基于Bayesian模型的电力大数据在生态环境监管中的应用策略优化研究

Optimization Research on the Application Strategy of Electric Power Big Data in Ecological Environment Regulation Based on Bayesian Model

随着社会快速发展和工业化进程加速,环境污染问题日益凸显,加强环境监管与治理刻不容缓。现有的环境监管方法难以准确及时地监测和预测环境污染情况。文章利用Bayesian模型分析排污企业用电量,以监测和预测区域环境污染情况。并选取我国西北某区域的排污企业用电数据作为研究对象开展实证分析,将预测结果与实际环境污染数据进行对比,展示了该方法在实际应用中的效果和可行性,为实现更精细化的环境保护和监管提供了一种新颖的方法和思路。

With the rapid development of society and the accelerated industrialization,environmental pollution has become a prominent issue.The effective regulation and control of environmental pollution is an urgent task.Currently,monitoring and predicting environmental pollution accurately and timely remains challenging under existing environmental regulation methods.The study employs the Bayesian model to examine electricity usage in wastewater companies for monitoring and forecasting environmental pollution within a region.The electricity consumption data from sewage enterprises in northwest China were selected for empirical analysis.Comparison between predicted results and actual environmental pollution data demonstrate the method's effective and practical application,providing a novel methodology for more refined environmental protection and regulation.