index includes that mean daily temperature, Daily minimum temperature, max. daily temperature and rice field day water layer are high Degree.
Rice meteorology biomass unit 209 is used for the data of the meteorological index based on rice current year each growthdevelopmental stage, According to the meteorological index of each growthdevelopmental stage of rice-meteorology biomass prediction model, rice current year each growthdevelopmental stage is determined Meteorological biomass.
Rice Meteorological Output unit 210 is used for the meteorological biomass based on rice current year each growthdevelopmental stage, according to water Rice meteorology biomass-Meteorological Output prediction model, determines the Meteorological Output of rice current year.
Preferably, the rice meteorological index unit 208 includes:
Unknown meteorological index unit 281 is used for the data based on the meteorological index past n for influencing rice growth, root According to the meteorological index prediction model of setting, the meteorological index data of current year unknown time are determined, wherein the mean daily temperature, The calculation formula of Daily minimum temperature, max. daily temperature and rice field day water layer Height Prediction model and the side for determining rice Meteorological Output Identical in method, details are not described herein again.
Index determination unit 282 is used to predict the meteorological index data of current year known time with by meteorological index The meteorological index data for the current year unknown time that model determines are divided according to the beginning and ending time of each growthdevelopmental stage of rice, i.e., Obtain the meteorological index data of each growthdevelopmental stage of rice.
Preferably, first data cell 204 includes:
First ray unit 241 is used for the data of the biomass past n of each growthdevelopmental stage of rice are temporally suitable Sequence generates biomass sequence data;
First equation group unit 242 is used for using i as sliding step, each to rice with the linear slide method of average The biomass of every i of growthdevelopmental stage carries out statistical regression analysis, obtains j group unary linear regression equation, wherein 1≤i≤n, 1≤j≤i, i, j and n are natural numbers;
First simulation value cell 243, is used to determine that each growthdevelopmental stage of rice is every based on j group unary linear regression equation The analogue value of the j biomass in year;
First trend value cell 244 is used for true according to the analogue value of j annual biomass of each growthdevelopmental stage of rice The average value of the analogue value of fixed annual biomass, and the trend biomass annual as each growthdevelopmental stage of rice;
First result unit 245 is used for the annual biomass of each growthdevelopmental stage of rice and trend biomass phase Subtract the annual meteorological biomass as each growthdevelopmental stage of rice.
Preferably, first model unit 205 includes:
First parameters unit 251, the data for being used for the meteorological index past n based on each growthdevelopmental stage of rice are gentle As biomass past n data determine each meteorological index with meteorology biomass kernel function, the weight of each kernel function, with And the deviation for seeking meteorological biomass is determined according to kernel function;
First formula cells 252 are used for kernel function, each kernel function based on each meteorological index and meteorological biomass Weight and deviation determine meteorological index-meteorology biomass prediction model of each growthdevelopmental stage of rice, calculation formula Are as follows:
In formula, yiIt is the meteorological biomass of rice i-th of growthdevelopmental stage of current year,It is rice i-th of growthdevelopmental stage of current year The kernel function of j-th of meteorological index, ωijIt is the weight of the kernel function of rice current year i-th of growthdevelopmental stage, j-th of meteorological index, biIt is according to kernel functionDetermine the deviation of the meteorological biomass of rice i-th of growthdevelopmental stage of current year.
Preferably, second data cell 206 includes:
Second sequence units 261 are used to generating the data that rice economic flow rate goes over n into economic production in chronological order Measure sequence data;
Second equation group unit 262 is used for using i as sliding step, with linear slide method of average i every to rice Economic flow rate carry out statistical regression analysis, obtain j group unary linear regression equation, wherein 1≤i≤n, 1≤j≤i, i, j and N is natural number;
Second simulation value cell 263 is used to determine j annual economy of rice based on j group unary linear regression equation The analogue value of yield;
Second trend value cell 264 is used to determine annual warp according to the analogue value of j annual economic flow rate of rice The average value of the analogue value for yield of helping, and the trend economic flow rate annual as rice;
Second result unit 265 subtracts each other the annual economic flow rate of rice and trend economic flow rate annual as rice Meteorological Output.
