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Water Quality Evaluation and Prediction Method Based on Fuzzy Wavelet Neural Network

A wavelet neural network and prediction method technology, applied in biological neural network models, neural architectures, computational models, etc., can solve problems such as slow convergence speed, inaccurate prediction results, and poor approximation effect, and achieve fast convergence speed and approximation ability. Strong, stable effect

Inactive Publication Date: 2017-11-28
HENAN INST OF ENG
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Problems solved by technology

[0003] For above-mentioned situation, in order to overcome the defective of prior art, the present invention provides a kind of water quality evaluation prediction method based on fuzzy wavelet neural network, the purpose is to solve BP neural network when carrying out water quality prediction, convergence speed is relatively slow, approximation effect is poor, and prediction The problem with inaccurate results

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  • Water Quality Evaluation and Prediction Method Based on Fuzzy Wavelet Neural Network
  • Water Quality Evaluation and Prediction Method Based on Fuzzy Wavelet Neural Network
  • Water Quality Evaluation and Prediction Method Based on Fuzzy Wavelet Neural Network

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[0049] The specific implementation manners of the present invention will be described in further detail below in conjunction with the accompanying drawings.

[0050] In one embodiment: as figure 1As shown, this paper adopts the fuzzy neural network based on the T-S model. There are two types of fuzzy logic, type I and type II. Traditional type I fuzzy systems cannot deal with the uncertainty of fuzzy rules, so in the face of complex systems, it is impossible to establish effective and reasonable Fuzzy rules. Type II fuzzy systems mainly include Mamdani type and T-S type. The T-S type fuzzy model uses IF-THEN fuzzy rules. The premise part of each rule includes premise variables and fuzzy sets. Its function is to define a fuzzy subspace, and the conclusion part is usually a linear function. Studies have shown that T-S network is better than Mamdani network in terms of learning accuracy. In the traditional wavelet neural network, the nonlinear Sigmoid function in the BP neural...

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Abstract

The present invention provides a water quality evaluation and prediction method based on fuzzy wavelet neural network. The purpose is to solve the problems of slow convergence speed, poor approximation effect and inaccurate prediction results of BP neural network in water quality prediction. Based on the known water quality analysis index The number is, the number of prediction indicators, and the number of fuzzy rules to construct a fuzzy wavelet neural network prediction model, which includes an input layer, a membership layer, a fuzzy rule layer, a wavelet layer, an output layer and a defuzzification layer; the membership function parameters Adjust the wavelet parameters of wavelet layer and wavelet layer, and define the cost function, and use the BP algorithm based on the gradient descent method to adjust the parameters. The worker bee colony algorithm optimizes the initial parameters, and the patented method is mainly used to predict water quality indicators.

Description

technical field [0001] The invention relates to the field of hydrological evaluation and prediction, in particular to a water quality evaluation and prediction method based on fuzzy wavelet neural network. Background technique [0002] Water quality prediction is a technology to establish water functional areas in water pollution control units, and use the corresponding relationship between water quality indicators and corresponding pollution sources in land areas to obtain target water quality information. In the water environment and water pollution control at home and abroad, the research and application of water quality models have made great progress. Water quality prediction methods mainly include water quality simulation models, mathematical statistics models and artificial neural network models. The traditional BP neural network model method has made great progress in the application research of water quality prediction and evaluation, but there are slow convergence ...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/06G06N3/00G06N3/04G06Q50/10
CPCG06N3/006G06Q10/06375G06Q50/10G06N3/043
Inventor 付立华王刚张晓玫邓丽霞李小魁韩大伟
Owner HENAN INST OF ENG
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