CN109376909A - A kind of agricultural product monitoring and warning model system - Google Patents
A kind of agricultural product monitoring and warning model system Download PDFInfo
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Abstract
The present invention discloses a kind of agricultural product monitoring and warning model system, including data preparation module, statistical analysis module, prediction module, warning module, visual presentation module and system management module；Data preparation module obtains big data and is pre-processed, and centrally stored and calculating, statistical analysis module carries out general and multidimensional statistics to data, forms portion statistical forms；Prediction module carries out modeling analysis prediction to statistical forms, obtains prediction result；Warning module judges whether prediction result reaches threshold value of warning, carries out early warning to the prediction result for reaching threshold value of warning；Visualize the visual presentation that module carries out prediction and warning information for large-size screen monitors；System management module manages each module.Each module of the system integration is to through agricultural production, circulation and consuming the mass data of overall process and information is handled, application and visual presentation by carrying out integrated treatment and application to agriculture big data realize the one-stop real-time monitoring and early warning of agricultural product.
Description
Technical field
The present invention relates to modern agriculture management domains, more particularly to a kind of agricultural product monitoring and warning model system.
Background technique
With the continuous propulsion and development of state socialism library development process, the development of China's agricultural economy is also gradually
It presents and previous completely different development model.Traditional Agricultural Information analyzes theory, cannot be with the economy of today's society
Development model is synchronised.Current China's agricultural and rural economy development is in a new historical stage, with economy globalization
The quickening of change development process, especially agricultural product production and supply contradiction recurring structure great change, international market and the country
The linkage of agricultural production is also increasingly closer, the application of the innovative development model of National agricultural economy, so that agricultural monitoring is pre-
Alert system there are essential.
Existing agricultural monitoring early warning system carries out early warning only by monitoring data, however agricultural production, price, disappears
Take, the agricultural procedures such as trade and link it is intricate, a large amount of data and information are through agricultural production, circulation and the full mistake of consumption
Journey, therefore a kind of system that can carry out integrated treatment and application to agriculture big data is badly in need of in this field, to realize agricultural product
One-stop real-time monitoring and early warning.
Summary of the invention
The object of the present invention is to provide a kind of agricultural product monitoring and warning model systems, can integrate to agriculture big data
Processing and application, realize the one-stop real-time monitoring and early warning of agricultural product.
To achieve the above object, the present invention provides following schemes:
A kind of agricultural product monitoring and warning model system, including data preparation module, statistical analysis module, prediction module, in advance
Alert module, visualizes module and system management module；
The data preparation module is used to obtain the history big data of long duration, to the history big data of the long duration into
Row pretreatment, establishes database and carries out history centrally stored and to the long duration to the history big data of the long duration
Big data is calculated, and is audited to obtain the qualified data of audit to calculated result, and remember the treatment process of data
Record；
The statistical analysis module is used to obtain the data of the audit qualification in the data preparation module, and to institute
It states the qualified data of audit and carries out general and multidimensional statistics, being formed a includes one-dimensional statistical information and multidimensional statistics information
Statistical forms；
The prediction module is used to obtain the statistical forms formed in the statistical analysis module, and according to institute
It states statistical forms and carries out modeling analysis prediction, obtain prediction result；
The warning module is used to obtain the prediction result of the prediction module, judges whether the prediction result reaches pre-
Alert threshold value carries out early warning to the prediction result for reaching the threshold value of warning；
The module that visualizes is used to show for the function in large-size screen monitors progress homepage is unified, to the prediction module
In the prediction result visualized in large-size screen monitors, to the statistic analysis result information in the statistical analysis module
It carries out visualizing and visualizing the early warning result in the warning module in large-size screen monitors in large-size screen monitors；
The system management module is used for the data preparation module, the statistical analysis module, the prediction module,
The warning module and the visual presentation module carry out system administration.
