CN111047096A - Regional water and soil loss daily forecasting algorithm - Google Patents
Regional water and soil loss daily forecasting algorithm Download PDFInfo
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- 239000002689 soil Substances 0.000 title claims abstract description 59
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 title claims abstract description 57
- 238000012544 monitoring process Methods 0.000 claims abstract description 29
- 230000007613 environmental effect Effects 0.000 claims abstract description 28
- 238000012806 monitoring device Methods 0.000 claims abstract description 16
- 238000009826 distribution Methods 0.000 claims abstract description 14
- 238000000034 method Methods 0.000 claims abstract description 10
- 238000012545 processing Methods 0.000 claims description 4
- 238000006467 substitution reaction Methods 0.000 claims description 3
- 238000010586 diagram Methods 0.000 description 9
- 238000004162 soil erosion Methods 0.000 description 9
- 239000011159 matrix material Substances 0.000 description 7
- 230000008901 benefit Effects 0.000 description 3
- 238000004364 calculation method Methods 0.000 description 3
- 238000012271 agricultural production Methods 0.000 description 2
- 230000003044 adaptive effect Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000007796 conventional method Methods 0.000 description 1
- 238000005520 cutting process Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000035558 fertility Effects 0.000 description 1
- 230000002068 genetic effect Effects 0.000 description 1
- 238000009776 industrial production Methods 0.000 description 1
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- 238000013507 mapping Methods 0.000 description 1
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
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- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/12—Computing arrangements based on biological models using genetic models
- G06N3/126—Evolutionary algorithms, e.g. genetic algorithms or genetic programming
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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Abstract
The invention discloses a regional water and soil loss daily forecasting algorithm, belonging to the technical field of water and soil loss, comprising the following steps: the method comprises the following steps: installing corresponding monitoring devices according to the plurality of monitoring points; step two: drawing a density image according to monitoring data on the monitoring points; step three: obtaining the influence size distribution condition of the factors according to each environment influence factor; step four: obtaining optimal water and soil loss influence factor data according to the size and the density image influenced by the environmental factors; step five: and obtaining data of the water and soil loss day according to the optimal data, predicting the water and soil loss day, drawing a uniform density map by counting the existing data and selecting and counting rainfall, temperature and humidity and annual occurrence amount of natural disasters, adjusting the influence proportion of the natural disasters according to main and secondary factors influencing the water and soil loss, obtaining a final density map, and obtaining the predicted water and soil loss day according to the density map, wherein the accuracy is higher.
Description
Technical Field
The invention relates to the technical field of water and soil loss, in particular to a regional water and soil loss daily forecasting algorithm.
Background
The water and soil loss refers to the phenomenon that water and soil are simultaneously lost due to the influence of natural or artificial factors, rainwater cannot be absorbed on the spot, flows down along the same trend and scours the soil. The main reasons are large ground gradient, improper land utilization, damaged ground vegetation, unreasonable cultivation technology, loose soil texture, excessive forest cutting, excessive grazing and the like. The harm of soil erosion is mainly shown in the following steps: the soil plough layer is eroded and destroyed, so that the soil fertility is gradually depleted; silting rivers, channels and reservoirs, reducing the benefit of hydraulic engineering, even causing flood and drought disasters and seriously affecting industrial and agricultural production; soil erosion and water loss bring serious threats to agricultural production in mountainous areas and downstream riverways.
The soil erosion has the influence of stage factors, such as stage climate, rainfall and rainfall, which affect the ground substance composition and vegetation, so when recording the soil erosion situation, the influence of environmental factors on the soil erosion in a specific date needs to be known, but the existing method does not have an algorithm for forecasting the soil erosion date, cannot accurately obtain specific data of the soil erosion date, and is not beneficial to monitoring the soil erosion.
Disclosure of Invention
This section is for the purpose of summarizing some aspects of embodiments of the invention and to briefly introduce some preferred embodiments. In this section, as well as in the abstract and the title of the invention of this application, simplifications or omissions may be made to avoid obscuring the purpose of the section, the abstract and the title, and such simplifications or omissions are not intended to limit the scope of the invention.
The present invention has been made in view of the above and/or other problems occurring in the existing water and soil erosion prediction algorithms.
Therefore, the invention aims to provide a regional water and soil loss daily forecasting algorithm, which can obtain the optimal water and soil loss daily data based on the existing statistical data to achieve the aim of accurate forecasting.
To solve the above technical problem, according to an aspect of the present invention, the present invention provides the following technical solutions:
an area water and soil loss daily forecasting algorithm comprises the following steps:
the method comprises the following steps: installing corresponding monitoring devices according to the plurality of monitoring points;
step two: drawing a density image according to monitoring data on the monitoring points;
step three: obtaining the influence size distribution condition of the factors according to each environment influence factor;
step four: obtaining optimal water and soil loss influence factor data according to the size and the density image influenced by the environmental factors;
step five: and obtaining the data of the water and soil loss day according to the optimal data, and forecasting the water and soil loss day.
