A Joint Detection Method of Groundwater-Level Change Based on Radial Basis Function Method with Multi-Social Networks

Introduction

Groundwater is the main source of water for industrial and agricultural development in China, and is also one of the water sources on which people rely for survival. Since a large part of water resources consists of groundwater, and groundwater has many characteristics, such as excellent water quality, strong sustainability, uniform distribution, stable water supply, etc. groundwater is extremely widely used in some areas of China and has become the only water source. The groundwater is the inhabitants of the critical exploitation of the damage control of the overlay operation to follow the management of the predictive operations in the random forest for predictive performance in the topographic under groundwater reforms in the predictive performance. The procedures of control variable over various coverage options are known as overlay. By combining data form multiple input datasets, new geographic information sets are formed in the land suitability analysis. One of most prevalent and effective GIS techniques is overlaying analysis. The random forest is a classifying technique that uses numerous decision trees to classify data. When creating each individual tree, it employs bagging and feature randomization in order to generate a statistically independent forest of trees whose consensus prediction is much more accurate than any one tree. Unconfined aquifers are those where the rock is immediately exposed at the ground's surface and groundwater is replenished directly, such as by rainfall or snowmelt. Thick deposits overburden the aquifer, enclosing it from the Earth's surface or other rocks, are known as confined aquifers. The groundwater may be the part of the receiver operating characteristics of the sensitive accuracy of the high potential groundwater managing the potential of the zonation app of the various performance in the temperature. A graphical way to evaluate the classification results is receivers operating characteristic (ROC) analysis. It evaluates a classifier's effectiveness using two statistics: true positive rate and false positive rate.