Optionally, the data preparation module includes data acquisition submodule, data sub-module stored, data processing submodule
Block, data audit submodule and data processing record sub module；
The data acquisition submodule is used to obtain the history big data of long duration and big to the history of the long duration
Data are pre-processed；
It is centrally stored to the history big data progress of the long duration that the data sub-module stored is used to establish database；
The data sub-module stored reaches the demand of different data sources usage scenario by heat, warm data isolation storage, passes through distribution
The storage of formula big data and parallel computation frame, with forward position Hadoop technology ecology platform and conventional data storage and relational data
Oracle fusion in library provides data storage and calculates service, realizes the centrally stored of data；
The data processing submodule is used to carry out the history big data of the long duration in the database automatic
Cleaning, error correction is complete, normalizes, initialization, calculates and modification is handled；The data processing submodule includes that automatic cleaning is single
Member, correcting data error processing unit, the complete processing unit of data, data normalization processing unit, initialization unit, data calculate single
Member and proposition modification unit；The automatic cleaning unit is used to find out problematic data automatically using data cleansing algorithm；Institute
Correcting data error processing unit is stated for the data for being identified as " mistake " to be carried out error correction by error correction algorithm；The complete place of data
Reason unit is for handling the data of missing by algorithm of filling a vacancy；The data normalization processing unit is used for different lists
The data of position are normalized；The initialization unit is for restoring data to original state；The data calculate single
Result of the member for being calculated as data to need according to calculating demand；It is proposed modification unit be used for some suspicious datas into
Line identifier proposes suggestion for revision；
The data audit submodule is used to audit the calculated result of the history big data of the long duration, retains
Audit qualified data；
The data processing record sub module is used for the history big data of the long duration in the data preparation module
The middle whole process handled is recorded.
Optionally, the statistical analysis module includes general statistic submodule and multidimensional statistics submodule；The general system
Count submodule be used for according to mean value, variance and sort algorithm to the data of the audit qualification in the data preparation module into
Row statistics；The multidimensional statistics submodule is used to press different dimensional to the data of the audit qualification in the data preparation module
Degree and index are counted.
Optionally, the prediction module includes information prediction submodule, and prediction result manages submodule, balance sheet template pipe
Submodule is managed, model management submodule and model test results manage submodule；
The information prediction submodule includes production forecast unit, Method for Sales Forecast unit and price expectation unit；The production
Predicting unit is measured to establish quantitative analysis model as core-prediction method to agricultural output, the Method for Sales Forecast unit is to agriculture
It is core-prediction method that product sales volume, which establishes quantitative analysis model, and the price expectation unit is measured with establishing to agricultural product price
Analysis model is core-prediction method；
The prediction result management submodule is used to obtain the prediction result of the information prediction submodule, and to described pre-
It surveys result and carries out Classification Management, form balance sheet；
The balance sheet Template Manager submodule is for being managed balance sheet template；
The model management submodule is for being managed model；
Model test results management submodule for measuring and calculation data result accuracy how.
Optionally, the warning module includes warning information inquiry submodule, and warning information audits submodule, groups of users
It manages submodule and threshold value of warning manages submodule；
The warning information inquiry submodule is for inquiring warning information；
The warning information audit submodule is for auditing warning information；
The groups of users management submodule is for managing groups of users；
The threshold value of warning management submodule is for determining alert threshold value of warning, establishing Early-warning Model and managing early warning
All kinds of threshold parameters；Determine that alert threshold value of warning includes expert's setting method given threshold, Statistics Indexes Analysis given threshold, intelligence
Habit method given threshold；Expert's setting method given threshold is the given threshold parameter of expert as threshold value of warning；The statistics
Index method given threshold is common statistical indicator as threshold value of warning, including n times of standard deviation, the coefficient of variation；The intelligence learning
Method given threshold be according to history alert data study after obtain corresponding learning model to determine whether there is corresponding alert, including
Machine learning method.
Optionally, the visual presentation module accelerates WebGL technology to realize that three-dimensional map data can by video card hardware
It is shown depending on changing, realizes and shown in Chinese agriculture early warning space large-size screen monitors according to real-time analysis result dynamic rendering；The visualization exhibition
Show that module includes that homepage visualizes submodule, prediction visualizes submodule, and statistical analysis visualizes submodule,
Early warning visualizes submodule；
The homepage visualizes the function unification that submodule is used to carry out for large-size screen monitors in homepage and shows；
The prediction visualizes submodule for visualizing prediction result information in large-size screen monitors；It is described
It includes forecast production that prediction, which visualizes the prediction result information that submodule is visualized in large-size screen monitors, predicts sales volume
And forecast price；
The statistical analysis visualizes submodule for visualizing statistic analysis result information in large-size screen monitors
It shows；
The early warning visualizes submodule for visualizing warning information in large-size screen monitors.
Optionally, the system management module includes statistical chart management submodule, and flow chart of data processing manages submodule, calculates
Method manages submodule, scene-type module management submodule, report management submodule and report management submodule；
The statistical chart management submodule for statistical chart for being managed；
The flow chart of data processing management submodule is used to be configured for flow chart of data processing；
The algorithm management submodule for algorithm for being managed；
The scene-type module management submodule is used to be managed for scene-type module；
The report management submodule is used to be managed for report；
The report management submodule for report for being managed.
Optionally, the Data Computation Unit includes the Meteorological Change elasticity for obtaining the history big data analysis of long duration and generating
Coefficient group, investment class coefficient of elasticity group and management class coefficient of elasticity group are as basic coefficient of elasticity, according to the foundation elasticity system
Number carries out elastic calculation.
