Evaluation method of agricultural environmental geological system state based on optimized particle swarm optimization algorithm

Abstract

The conventional evaluation methods for the state of agricultural environmental geological system mainly use the support vector regression (SVR) model to process the evaluation samples, which is vulnerable to the influence of the sensitive loss function, resulting in the high difference of the evaluation entropy. Therefore, a new evaluation method for the state of agricultural environmental geological system needs to be designed based on the optimized particle swarm optimization algorithm. That is to say, combining with the evolution process of regional agricultural environmental geology, the accurate state evaluation target is selected, the state evaluation system of agricultural environmental geology system is constructed, and the state evaluation model of agricultural environmental geology system is designed combined with the optimized particle swarm optimization algorithm, so as to complete the state evaluation of geological system. The results demonstrated the suggested methodology assesses the state of an agricultural environmental geological system. Key factors included soil texture (0.254), soil nutrient (0.118), and soil pH (0.256). It showed that the designed evaluation method of agricultural environmental geological system state based on optimized particle swarm optimization algorithm has good evaluation effect, reliability and certain application value, and has made certain contributions to the formulation of reasonable agricultural ecological protection scheme.