Preferably, second model unit 207 includes:
Second parameters unit 271, be used for based on each growthdevelopmental stage of rice meteorological biomass past n data with The data of rice Meteorological Output past n determine the meteorological biomass of each growthdevelopmental stage and the kernel function of Meteorological Output, each The weight of kernel function, and the deviation for seeking Meteorological Output is determined according to kernel function;
Second formula cells 272 are used for the core of meteorological biomass and Meteorological Output based on each growthdevelopmental stage of rice Function, the weight of each kernel function and deviation determine rice meteorology biomass-Meteorological Output prediction model, calculate public Formula are as follows:
In formula, y is the Meteorological Output of rice current year,It is the core letter of rice i-th of growthdevelopmental stage meteorology biomass of current year Number, ωiIt is the weight of the kernel function of rice i-th of growthdevelopmental stage of current year, b is according to kernel functionDetermine the meteorology of rice current year The deviation of yield.
The present invention is described by reference to a small amount of embodiment.However, it is known in those skilled in the art, as Defined by subsidiary Patent right requirement, in addition to the present invention other embodiments disclosed above equally fall in it is of the invention In range.
Normally, all terms used in the claims are all solved according to them in the common meaning of technical field It releases, unless in addition clearly being defined wherein.All references " one/described/be somebody's turn to do [device, component etc.] " are all opened ground At least one example being construed in described device, component etc., unless otherwise expressly specified.Any method disclosed herein Step need not all be run with disclosed accurate sequence, unless explicitly stated otherwise.

Claims (14)

1. a kind of method of determining rice Meteorological Output, which is characterized in that the described method includes:
The data of data and current year known time based on the meteorological index past n for influencing rice growth, according to the gas of setting As index prediction model, the data of the meteorological index of rice current year each growthdevelopmental stage are determined, wherein the meteorological index includes Mean daily temperature, Daily minimum temperature, max. daily temperature and rice field day water layer height;
The data of meteorological index based on rice current year each growthdevelopmental stage, according to the meteorological index-of each growthdevelopmental stage of rice Meteorological biomass prediction model determines the meteorological biomass of rice current year each growthdevelopmental stage;
Based on the meteorological biomass of rice current year each growthdevelopmental stage, according to rice meteorology biomass-Meteorological Output prediction model, Determine the Meteorological Output of rice current year.
2. the method according to claim 1, wherein the method is based on the meteorological index for influencing rice growth The data of past n and the data of current year known time determine that rice current year is each according to the meteorological index prediction model of setting Before the data of the meteorological index of growthdevelopmental stage further include:
According to the fertility feature of rice, the growth stage of rice is divided into several growthdevelopmental stages;
Acquisition influences the data of the meteorological index past n of rice growth and data, each growthdevelopmental stage of current year known time The biomass past data of n, economic flow rate go over the data of n and going through for rice each growthdevelopmental stage beginning and ending time History data;
The beginning and ending time of current year each growthdevelopmental stage is determined according to the historical data of rice each growthdevelopmental stage beginning and ending time;
The meteorological biomass of each growthdevelopmental stage of rice is determined based on the data of the biomass past n of each growthdevelopmental stage of rice The data of past n;
The data of data and meteorological biomass past n based on the meteorological index past n of each growthdevelopmental stage of rice determine The meteorological index of each growthdevelopmental stage of rice-meteorology biomass prediction model;
The data of rice Meteorological Output past n are determined based on the data of rice economic flow rate past n;
The data of meteorological biomass past n based on each growthdevelopmental stage of rice and the data of rice Meteorological Output past n Determine meteorological biomass-Meteorological Output prediction model of rice.
