A method and system for dynamic adjustment and fusion of farmland multi-source information

A dynamic adjustment and multi-source information technology, applied in the field of agricultural informatization, can solve problems such as misleading decision-making results, uncertain fusion results, and contradictory facts, and achieve the effects of reducing risks and improving reliability and rationality

Active Publication Date: 2021-04-30
XIAN UNIV OF POSTS & TELECOMM +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to provide a method and system for dynamic adjustment and fusion of farmland multi-source information. By introducing evidence weights and historical accumulation data factors, the synthesis rules of D-S evidence theory are improved, which solves the problem of neglecting The fusion results caused by the influence of irrigation factors and historical accumulated data on the current data are uncertain or even contrary to the facts, thus misleading the decision-making results

Method used

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  • A method and system for dynamic adjustment and fusion of farmland multi-source information
  • A method and system for dynamic adjustment and fusion of farmland multi-source information
  • A method and system for dynamic adjustment and fusion of farmland multi-source information

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Embodiment 1

[0077] Such as figure 1 As shown, the method for dynamic adjustment and fusion of farmland multi-source information provided in this embodiment includes:

[0078] Step 101: Obtain multi-source farmland data and determine the multi-source data as evidence factors; the evidence factors include soil moisture, water stress index and stomatal conductance.

[0079] Step 102: Determine the recognition framework for data fusion; the recognition framework includes three propositions, namely irrigation proposition, non-irrigation proposition and uncertain proposition.

[0080] Step 103: Calculate the probability assignment values ​​of each of the evidence factors to each proposition in the recognition framework, and establish a basic probability assignment matrix; the elements of the basic probability assignment matrix are probability assignment values.

[0081] Step 104: Calculate the conflict coefficient according to the basic probability distribution matrix and in combination with t...

Embodiment 2

[0115] Such as figure 2 As shown, a farmland multi-source information dynamic adjustment and fusion system provided in this embodiment includes:

[0116] The farmland multi-source data acquisition module 100 is configured to acquire farmland multi-source data and determine the farmland multi-source data as evidence factors; the evidence factors include soil moisture, water stress index and stomatal conductance.

[0117] The recognition frame determination module 200 is used to determine the recognition frame for data fusion; the recognition frame includes three propositions, namely irrigation proposition, non-irrigation proposition and uncertain proposition.

[0118] The basic probability assignment matrix building module 300 is used to calculate the probability assignment values ​​of each of the evidence factors to each proposition in the recognition framework, and establish a basic probability assignment matrix; the elements of the basic probability assignment matrix are pr...

Embodiment 3

[0125] The present invention is carried out on the basis of monitoring information related to the crop itself and the growth environment collected by various types of sensors, including soil moisture sensors, soil temperature sensors, electrical conductivity sensors, wind speed and direction sensors, light intensity sensors, and light radiation sensors. As well as the real-time data of the canopy temperature sensor and stomatal conductance sensor for observing the growth of farmland crops, the above sensors collect data every 10 minutes.

[0126] Such as image 3 As shown, under the background of the above experimental environment, the specific steps of the method for dynamic adjustment and fusion of farmland multi-source information provided in this embodiment are as follows:

[0127] Step 1: Select multi-source farmland monitoring data as the evidence factor for data fusion, and determine a reasonable identification framework based on data characteristics and fusion decision...

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Abstract

The invention discloses a method and system for dynamic adjustment and fusion of farmland multi-source information, including determining evidence factors and identification frames, and calculating the probability assignment values ​​of each evidence factor to each proposition in the identification frame; according to the probability assignment value and D‑S The conflict coefficient calculation formula in the evidence theory calculates the conflict coefficient and judges whether the conflict coefficient is within the set threshold interval. If not, the classic D-S evidence theory synthesis rule is used for data fusion. If it is, the average evidence factor is used to replace the conflict factor. The evidence source is corrected by means of probability distribution value, and the classical D‑S evidence theory synthesis rules are used for data fusion, or the classic D‑S evidence theory synthesis rules are improved according to the weight coefficients of each evidence factor and the historical accumulation data factors, and The improved classic D-S evidence theory synthesis rules are used for data fusion, which improves the reliability and rationality of farmland monitoring data fusion and reduces the risk of decision-making.

Description

technical field [0001] The invention relates to the technical field of agricultural informatization, in particular to a method and system for dynamic adjustment and fusion of farmland multi-source information. Background technique [0002] With the development of refined and information-based modern agriculture, high-tech technologies such as Internet of Things and computer technology have begun to be widely applied in the agricultural field, and an information technology platform, combined with big data and mechanical equipment, to optimize crop management and use of agricultural resources has begun to form Comprehensive farmland management optimization technology for efficiency, that is, precision agriculture. As a part of precision agriculture, precision irrigation can finely and accurately adjust various soil and crop management measures, and optimize the use of water input to the greatest extent to obtain the highest yield and maximum economic benefits. The realization ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/06G06Q50/02G06K9/62
CPCG06Q10/06393G06Q50/02G06F18/257G06F18/254
Inventor 赵小强高强权恒晏珠峰石俊丽赵治伟刘耀文
Owner XIAN UNIV OF POSTS & TELECOMM
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