Optionally, the proposition modification unit is for modifying to each parameter of model, coefficient, by respectively joining to model
Number, coefficient modify and realize the prediction of the future trend of the agricultural product under different scenes, varying environment.
Optionally, the information prediction submodule uses agricultural product traditional financial analysis model method, forward position artificial intelligence
TensonFlow data modeling, machine learning algorithm New Algorithm combine, and realize the new model of intelligent multi-source model analysis.
The specific embodiment provided according to the present invention, the invention discloses following technical effects: agricultural production disclosed by the invention
Product monitoring and warning model system, including data preparation module, statistical analysis module, prediction module, warning module visualize
Module and system management module；The data preparation module obtains the history big data of long duration, pre-processes, builds to it
Vertical database is carried out centrally stored and is calculated, and the statistical analysis module, which obtains, audits qualified number in the data preparation module
According to the statistics for carrying out general and multidimensional, a statistical forms are formed；The prediction module obtains the statistical analysis module
The statistical forms of middle formation carry out modeling analysis prediction, obtain prediction result；The warning module obtains the prediction mould
The prediction result of block judges whether to reach threshold value of warning, carries out early warning to the prediction result for reaching the threshold value of warning；Institute
It states and visualizes the visual presentation that module carries out prediction and warning information for large-size screen monitors；The system management module is to system
In other modules carry out system administration.The each functional module of the system integration is to through agricultural production, circulation and consumption
The mass data and information of overall process handled, application and visual presentation, passes through the General Office carried out to agriculture big data
Reason and application, to realize the one-stop real-time monitoring and early warning of agricultural product.
Detailed description of the invention
It in order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, below will be to institute in embodiment
Attached drawing to be used is needed to be briefly described, it should be apparent that, the accompanying drawings in the following description is only some implementations of the invention
Example, for those of ordinary skill in the art, without any creative labor, can also be according to these attached drawings
Obtain other attached drawings.
Fig. 1 is the structure chart of agricultural product monitoring and warning model system embodiment of the present invention；
Fig. 2 is the network structure topological diagram of agricultural product monitoring and warning model system embodiment of the present invention；
Fig. 3 is the network structure topological diagram of agricultural product monitoring and warning model system embodiment of the present invention.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other
Embodiment shall fall within the protection scope of the present invention.
The object of the present invention is to provide a kind of agricultural product monitoring and warning model systems, to realize to the future of agriculture operation situation
Analysis and judgement, so that publication advance notice in advance, takes counter-measure, prevention and neutralizing Agricultural Risks.
In order to make the foregoing objectives, features and advantages of the present invention clearer and more comprehensible, with reference to the accompanying drawing and specific real
Applying mode, the present invention will be further described in detail.
Fig. 1 is the structure chart of agricultural product monitoring and warning model system embodiment of the present invention.
Referring to Fig. 1, the agricultural product monitoring and warning model system, including data preparation module 101, statistical analysis module 102,
Prediction module 103, warning module 104 visualize module 105 and system management module 106.
The data preparation module 101 is used to obtain the history big data of long duration, to the big number of the history of the long duration
According to being pre-processed, establish database the history big data of the long duration is carried out it is centrally stored and to the long duration
History big data is calculated, and is audited to obtain the qualified data of audit to calculated result, and to the treatment process of data into
Row record.