The invention relates to a preferable scheme of a regional water and soil loss daily forecasting algorithm, wherein the regional water and soil loss daily forecasting algorithm comprises the following steps: the monitoring points in the first step are environment factor monitoring points, the monitoring devices are environment factor monitoring devices, and the environment factor monitoring devices are used for monitoring rainfall, temperature and humidity and natural disaster annual average occurrence amount.
The invention relates to a preferable scheme of a regional water and soil loss daily forecasting algorithm, wherein the regional water and soil loss daily forecasting algorithm comprises the following steps: and the specific step of monitoring data in the second step is recording and storing specific environmental information generated in the environmental factor monitoring device, and drawing a plane image through the processing device to form a multi-point density image.
The invention relates to a preferable scheme of a regional water and soil loss daily forecasting algorithm, wherein the regional water and soil loss daily forecasting algorithm comprises the following steps: the size distribution of the environmental factors in the third step is specifically the main factors and the secondary factors influenced by the environmental factors, and the actual size distribution of the influence of the factors is calculated according to the main factors and the secondary factors and the ratio.
The invention relates to a preferable scheme of a regional water and soil loss daily forecasting algorithm, wherein the regional water and soil loss daily forecasting algorithm comprises the following steps: and the combination of the environmental factor influence and the density image in the fourth step is to substitute the data generated by the environmental factor influence into the density image, change the density distribution condition of the image according to the numerical value, and obtain the water and soil loss influence factor data after the substitution is finished.
Compared with the prior art: the method comprises the steps of recording the water and soil loss conditions, knowing the influence of environmental factors on the water and soil loss within a specific date, wherein the influence of environmental factors on the water and soil loss within the specific date is needed, but no algorithm for forecasting the water and soil loss date exists in the conventional method, so that specific data of the water and soil loss date cannot be accurately obtained, and monitoring of the water and soil loss is not facilitated.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the present invention will be described in detail with reference to the accompanying drawings and detailed embodiments, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise. Wherein:
FIG. 1 is a schematic diagram of a structural single month environmental factor distribution lattice of a regional water and soil loss daily prediction algorithm.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in detail below.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, but the present invention may be practiced in other ways than those specifically described herein, and it will be apparent to those of ordinary skill in the art that the present invention may be practiced without departing from the spirit and scope of the present invention, and therefore the present invention is not limited to the specific embodiments disclosed below.
Next, the present invention will be described in detail with reference to the drawings, wherein for convenience of illustration, the cross-sectional view of the device structure is not enlarged partially according to the general scale, and the drawings are only examples, which should not limit the scope of the present invention. In addition, the three-dimensional dimensions of length, width and depth should be included in the actual fabrication.
In order to make the objects, technical solutions and advantages of the present invention more apparent, embodiments of the present invention will be described in detail with reference to the accompanying drawings.
The invention provides a regional water and soil loss daily forecasting algorithm, which comprises the following steps:
the method comprises the following steps: installing corresponding monitoring devices according to the plurality of monitoring points;
step two: drawing a density image according to monitoring data on the monitoring points;
step three: obtaining the influence size distribution condition of the factors according to each environment influence factor;
step four: obtaining optimal water and soil loss influence factor data according to the size and the density image influenced by the environmental factors;
step five: and obtaining the data of the water and soil loss day according to the optimal data, and forecasting the water and soil loss day.
The monitoring points in the first step are environment factor monitoring points, the monitoring devices are environment factor monitoring devices, and the environment factor monitoring devices are used for monitoring rainfall, temperature and humidity and natural disaster annual average occurrence amount;
the rainfall is obtained by a coverage algorithm, which is good at constructing a classifier, so that the rainfall is predicted by classifying the result to be obtained by using the classification grade of the meteorological field and then processing the data by applying the coverage algorithm. Obtaining the relation between the influence factors and the target result, and converting the prediction of the target result with higher difficulty into the prediction of the result by using the value of the obtained influence factors which are easier to predict;
the natural disasters are predicted through a genetic algorithm, and the method comprises the following specific steps:
let the variation range of the parameter P be (P)min，Pmax) If binary is used, b is (2)m-1)(P-Pmin)/(Pmax-Pmin)
Thus, there is a section mapping relationship
[Cmin，Cmax]→[0，2m-1]
Let PbA binary bit string of decimal numbers P, Cb(. cndot.) is a binary encoding function. Then there are:
Pb＝Cb(P)
and then the binary bit strings of all the parameters are combined into a long character string s which is called an individual. If there are N model parameters, each parameter is represented by m-bit binary code, the length of the individual character string is m × N bits in total.
Let the population size be n1Randomly generating n1+n2+1And (4) individual character strings are used for establishing an initial population.