3. the method according to claim 1, wherein based on the meteorological index past n's for influencing rice growth The data of data and current year known time determine rice current year each growthdevelopmental stage according to the meteorological index prediction model of setting Meteorological index data include:
Based on the data for the meteorological index past n for influencing rice growth, according to the meteorological index prediction model of setting, determination is worked as The meteorological index data of unknown time in year, in which:
The calculation formula of mean daily temperature prediction model are as follows:
Existed when the max. daily temperature standard deviation determined according to certain day max. daily temperature in past n is greater than or equal to according to certain day When the Daily minimum temperature standard deviation that the Daily minimum temperature of past n determines:
When the max. daily temperature standard deviation determined according to certain day max. daily temperature in past n is less than according to certain day in past n When the Daily minimum temperature standard deviation that the Daily minimum temperature in year determines:
In formula, TnaveIt is certain day mean daily temperature in the current year unknown time, ThminIt is certain day in the current year unknown time in mistake Remove the minimum value in the Daily minimum temperature of n, ThmaxIt is certain day in the current year unknown time in the max. daily temperature of past n Maximum value, μminBe where certain day in unknown time current year month the Daily minimum temperature in past n mean value, μmaxIt is to work as Where certain day in year unknown time month max. daily temperature in past n mean value, μaveIt is certain in the current year unknown time Mean value of the month in the mean daily temperature of past n, σ where itminIt was month where certain day in the current year unknown time in the past The standard deviation of the Daily minimum temperature of n, σmaxIt is month where certain day in the current year unknown time in the day highest temperature of past n The standard deviation of degree, σaveBe where certain day in unknown time current year month the mean daily temperature in past n standard deviation, χ is The daily standard normal deviation generated, according to two random number rnd1And rnd2It obtains;
The calculation formula of Daily minimum temperature prediction model are as follows:
Existed when the max. daily temperature standard deviation determined according to certain day max. daily temperature in past n is greater than or equal to according to certain day When the Daily minimum temperature standard deviation that the Daily minimum temperature of past n determines:
Tnminminmin×χ
When the max. daily temperature standard deviation determined according to certain day max. daily temperature in past n is less than according to certain day in past n When the Daily minimum temperature standard deviation that the Daily minimum temperature in year determines:
In formula, TnminIt is certain day Daily minimum temperature in the current year unknown time, ThmaxIt is certain day in the current year unknown time in mistake Remove the maximum value in the max. daily temperature of n, μminMonth where certain day in unknown time current year past n day most The mean value of low temperature, μmaxBe where certain day in unknown time current year month the max. daily temperature in past n mean value, σmin Be where certain day in unknown time current year month the Daily minimum temperature in past n standard deviation, σmaxIt is the current year unknown time In certain day where month the max. daily temperature of past n standard deviation, χ be generation daily standard normal deviation, according to Two random number rnd1And rnd2It obtains;
The calculation formula of max. daily temperature prediction model are as follows:
Existed when the max. daily temperature standard deviation determined according to certain day max. daily temperature in past n is greater than or equal to according to certain day When the Daily minimum temperature standard deviation that the Daily minimum temperature of past n determines:
When the max. daily temperature standard deviation determined according to certain day max. daily temperature in past n is less than according to certain day in past n When the Daily minimum temperature standard deviation that the Daily minimum temperature in year determines:
Tnmaxmaxmax×χ
In formula, TnmaxIt is certain day max. daily temperature in the current year unknown time, ThminIt is certain day in the current year unknown time in mistake Remove the minimum value in the Daily minimum temperature of n, μminMonth where certain day in unknown time current year past n day most The mean value of low temperature, μmaxBe where certain day in unknown time current year month the max. daily temperature in past n mean value, σmin Be where certain day in unknown time current year month the Daily minimum temperature in past n standard deviation, σmaxIt is the current year unknown time In certain day where month the max. daily temperature of past n standard deviation, χ be generation daily standard normal deviation, according to Two random number rnd1And rnd2It obtains;
The calculation formula of rice field day water layer Height Prediction model are as follows:
H=μHH×χ
In formula, H is certain day rice field day water layer height in the current year unknown time, μHIt is certain day place in the current year unknown time Month the mean value in the rice field day water layer height of past n, σGMonth is past n's where certain day in the unknown time for the year The standard deviation of rice field day water layer height, χ are the daily standard normal deviations of generation according to two random number rnd1And rnd2It obtains;
By the gas of the meteorological index data of current year known time and the current year unknown time determined by meteorological index prediction model As achievement data according to the beginning and ending time of each growthdevelopmental stage of rice divided to get arrive each growthdevelopmental stage of rice meteorology Achievement data.
4. according to the method described in claim 2, it is characterized in that, the biomass based on each growthdevelopmental stage of rice is gone over The data of n determine that the data of the meteorological biomass past n of each growthdevelopmental stage of rice include:
The data of the biomass past n of each growthdevelopmental stage of rice are generated into biomass sequence data in chronological order;
Using i as sliding step, unite with biomass of the linear slide method of average to every i of each growthdevelopmental stage of rice Regression analysis is counted, obtains j group unary linear regression equation, wherein 1≤i≤n, 1≤j≤i, i, j and n are natural numbers;
The analogue value of j annual biomass of each growthdevelopmental stage of rice is determined based on j group unary linear regression equation;
Being averaged for the analogue value of annual biomass is determined according to the analogue value of j annual biomass of each growthdevelopmental stage of rice Value, and the trend biomass annual as each growthdevelopmental stage of rice;
The annual biomass of each growthdevelopmental stage of rice and trend biomass are subtracted each other as the every of each growthdevelopmental stage of rice The meteorological biomass in year.