The data preparation module 101 includes data acquisition submodule 1011, data sub-module stored 1012, data processing
Submodule 1013, data audit submodule 1014 and data processing record sub module 1015；
The data acquisition submodule 1011 is used to obtain the history big data of long duration and goes through to the long duration
History big data is pre-processed；
The data sub-module stored 1012 concentrates the history big data of the long duration for establishing database
Storage；The data sub-module stored 1012 reaches the demand of different data sources usage scenario by heat, warm data isolation storage,
It is stored by distributed big data and parallel computation frame, with forward position Hadoop technology ecology platform and conventional data storage and pass
It is that type database Oracle fusion provides data storage calculating service, realizes the centrally stored of data；
The data processing submodule 1013 is used to carry out the history big data of the long duration in the database
Automatic cleaning, error correction is complete, normalizes, initialization, calculating and modification processing；The data processing submodule 1013 includes certainly
Dynamic cleaning unit 10131, correcting data error processing unit 10132, the complete processing unit 10133 of data, data normalization processing are single
Member 10134, initialization unit 10135, Data Computation Unit 10136 and proposition modification unit 10137；The automatic cleaning unit
10131 for finding out problematic data using data cleansing algorithm automatically；The correcting data error processing unit 10132 is used for will
The data of " mistake " are identified as by error correction algorithm, filling scheduling algorithm is such as returned and carries out error correction；The complete processing unit of data
10133 for being handled the data of missing by algorithm of filling a vacancy, such as interpolation scheduling algorithm；The data normalization processing unit
10134 for the data of not commensurate to be normalized, General Transformations data between 0-1 or between -1-1；Institute
Initialization unit 10135 is stated for restoring data to original state；The Data Computation Unit 10136 is used for according to calculating need
It asks and data is calculated as the result needed；The it is proposed modification unit 10137 is proposed for being identified to some suspicious datas
Suggestion for revision, but without modification；
The Data Computation Unit 10136 includes the Meteorological Change elasticity system for obtaining the history big data analysis of long duration and generating
Several groups, investment class coefficient of elasticity group and management class coefficient of elasticity group are as basic coefficient of elasticity, according to the foundation elasticity coefficient
Elastic calculation is carried out, such as consumption price elasticity, that is, the price for calculating every variation 1% can cause consumption figure percentage change,
There are also input and output elasticity etc. for he；
It is proposed modification unit 10137 for modifying to each parameter of model, coefficient, by each parameter of model,
Coefficient, which is modified, realizes the prediction of the future trend of the agricultural product under different scenes, varying environment；
The data audit submodule 1014 is used to audit the calculated result of the history big data of the long duration,
Retain the qualified data of audit；
The data processing record sub module 1015 is used for the history big data of the long duration in the data preparation
The whole process handled in module is recorded.
The statistical analysis module 102 is used to obtain the data of the audit qualification in the data preparation module 101,
And qualified data carry out general and multidimensional statistics to the audit, being formed a includes one-dimensional statistical information and multidimensional statistics
The statistical forms of information；Wherein, general statistics includes according to mean value, variance and sequence scheduling algorithm to the data preparation mould
The data of audit qualification in block 101 are counted；Multidimensional statistics includes to described in the data preparation module 101
The qualified data of audit are counted by different dimensions and index etc..
The statistical analysis module 102 includes general statistic submodule 1021 and multidimensional statistics submodule 1022；Described one
As statistic submodule 1021 be used for it is qualified to the audit in the data preparation module according to mean value, variance and sort algorithm
Data counted；The multidimensional statistics submodule 1022 is used to close the audit in the data preparation module 101
The data of lattice are counted by different dimensions and index.
The prediction module 103 is used to obtain the statistical forms formed in the statistical analysis module 102, and
Modeling analysis prediction is carried out according to the statistical forms, obtains prediction result；The information conduct of the statistical forms
The input of model, model are analysis prediction model, including supply and demand analysis prediction model etc., and the output of model is prediction result.
The prediction module 103 includes information prediction submodule 1031, and prediction result manages submodule 1032, balance sheet mould
Board management submodule 1033, model management submodule 1034 and model test results manage submodule 1035；
The information prediction submodule 1031 includes production forecast unit 10311, and Method for Sales Forecast unit 10312 and price are pre-
Survey unit 10313；The production forecast unit 10311 is to establish quantitative analysis model as core-prediction side to agricultural output
Method, the Method for Sales Forecast unit 10312 is to establish quantitative analysis model as core-prediction method to agricultural product sales volume, the price
Predicting unit 10313 is to establish quantitative analysis model as core-prediction method to agricultural product price；The information prediction submodule
1031 are calculated using agricultural product traditional financial analysis model method, forward position artificial intelligence TensonFlow data modeling, machine learning
Method New Algorithm combines, and realizes the new model of intelligent multi-source model analysis；
The prediction result management submodule 1032 is used to obtain the prediction result of the information prediction submodule 1031, and
Classification Management is carried out to the prediction result, forms balance sheet；
The balance sheet Template Manager submodule 1033 is for being managed balance sheet template；
The model management submodule 1034 is for being managed model；
Model test results management submodule 1035 for measuring and calculation data result accuracy how.
The warning module 104 is used to obtain the prediction result of the prediction module 103, whether judges the prediction result
Reach threshold value of warning, early warning is carried out to the prediction result for reaching the threshold value of warning.