The decoded value of parameter P is: p ═ Pmin+Cb -1(Pb)(Cmax-Cmin)
Converting binary bit string of each parameter into decimal number, substituting the decimal number into a prediction model together with practical variables, calculating model value of each individual at each time point in observation or statistical period, calculating difference value of each individual observed and model value at each practical point, calculating residual sum of squares (S), calculating adaptive value F according to the residual sum of squares (C/S), wherein C is constant, and as S is larger, a larger constant C can be taken to prevent F from being valuedIf too small, then selection calculation is carried out, in which the larger individual is selected to participate in the crossover calculation, and n obtained after crossover2Randomly selecting one bit in the individual bit string for negation in each individual, and generating n2+1And adding the new individual into the population, outputting the final model parameter value, establishing a prediction model, and performing prediction calculation.
Recording rainfall information generated by monitoring as X, recording temperature and humidity information generated by monitoring as Y, recording natural disaster information generated by monitoring as Z, drawing a day/year dot matrix diagram, and substituting X, Y, Z data into the dot matrix diagram, as shown in figure 1, so as to obtain a density diagram.
And the specific step of monitoring data in the second step is recording and storing specific environmental information generated in the environmental factor monitoring device, and drawing a plane image through the processing device to form a multi-point density image.
The size distribution of the environmental factors in the third step is specifically the main factors and the secondary factors influenced by the environmental factors, and the actual size distribution of the influence of the factors is calculated according to the main factors and the secondary factors and the ratio.
The combination of the environmental factor influence and the density image in the fourth step is to substitute data generated by the environmental factor influence into the density image, change the density distribution condition of the image according to the numerical value, and obtain the water and soil loss influence factor data after the substitution is finished.
In a specific use process, the specific ratio of rainfall factors, temperature and humidity factors and natural disasters in environmental factors to the influence of water and soil loss is set as 2: 1: substituting the proportion information into the dot matrix diagram, comparing rainfall information, temperature information and natural disaster information generated on a single day in the proportion and dot matrix diagram, setting the marking mode of the rainfall information in the dot matrix diagram as pink, setting the rainfall information as red according to the proportion, setting the color of the temperature and humidity information as green according to the same method, keeping the color unchanged according to the proportion, setting the natural disaster information as gray, setting the color as black according to the proportion, displaying the color information on the day/year dot matrix diagram, and displaying the environmental factor information in recent years on the dot matrix diagram according to the method, so that the water and soil loss day can be visually checked and predicted.
While the invention has been described above with reference to an embodiment, various modifications may be made and equivalents may be substituted for elements thereof without departing from the scope of the invention. In particular, the various features of the disclosed embodiments of the invention may be used in any combination, provided that no structural conflict exists, and the combinations are not exhaustively described in this specification merely for the sake of brevity and resource conservation. Therefore, it is intended that the invention not be limited to the particular embodiments disclosed, but that the invention will include all embodiments falling within the scope of the appended claims.
Claims (5)
1. A regional water and soil loss daily forecasting algorithm is characterized in that: the algorithm comprises the following steps:
the method comprises the following steps: installing corresponding monitoring devices according to the plurality of monitoring points;
step two: drawing a density image according to monitoring data on the monitoring points;
step three: obtaining the influence size distribution condition of the factors according to each environment influence factor;
step four: obtaining optimal water and soil loss influence factor data according to the size and the density image influenced by the environmental factors;
step five: and obtaining the data of the water and soil loss day according to the optimal data, and forecasting the water and soil loss day.
2. The regional water and soil loss daily forecasting algorithm according to claim 1, wherein the regional water and soil loss daily forecasting algorithm comprises the following steps: the monitoring points in the first step are environment factor monitoring points, the monitoring devices are environment factor monitoring devices, and the environment factor monitoring devices are used for monitoring rainfall, temperature and humidity and natural disaster annual average occurrence amount.
3. The regional water and soil loss daily forecasting algorithm according to claim 1, wherein the regional water and soil loss daily forecasting algorithm comprises the following steps: and the specific step of monitoring data in the second step is recording and storing specific environmental information generated in the environmental factor monitoring device, and drawing a plane image through the processing device to form a multi-point density image.
4. The regional water and soil loss daily forecasting algorithm according to claim 1, wherein the regional water and soil loss daily forecasting algorithm comprises the following steps: the size distribution of the environmental factors in the third step is specifically the main factors and the secondary factors influenced by the environmental factors, and the actual size distribution of the influence of the factors is calculated according to the main factors and the secondary factors and the ratio.
5. The regional water and soil loss daily forecasting algorithm according to claim 1, wherein the regional water and soil loss daily forecasting algorithm comprises the following steps: and the combination of the environmental factor influence and the density image in the fourth step is to substitute the data generated by the environmental factor influence into the density image, change the density distribution condition of the image according to the numerical value, and obtain the water and soil loss influence factor data after the substitution is finished.
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Cited By (2)
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| CN112801370A (en) * | 2021-01-28 | 2021-05-14 | 深圳市深水水务咨询有限公司 | Water and soil loss prediction method, device, equipment and storage medium |
| WO2023010856A1 (en) * | 2021-08-02 | 2023-02-09 | 上海派森诺生物科技有限公司 | Online drawing method and apparatus for combined density plot, and electronic device |
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