5. according to the method described in claim 2, it is characterized in that, the meteorological index mistake based on each growthdevelopmental stage of rice The data of the data and meteorological biomass past n of removing n determine meteorological index-meteorology biomass of each growthdevelopmental stage of rice Prediction model includes:
The data of data and meteorological biomass past n based on the meteorological index past n of each growthdevelopmental stage of rice determine Kernel function, the weight of each kernel function of each meteorological index and meteorological biomass, and meteorology is sought according to kernel function determination The deviation of biomass;
Kernel function, the weight of each kernel function and deviation based on each meteorological index and meteorological biomass determine rice The meteorological index of each growthdevelopmental stage-meteorology biomass prediction model, its calculation formula is:
In formula, yiIt is the meteorological biomass of rice i-th of growthdevelopmental stage of current year,It is i-th j-th of growthdevelopmental stage of rice current year The kernel function of meteorological index, ωijIt is the weight of the kernel function of rice current year i-th of growthdevelopmental stage, j-th of meteorological index, biIt is root According to kernel functionDetermine the deviation of the meteorological biomass of rice i-th of growthdevelopmental stage of current year.
6. according to the method described in claim 2, it is characterized in that, the data based on rice economic flow rate past n are true Determine rice Meteorological Output past n data include:
The data of rice economic flow rate past n are generated into economic flow rate sequence data in chronological order;
Using i as sliding step, statistical regression analysis is carried out with the economic flow rate of linear slide method of average i every to rice, Obtain j group unary linear regression equation, wherein 1≤i≤n, 1≤j≤i, i, j and n are natural numbers;
The analogue value of j annual economic flow rate of rice is determined based on j group unary linear regression equation;
The average value of the analogue value of annual economic flow rate is determined according to the analogue value of j annual economic flow rate of rice, and will Its trend economic flow rate annual as rice;
The annual economic flow rate of rice and trend economic flow rate are subtracted each other to the Meteorological Output annual as rice.
7. according to the method described in claim 2, it is characterized in that, the meteorological biomass based on each growthdevelopmental stage of rice is gone over The data of data and rice Meteorological Output the past n of n determine rice meteorology biomass-Meteorological Output prediction model packet It includes:
The data of meteorological biomass past n based on each growthdevelopmental stage of rice and the data of rice Meteorological Output past n Determine the meteorological biomass of each growthdevelopmental stage and the kernel function of Meteorological Output, the weight of each kernel function, and according to core letter Number determines the deviation for seeking Meteorological Output;
Kernel function, the weight of each kernel function of meteorological biomass and Meteorological Output based on each growthdevelopmental stage of rice, and Deviation determines rice meteorology biomass-Meteorological Output prediction model, its calculation formula is:
In formula, y is the Meteorological Output of rice current year,It is the kernel function of rice i-th of growthdevelopmental stage meteorology biomass of current year, ωiIt is the weight of the kernel function of rice i-th of growthdevelopmental stage of current year, b is according to kernel functionDetermine that the meteorological of rice current year produces The deviation of amount.
8. a kind of system of determining rice Meteorological Output, which is characterized in that the system comprises:
Rice meteorological index unit was used for known to data and current year based on the meteorological index past n for influencing rice growth The data of time determine the number of the meteorological index of rice current year each growthdevelopmental stage according to the meteorological index prediction model of setting According to, wherein the meteorological index includes mean daily temperature, Daily minimum temperature, max. daily temperature and rice field day water layer height;
Rice meteorology biomass unit is used for the data of the meteorological index based on rice current year each growthdevelopmental stage, according to water The meteorological index of each growthdevelopmental stage of rice-meteorology biomass prediction model determines that the meteorology of rice current year each growthdevelopmental stage is raw Object amount;
Rice Meteorological Output unit is used for the meteorological biomass based on rice current year each growthdevelopmental stage, according to rice meteorology Biomass-Meteorological Output prediction model, determines the Meteorological Output of rice current year.