The warning module 104 includes that warning information inquires submodule 1041, and warning information audits submodule 1042, user
Management and group submodule 1043 and threshold value of warning manage submodule 1044；
The warning information inquiry submodule 1041 is for inquiring warning information；
The warning information audit submodule 1042 is for auditing warning information；
The groups of users management submodule 1043 is for managing groups of users；
The threshold value of warning management submodule 1044 establishes Early-warning Model and management is pre- for determining alert threshold value of warning
Alert all kinds of threshold parameters；Determine that alert threshold value of warning includes expert's setting method given threshold, Statistics Indexes Analysis given threshold, intelligence
It can learning method given threshold；Expert's setting method given threshold is the given threshold parameter of expert as threshold value of warning；It is described
Statistics Indexes Analysis given threshold is common statistical indicator as threshold value of warning, including n times of standard deviation, the coefficient of variation；The intelligence
Learning method given threshold is to obtain corresponding learning model after learning according to history alert data to determine whether there is corresponding alert,
Including machine learning method.
The module 105 that visualizes is used to show for the function in large-size screen monitors progress homepage is unified, to the prediction
The prediction result in module 103 is visualized in large-size screen monitors, to the statistical in the statistical analysis module 102
Analysis result information carries out visualizing and carrying out the early warning result in the warning module 104 in large-size screen monitors in large-size screen monitors
It visualizes.
The visual presentation module 105 accelerates WebGL technology to realize three-dimensional map data visualization by video card hardware
It shows, realizes and shown in Chinese agriculture early warning space large-size screen monitors according to real-time analysis result dynamic rendering；The visual presentation mould
Block 105 includes that homepage visualizes submodule 1051, and prediction visualizes submodule 1052, and statistical analysis visualizes
Submodule 1053, early warning visualize submodule 1054；
The homepage visualizes the function unification that submodule 1051 is used to carry out for large-size screen monitors in homepage and shows；
The prediction visualizes submodule 1052 for visualizing prediction result information in large-size screen monitors；
It includes forecast production that the prediction, which visualizes the prediction result information that submodule 1052 is visualized in large-size screen monitors,
Predict sales volume and forecast price；
The statistical analysis visual presentation submodule 1053 is used to carry out statistic analysis result information in large-size screen monitors can
It is shown depending on changing；
The early warning visualizes submodule 1054 for visualizing warning information in large-size screen monitors.
The system management module 106 is used for the data preparation module 101, and the statistical analysis module 102 is described
Prediction module 103, the warning module 104 and the visual presentation module 105 carry out system administration.
The system management module 106 includes that statistical chart manages submodule 1061, and flow chart of data processing manages submodule
1062, algorithm management submodule 1063, scene-type module management submodule 1064 reports management submodule 1065 and report pipe
Manage submodule 1066；
The statistical chart management submodule 1061 for statistical chart for being managed；
The flow chart of data processing management submodule 1062 is used to be configured for flow chart of data processing；
The algorithm management submodule 1063 for algorithm for being managed；
The scene-type module management submodule 1064 is used to be managed for scene-type module；
The report management submodule 1065 is used to be managed for report；
The report management submodule 1066 for report for being managed.
Agricultural product monitoring and warning model system disclosed by the invention, including data preparation module, statistical analysis module, prediction
Module, warning module visualize module and system management module；The data preparation module obtains the history of long duration
Big data pre-processes it, establishes database and carries out centrally stored and calculate, the statistical analysis module obtains the number
General and multidimensional statistics is carried out according to qualified data are audited in sorting module, forms a statistical forms；The prediction
Module obtains the statistical forms formed in the statistical analysis module and carries out modeling analysis prediction, obtains prediction result；Institute
The prediction result that warning module obtains the prediction module is stated, judges whether to reach threshold value of warning, to reaching the threshold value of warning
The prediction result carry out early warning；The visualization exhibition for visualizing module and carrying out prediction with warning information for large-size screen monitors
Show；The system management module carries out system administration to other modules in system.The each functional module of the system integration
To through agricultural production, circulation and consume the mass data of overall process and information handled, application and visual presentation, pass through
To integrated treatment and application that agriculture big data carries out, so that the one-stop real-time monitoring and early warning of agricultural product are realized, wherein real
When monitoring be to enter database by information, and modeling analysis realization is carried out to the data of storage, real-time early warning is to pass through model
Calculate as a result, then carrying out judging realization to result.
The agricultural product monitoring and warning model system passes through to the agricultural procedures such as agricultural production, price, consumption, trade and link
Progress information characteristics extraction, information change observation, information flow direction are tracked, and are passed through big data and are constructed basic platform, detailed structure
Refinement agricultural product disaggregated model is built, and establishes integrated Early-warning Model management system and the future of agriculture operation situation is carried out to realize
Analysis and judgement, publication advance notice, takes counter-measure, to take precautions against and dissolve Agricultural Risks in advance.
