Optimization calculation of well function W (u, r/B) based on BP neural network

T.Y. Fang,Zhang Yuxia,V. Khaletski

doi:10.1051/e3sconf/201913604031

Abstract

In order to obtain the calculation result of the well function W (u, r/B) in the groundwater more quickly and the obtained result is more accurate than the approximation obtained by the conventional interpolation. Based on the selection of BP neural network structure and the selection of parameters, the corresponding BP neural network model was established to study the well function W (u, r/B). The results show that the partial data of well function are trained by BP neural network, and the prediction result is faster and more accurate than the approximate solution obtained by the equal logarithmic distance trapezoidal segmentation method. It can be seen that using BP neural network to learn and train, the network model obtained is used for solving and calculation, which is a convenient, fast and accurate calculation method.

Highlights

As a kind of valuable resource, it is of great significance for the development of society to study the movement law of groundwater, make correct evaluation and make reasonable development and utilization [1]
Through the learning and training the relationship between u, r/B and W (u, r/B), we obtain the neural network model, which makes the solution faster and more accurate than the approximate solution obtained by equal logarithmic interval trapezoidal segmentation method
Network model [5].BP neural network can learn and store a large number of input-output pattern mapping relationships without revealing the mathematical equation describing such mapping relationship in advance, and it has a strong nonlinear mapping ability [6].BP neural network is a kind of multi-layer neural network with three or more layers, which has an input layer and an output layer, and has one or more hidden layers [7]

Summary

Introduction

As a kind of valuable resource, it is of great significance for the development of society to study the movement law of groundwater, make correct evaluation and make reasonable development and utilization [1]. The well function of unsteady motion is the exponential integral function [2], which has no analytic solution and can only be solved approximately by numerical calculation method [3]. Each r/B has a standard curve, which is generally solved by look-up table method. There is approximate well function programming [4] to solve the calculation. BP neural network is used to solve and calculate the well function W (u, r/B). Through the learning and training the relationship between u, r/B and W (u, r/B), we obtain the neural network model, which makes the solution faster and more accurate than the approximate solution obtained by equal logarithmic interval trapezoidal segmentation method

Principle of BP neural network

Training data generation and processing

Selection of BP neural network structure and determination of parameters

Comparison of training results

Conclusion