9. system according to claim 8, which is characterized in that system further include:
Growth period duration of rice division unit, is used for the fertility feature according to rice, and the growth stage of rice is divided into several Growthdevelopmental stage;
Data acquisition unit is used to acquire the data and current year known time for influencing the meteorological index past n of rice growth Data, the biomass past data of n of each growthdevelopmental stage, economic flow rate go over the data and each life of rice of n Educate the historical data of beginning and ending time in period;
Time breeding time determination unit is used to determine that current year is every according to the historical data of rice each growthdevelopmental stage beginning and ending time The beginning and ending time of a growthdevelopmental stage;
First data cell is used to determine that rice is each based on the data of the biomass past n of each growthdevelopmental stage of rice The data of the meteorological biomass past n of growthdevelopmental stage;
First model unit is used for the data and meteorology biology of the meteorological index past n based on each growthdevelopmental stage of rice The data of amount past n determine meteorological index-meteorology biomass prediction model of each growthdevelopmental stage of rice;
Second data cell is used to determine rice Meteorological Output past n's based on the data that rice economic flow rate goes over n Data;
Second model unit is used for the data and rice gas of the meteorological biomass past n based on each growthdevelopmental stage of rice As the data of yield past n determine meteorological biomass-Meteorological Output prediction model of rice.
10. system according to claim 8, which is characterized in that the rice meteorological index unit includes:
Unknown meteorological index unit is used for the data based on the meteorological index past n for influencing rice growth, according to setting Meteorological index prediction model determines the meteorological index data of current year unknown time, in which:
The calculation formula of mean daily temperature prediction model are as follows:
Gone over when the max. daily temperature standard deviation determined according to the max. daily temperature of past certain day n is greater than or equal to according to certain day When the Daily minimum temperature standard deviation that the Daily minimum temperature of n determines:
When the max. daily temperature standard deviation determined according to the max. daily temperature of past certain day n is less than according to past certain day n's When the Daily minimum temperature standard deviation that Daily minimum temperature determines:
In formula, TnaveIt is the mean daily temperature in the current year unknown time with identical certain day in the data of past n, ThminIt was Remove the minimum value in certain day in the data of n Daily minimum temperature, ThmaxIt is certain day day highest in the data of past n Maximum value in temperature, μminIt is the mean value of the Daily minimum temperature in month where certain day in the data of past n, μmaxIt is the past The mean value of the max. daily temperature in month, μ where certain day in the data of naveIt is the moon where certain day in the data of past n The mean value of the mean daily temperature of part, σminIt is the standard deviation of the Daily minimum temperature in month where certain day in the data of past n, σmaxIt is the standard deviation of the max. daily temperature in month where certain day in the data of past n, σaveIt is in the data of past n The standard deviation of the mean daily temperature in month where certain day, χ is the daily standard normal deviation generated, according to two random number rnd1 And rnd2It obtains;
The calculation formula of Daily minimum temperature prediction model are as follows:
Existed when the max. daily temperature standard deviation determined according to certain day max. daily temperature in past n is greater than or equal to according to certain day When the Daily minimum temperature standard deviation that the Daily minimum temperature of past n determines:
Tnminminmin×χ
When the max. daily temperature standard deviation determined according to certain day max. daily temperature in past n is less than according to certain day in past n When the Daily minimum temperature standard deviation that the Daily minimum temperature in year determines:
In formula, TnminIt is certain day Daily minimum temperature in the current year unknown time, ThmaxIt is certain day in the current year unknown time in mistake Remove the maximum value in the max. daily temperature of n, μminMonth where certain day in unknown time current year past n day most The mean value of low temperature, μmaxBe where certain day in unknown time current year month the max. daily temperature in past n mean value, σmin Be where certain day in unknown time current year month the Daily minimum temperature in past n standard deviation, σmaxIt is the current year unknown time In certain day where month the max. daily temperature of past n standard deviation, χ be generation daily standard normal deviation, according to Two random number rnd1And rnd2It obtains;
The calculation formula of max. daily temperature prediction model are as follows:
Existed when the max. daily temperature standard deviation determined according to certain day max. daily temperature in past n is greater than or equal to according to certain day When the Daily minimum temperature standard deviation that the Daily minimum temperature of past n determines:
When the max. daily temperature standard deviation determined according to certain day max. daily temperature in past n is less than according to certain day in past n When the Daily minimum temperature standard deviation that the Daily minimum temperature in year determines:
Tnmaxmaxmax×χ
In formula, TnmaxIt is certain day max. daily temperature in the current year unknown time, ThminIt is certain day in the current year unknown time in mistake Remove the minimum value in the Daily minimum temperature of n, μminMonth where certain day in unknown time current year past n day most The mean value of low temperature, μmaxBe where certain day in unknown time current year month the max. daily temperature in past n mean value, σmin Be where certain day in unknown time current year month the Daily minimum temperature in past n standard deviation, σmaxIt is the current year unknown time In certain day where month the max. daily temperature of past n standard deviation, χ be generation daily standard normal deviation, according to Two random number rnd1And rnd2It obtains;
The calculation formula of rice field day water layer Height Prediction model are as follows:
H=μHH×χ
In formula, H is certain day rice field day water layer height in the current year unknown time, μHIt is certain day place in the current year unknown time Month the mean value in the rice field day water layer height of past n, σGMonth is past n's where certain day in the unknown time for the year The standard deviation of rice field day water layer height, χ are the daily standard normal deviations of generation according to two random number rnd1And rnd2It obtains;
Index determination unit is used to determine the meteorological index data of current year known time with by meteorological index prediction model The meteorological index data of current year unknown time divided according to the beginning and ending time of each growthdevelopmental stage of rice to get to rice The meteorological index data of each growthdevelopmental stage.