Agricultural product monitoring and warning model system disclosed by the invention is agriculture big data product, is to provide at agriculture big data
The big data platform type product of reason ability, contain data acquisition (by dock other division data library, internet of things data etc. into
The acquisition of row data, data are stored in oracle database), data storage, data processing (data cleansing, integration etc. are handled),
Function in terms of the data such as data application (with modal analysis results are established)；The models function such as new established model, model debugging, model running
Energy；The application functions such as threshold management, agricultural product prediction and warning.System is based on the big of agricultural product production supply-demand structure principle foundation
Type intellectual analysis early warning system, the functions such as transporting something containerized peacekeeping operation management are integrated, and are generated with the history big data analysis of long duration
Meteorological Change coefficient of elasticity group, investment class coefficient of elasticity group, management class coefficient of elasticity group be basic coefficient of elasticity, realize with agricultural production
Product production, consumption, price, trade, inventory, the method for predicting that cost class quantitative analysis model is core；With the more scenes of real-time
Condition and machine learning are key analytical early warning component；Integrated analysis is carried out by above-mentioned a few alanysis models, is calculated all kinds of
The parameter and result of index；Constituting has real-time, all standing, the analysis of long middle or short term, covering 953 kinds of agricultural product, 17 alanysis
The large complicated analysis system of model.This system uses the architecture of Hadoop, and big data processing engine is leaned on as far as possible
Nearly storage, to improve the processing speed to agricultural acquisition data.This system is intended to construct one-stop visualization agricultural product data point
Agricultural product big data monitoring and warning whole process platform, referring to figs. 2 and 3, agricultural product monitoring and warning model system of the present invention are realized in analysis
For system using distributed big data storage and parallel computation frame, it is centrally stored to data to establish database, by heat, warm data every
From the demand that storage reaches different data sources usage scenario, with forward position Hadoop technology ecology platform and conventional data storage and pass
It is that type database such as Oracle fusion provides data storage calculating service, realizes the centrally stored and elastic calculation of data, cluster
Resource can start and stop at any time, resource allocation dynamic adjust, guarantee storage and analysis uniformity and high efficiency.Pass through independent research base
In the self-service model development of the visualization of HTML5 technology and commissioning test system, realizes and pull algoritic module, Controlling model operation
Analysis result is presented with functions, self-service establishment analysis process, dynamic and visuals such as debugging, alignment parameters and results.By aobvious
Block hardware-accelerated WebGL technology and realize that three-dimensional map data visualizes system, realizes in Chinese agriculture early warning space large-size screen monitors
The effect shown according to real-time analysis result dynamic rendering.Using agricultural product traditional financial analysis model method, the artificial intelligence in forward position
The data modeling such as energy TensonFlow, machine learning algorithm New Algorithm combine, and realize the new mould of intelligent multi-source model analysis
Formula.The commerciality of the system facilitates attention of the capital management part to agri-scientific research, reinforces the investment to agri-scientific research；This is
The application of system facilitates the efficiency that itself improves in R&D institution, effectively use limited resource, and according to production needs into
Row research and development；The professional comparison for peomoting economic benefit between scientific achievement or R&D institution of the system, thus excellent
Change the configuration of macro resource；Decision service can be promoted, the more increasing both production and income of energy are promoted and obtains the achievement of bigger economic benefit,
It is analyzed from resulting data and pre-alarm love knot fruit, direction can be provided for Chinese agriculture economy, it is indicated that agro based economic development
Trend.
Agricultural policy can be reasonably adjusted by the agricultural product monitoring and warning model system, agricultural synthesis is improved and competes energy
Power guides operator effectively to evade the market risk in time.Using the method designed in system be alert, warning limit really
Fixed and Early-warning Model foundation provides reasonable method, while the prediction of alert may be that government's macroscopic view is determined with actual error
The preferable theoretical foundation of plan offer, the result that the early warning system comprehensive test of foundation obtains more science and reasonability, thus
Reasonable implantation methods are provided for place and National agricultural.In addition, difference may be implemented by the modification to model each parameter, coefficient
The prediction of agricultural product future trend under scene, varying environment, while according to the performance for testing each model, it is preferably provided for model
Foundation.According to setting parameter, corresponding threshold value index is provided for user, exports alert threshold information, alert knot to user immediately
Fruit, the result being calculated determine which kind of alert belonged to according to threshold range.The pre- police of each agricultural products involved in agricultural
Formula, different regional scopes, different product seasonal variations, select be suitable for method for early warning, can effectively, timely implement agricultural production
The monitoring and warning of product production, consumption and market.Crop growth model involved in system have it is stronger it is mechanistic, it is systemic and
Versatility, the successful exploitation of crop modeling can be promoted to crop growth rule from qualitative description to the transformed of quantitative analysis
Journey has established excellent basis for the exploitation and application of Crop management decision system, especially for sustainable agriculture and accurate agricultural
Research provide science tool.The system will become the most important means of modern agriculture management, and monitoring and warning will implement agriculture
Industry production, circulation and consumption overall process pass through information flow announcement, simulation, operation, regulation and management promotion modern agricultural development.
