Method for Optimal Arrangement of Soil Sampling Based on Neural Networks and Genetic Algorithms

被引：0
|
作者：
Wu Zongshu [1 ]
Ai Jiaoyan [1 ]
Deng Chaobing [2 ]
Cai Yajuan [1 ]
Wei Zongming [1 ]
机构：
[1] Guangxi Univ, Coll Elect Engn, Nanning 530004, Peoples R China
[2] Guangxi Autonomous Reg Environm Monitoring Cent S, Nanning 530028, Peoples R China
来源：
PROCEEDINGS OF THE 2015 INTERNATIONAL CONFERENCE ON AUTOMATION, MECHANICAL CONTROL AND COMPUTATIONAL ENGINEERING | 2015年 / 124卷
关键词：
Neural networks; Genetic algorithms; Soil sampling; Optimal arrangement;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In order to explore a new way of optimization for soil sampling layout, in this paper, spatial distribution of heavy metal concentrations which is based on RBF neural network fitting was studied by genetic algorithm, corresponding network structure and algorithm flow were constructed, in addition the network and algorithm parameters settings were analyzed and a sampling experiment using this method was conducted in an abandoned mine located in a county of Guangxi. The results of optimizing the layout point prove that the number of the sampling points can be reduced by about a half under the premise of meeting the fitting accuracy, this will greatly reduce the cost of sampling and analysis and the redundancy of the data, and is expected to promote the relevant application in soil composition analysis and other related fields.
引用
收藏
页码：1121 / 1126
页数：6
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