New information compensating multilayered nonlinear mapping neural network model water needed forecasting method

Abstract

A water demand forecasting method for an information renewal multi-layer non-linear mapping neural network model relates to a water amount forecasting method, wherein, a multi-layer non-linear mapping neural network belongs to a static network; a minimum mean-square error learning way is used to complete the mapping from signal input to signal output in the minimum process of an evaluation function; the network is composed of an input layer, an output layer, as well as one or more hidden layers; the neurons of each layer are mutually and unilaterally connected; in the learning stage, the network adopts an error direction for layer-to-layer transmission to the input layer, while in the working stage, the network uses the input vector for layer-to-layer forward transmission to the output layer; therefore, the network is a feed-forward network composed of non-linear conversion units. The BP neural network has the advantages of large-scale parallel processing, good robustness, easy operation, strong learning ability and particularly strong simulation ability, which is totally feasible in forecasting water demand.

Description

technical field [0001] The invention relates to a method for forecasting water quantity, in particular to a water demand forecasting method for a new information supplementary BP (multi-layer nonlinear mapping neural network) model. Background technique [0002] Water resources are basic natural resources, but also strategic economic resources. Looking ahead, water resources are increasingly affecting the global environment and development. Discussing the strategic issue of water resources in the 21st century is one of the focuses of common attention in the world. In the past, due to the limitations of forecasting methods, the forecast of water demand was generally high, resulting in varying degrees of misleading decisions on water resources. However, my country is one of the main countries in the world that suffers from water resource shortage. In some areas, the water resource shortage has reached a serious shortage level, and the unreasonable development and utilization...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide a kind of in water demand prediction, there is the problem that the long-term prediction result of water demand prediction and the actual situation have bigger error, the proposed gray model is applied to the prediction of water volume, by programming the mathematical model, New Information Supplemented BP Neural Network Model to Forecast Water Consumption

Forecast the water volume

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