Agricultural monitoring early warning has become the important means of modern agriculture " high yield, high-quality, efficient, ecological, safe " realization of goal, with skill
Art is promoted leads mode to rapidly develop the cutting edge technology formed around monitoring and warning with technology, will break through all of modern agricultural development
More bottlenecks will lead agricultural to develop towards the direction of " low cost, low-carbon, intelligence ", while being scientific research in the form of wisdom agricultural
Personnel, which conduct a research, provides sufficient data supporting.
Each embodiment in this specification is described in a progressive manner, the highlights of each of the examples are with other
The difference of embodiment, the same or similar parts in each embodiment may refer to each other.
Used herein a specific example illustrates the principle and implementation of the invention, and above embodiments are said
It is bright to be merely used to help understand system and its core concept of the invention；At the same time, for those skilled in the art, foundation
Thought of the invention, there will be changes in the specific implementation manner and application range.In conclusion the content of the present specification is not
It is interpreted as limitation of the present invention.
Claims (10)
1. a kind of agricultural product monitoring and warning model system, which is characterized in that including data preparation module, statistical analysis module, in advance
Module is surveyed, warning module visualizes module and system management module；
The data preparation module is used to obtain the history big data of long duration, carries out to the history big data of the long duration pre-
Processing, establish database the history big data of the long duration is carried out it is centrally stored and to the big number of the history of the long duration
According to being calculated, calculated result is audited to obtain the qualified data of audit, and record the treatment process of data；
The statistical analysis module is used to obtain the data of the audit qualification in the data preparation module, and examines described
The data of core qualification carry out general and multidimensional statistics, form a statistics including one-dimensional statistical information and multidimensional statistics information
Analytical statement；
The prediction module is used to obtain the statistical forms formed in the statistical analysis module, and according to the system
It counts analytical statement and carries out modeling analysis prediction, obtain prediction result；
The warning module is used to obtain the prediction result of the prediction module, judges whether the prediction result reaches early warning threshold
Value carries out early warning to the prediction result for reaching the threshold value of warning；
The module that visualizes is used to show for the function in large-size screen monitors progress homepage is unified, in the prediction module
The prediction result is visualized in large-size screen monitors, to the statistic analysis result information in the statistical analysis module big
It carries out visualizing and visualizing the early warning result in the warning module in large-size screen monitors in screen；
The system management module is used for the data preparation module, the statistical analysis module, and the prediction module is described
Warning module and the visual presentation module carry out system administration.
2. agricultural product monitoring and warning model system according to claim 1, which is characterized in that the data preparation module packet
Data acquisition submodule is included, data sub-module stored, data processing submodule, data audit submodule and data processing record is sub
Module；
The data acquisition submodule is used to obtain the history big data of long duration and the history big data to the long duration
It is pre-processed；
It is centrally stored to the history big data progress of the long duration that the data sub-module stored is used to establish database；It is described
Data sub-module stored reaches the demand of different data sources usage scenario by heat, warm data isolation storage, by distributed big
Data storage and parallel computation frame, with forward position Hadoop technology ecology platform and conventional data storage and relevant database
Oracle fusion provides data storage and calculates service, realizes the centrally stored of data；
The data processing submodule is used to clean the history big data of the long duration in the database automatically,
Error correction, it is complete, it normalizes, initialization, calculates and modification is handled；The data processing submodule includes automatic cleaning unit, number
According to correction process unit, the complete processing unit of data, data normalization processing unit, initialization unit, Data Computation Unit and
It is proposed modification unit；The automatic cleaning unit is used to find out problematic data automatically using data cleansing algorithm；The number
It is used to the data for being identified as " mistake " carrying out error correction by error correction algorithm according to correction process unit；The complete processing of data is single
Member is for handling the data of missing by algorithm of filling a vacancy；The data normalization processing unit is used for not commensurate
Data are normalized；The initialization unit is for restoring data to original state；The Data Computation Unit is used
In the result for being calculated as data to need according to calculating demand；The it is proposed modification unit is for marking some suspicious datas
Know, proposes suggestion for revision；
The data audit submodule is used to audit the calculated result of the history big data of the long duration, retains audit
Qualified data；
The data processing record sub module be used for the history big data of the long duration in the data preparation module into
The whole process of row processing is recorded.