11. system according to claim 9, which is characterized in that first data cell includes:
First ray unit is used in chronological order generate the data of the biomass past n of each growthdevelopmental stage of rice Biomass sequence data;
First equation group unit is used for using i as sliding step, with the linear slide method of average to each growthdevelopmental stage of rice Every i biomass carry out statistical regression analysis, obtain j group unary linear regression equation, wherein 1≤i≤n, 1≤j≤i, I, j and n is natural number;
First simulation value cell, is used to determine each growthdevelopmental stage of rice annual j based on j group unary linear regression equation The analogue value of biomass;
First trend value cell is used to be determined according to the analogue value of j annual biomass of each growthdevelopmental stage of rice annual Biomass the analogue value average value, and the trend biomass annual as each growthdevelopmental stage of rice;
First result unit is used to subtract each other the annual biomass of each growthdevelopmental stage of rice and trend biomass as water The annual meteorological biomass of each growthdevelopmental stage of rice.
12. system according to claim 9, which is characterized in that first model unit includes:
First parameters unit is used for the data and meteorology biology of the meteorological index past n based on each growthdevelopmental stage of rice Amount in the past n data determine each meteorological index with meteorology biomass kernel function, the weight of each kernel function, and according to Kernel function determines the deviation for seeking meteorological biomass;
First formula cells are used for kernel function, the weight of each kernel function based on each meteorological index and meteorological biomass, And deviation determines meteorological index-meteorology biomass prediction model of each growthdevelopmental stage of rice, its calculation formula is:
In formula, yiIt is the meteorological biomass of rice i-th of growthdevelopmental stage of current year,It is rice i-th of growthdevelopmental stage jth of current year The kernel function of a meteorological index, ωijIt is the weight of the kernel function of rice current year i-th of growthdevelopmental stage, j-th of meteorological index, biIt is According to kernel functionDetermine the deviation of the meteorological biomass of rice i-th of growthdevelopmental stage of current year.
13. system according to claim 9, which is characterized in that second data cell includes:
Second sequence units, the data for being used to pass by rice economic flow rate n generate economic flow rate sequence in chronological order Data;
Second equation group unit is used for using i as sliding step, with the economy of linear slide method of average i every to rice Yield carries out statistical regression analysis, obtains j group unary linear regression equation, wherein 1≤i≤n, 1≤j≤i, i, j and n are Natural number;
Second simulation value cell, is used to determine the mould of j annual economic flow rate of rice based on j group unary linear regression equation Analog values;
Second trend value cell is used to determine annual economic flow rate according to the analogue value of j annual economic flow rate of rice The analogue value average value, and the trend economic flow rate annual as rice;
The annual economic flow rate of rice and trend economic flow rate are subtracted each other the meteorological production annual as rice by the second result unit Amount.
14. system according to claim 9, which is characterized in that second model unit includes:
Second parameters unit is used for the data and rice gas of the meteorological biomass past n based on each growthdevelopmental stage of rice As the data of yield past n determine the meteorological biomass of each growthdevelopmental stage and the kernel function of Meteorological Output, each kernel function Weight, and determined according to kernel function and seek the deviation of Meteorological Output;
Second formula cells are used for the kernel function, every of meteorological biomass and Meteorological Output based on each growthdevelopmental stage of rice The weight and deviation of a kernel function determine rice meteorology biomass-Meteorological Output prediction model, its calculation formula is:
In formula, y is the Meteorological Output of rice current year,It is the kernel function of rice i-th of growthdevelopmental stage meteorology biomass of current year, ωiIt is the weight of the kernel function of rice i-th of growthdevelopmental stage of current year, b is according to kernel functionDetermine that the meteorological of rice current year produces The deviation of amount.
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