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Land evaluation method based on artificial neural network

An artificial neural network and evaluation method technology, applied in the field of land survey and evaluation, can solve the problems of large knowledge deviation, difficult to describe the complex relationship between land quality and its influencing factors, sensitive to the accuracy of empirical knowledge, etc., and achieve high accuracy of results. , ease of understanding, improved accuracy and usability

Inactive Publication Date: 2009-12-09
WUHAN UNIV
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AI Technical Summary

Problems solved by technology

[0003] In view of the traditional land evaluation method, the approximation of the relationship between the participating factors and the land quality is oversimplified by the simple fitting method, and the given functional form is difficult to describe the complex relationship between the land quality and its influencing factors; the reasoning method of empirical rules The process is simple, but it is extremely sensitive to the accuracy of empirical knowledge, and inaccurate knowledge often brings defects such as results with large deviations

Method used

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  • Land evaluation method based on artificial neural network
  • Land evaluation method based on artificial neural network
  • Land evaluation method based on artificial neural network

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Embodiment Construction

[0026] Utilize the land evaluation method based on genetic optimization constructed by the present invention, its structure is as attached figure 1 As shown, the proposed evaluation method is used to evaluate the suitability of paddy fields in a certain area, and the initial evaluation indicators are as follows:

[0027] Evaluation factor index system of initial suitable paddy fields

[0028]

[0029] Optimizing the connection weight of neural network with genetic algorithm includes the following steps:

[0030] (1) Arrange the connection weights and thresholds of the neural network in a certain order and encode them with a binary coding scheme, randomly generate a set of distributions, and then construct a set of code chains, each code chain represents a weight of the neural network Distribution, that is, a neural network corresponding to a specific value of weight and threshold;

[0031] (2) Calculate its mean square error on the training sample set for the generated ne...

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Abstract

The invention discloses a land evaluation method based on artificial neural network; in the method, on the basis of a self-studying method based on actual survey samples or known knowledge, self-studying correction is carried out according to samples, so as to construct a land evaluation method of a self-studying and self-adapting neural network. According to the problem that convergence is over slow, even is diverged owning to jump functions such as non-differential excitation function in a model structure of a neural network model, genetic optimization is introduced, thereby constructing the land evaluation method based on the genetic optimization and realizing the land evaluation method of the artificial neural network based on the genetic optimization. A genetic algorithm is used for optimizing the connecting weight of the neural network and neural network structure for improving the accuracy and the practicability of the neural network model.

Description

Technical field: [0001] The invention relates to a land evaluation method based on genetically optimized neural network self-learning technology, which belongs to the field of land investigation and evaluation. Background technique [0002] Land evaluation is the basis of land use planning and an important prerequisite for rational use of land. Since the 1960s, land evaluation has been widely concerned, and its theory, technology and application have been developed rapidly. The land evaluation model is the core of land evaluation, and it has always been a hot spot in land evaluation research, and has been widely concerned at home and abroad. In general, its development has gone through a process from qualitative to quantitative, from individual to comprehensive, from mathematical statistical analysis to intelligent computing, complex geographic computing and expert systems, forming qualitative models, statistical methods, parameterized systems, expert systems, and hybrid m...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/08G06N3/12G06Q10/00G06Q50/00G06Q50/26
Inventor 刘耀林焦利民刘艳芳
Owner WUHAN UNIV
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