3. agricultural product monitoring and warning model system according to claim 2, which is characterized in that the statistical analysis module packet
Include general statistic submodule and multidimensional statistics submodule；The general statistic submodule is used to be calculated according to mean value, variance and sequence
Method counts the data of the audit qualification in the data preparation module；The multidimensional statistics submodule is used for institute
The data for stating the audit qualification in data preparation module are counted by different dimensions and index.
4. agricultural product monitoring and warning model system according to claim 1, which is characterized in that the prediction module includes letter
Breath prediction submodule, prediction result manage submodule, balance sheet Template Manager submodule, model management submodule and model measurement
Results management submodule；
The information prediction submodule includes production forecast unit, Method for Sales Forecast unit and price expectation unit；The yield is pre-
Unit is surveyed to establish quantitative analysis model as core-prediction method to agricultural output, the Method for Sales Forecast unit is to agricultural product
It is core-prediction method that sales volume, which establishes quantitative analysis model, and the price expectation unit is to establish quantitative analysis to agricultural product price
Model is core-prediction method；
The prediction result management submodule is used to obtain the prediction result of the information prediction submodule, and ties to the prediction
Fruit carries out Classification Management, forms balance sheet；
The balance sheet Template Manager submodule is for being managed balance sheet template；
The model management submodule is for being managed model；
Model test results management submodule for measuring and calculation data result accuracy how.
5. agricultural product monitoring and warning model system according to claim 1, which is characterized in that the warning module includes pre-
Alert information inquires submodule, and warning information audits submodule, and groups of users manages submodule and threshold value of warning manages submodule；
The warning information inquiry submodule is for inquiring warning information；
The warning information audit submodule is for auditing warning information；
The groups of users management submodule is for managing groups of users；
The threshold value of warning management submodule is for determining alert threshold value of warning, establishing Early-warning Model and managing all kinds of of early warning
Threshold parameter；Determine that alert threshold value of warning includes expert's setting method given threshold, Statistics Indexes Analysis given threshold, intelligence learning method
Given threshold；Expert's setting method given threshold is the given threshold parameter of expert as threshold value of warning；The statistical indicator
Method given threshold is common statistical indicator as threshold value of warning, including n times of standard deviation, the coefficient of variation；The intelligence learning method is set
Determining threshold value is to obtain corresponding learning model to determine whether having corresponding alert, including machine according to after the study of history alert data
Learning method.
6. agricultural product monitoring and warning model system according to claim 1, which is characterized in that the visual presentation module
Accelerate WebGL technology to realize that three-dimensional map data visualizes by video card hardware, realizes big in Chinese agriculture early warning space
Screen is shown according to analysis result dynamic rendering in real time；The visual presentation module includes that homepage visualizes submodule, in advance
It surveys and visualizes submodule, statistical analysis visualizes submodule, and early warning visualizes submodule；
The homepage visualizes the function unification that submodule is used to carry out for large-size screen monitors in homepage and shows；
The prediction visualizes submodule for visualizing prediction result information in large-size screen monitors；The prediction
Visualizing the prediction result information that is visualized in large-size screen monitors of submodule includes forecast production, prediction sales volume and pre-
Survey price；
The statistical analysis visualizes submodule for visualizing statistic analysis result information in large-size screen monitors；
The early warning visualizes submodule for visualizing warning information in large-size screen monitors.
7. agricultural product monitoring and warning model system according to claim 1, which is characterized in that the system management module packet
Statistical chart management submodule is included, flow chart of data processing manages submodule, algorithm management submodule, scene-type module management submodule
Block, report management submodule and report management submodule；
The statistical chart management submodule for statistical chart for being managed；
The flow chart of data processing management submodule is used to be configured for flow chart of data processing；
The algorithm management submodule for algorithm for being managed；
The scene-type module management submodule is used to be managed for scene-type module；
The report management submodule is used to be managed for report；
The report management submodule for report for being managed.
8. agricultural product monitoring and warning model system according to claim 2, which is characterized in that the Data Computation Unit packet
It includes and obtains the Meteorological Change coefficient of elasticity group that the history big data analysis of long duration generates, investment class coefficient of elasticity group and management class bullet
Property coefficient group carries out elastic calculation as basic coefficient of elasticity, according to the foundation elasticity coefficient.
9. agricultural product monitoring and warning model system according to claim 2, which is characterized in that the proposition modification unit is used
It modifies in each parameter of model, coefficient, realizes different scenes, different rings by modifying to each parameter of model, coefficient
The prediction of agricultural product future trend under border.
10. agricultural product monitoring and warning model system according to claim 4, which is characterized in that the information prediction submodule
Block uses agricultural product traditional financial analysis model method, forward position artificial intelligence TensonFlow data modeling, machine learning algorithm
New Algorithm combines, and realizes the new model of intelligent multi-source model analysis.
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