Energy Evaluation And Prediction Of JC Metal Nickel Smelting Industry Based On Optimized Neural Network

Metal nickel smelting enterprises are not only important metal producers,but also large consumers of energy resources.The cost of energy consumption has accounted for most of the company's single operating costs.Choosing the right method to monitor and control energy consumption is the current situation of energy saving and emission reduction.Based on the basic model of nickel-containing material flow in the smelting process of JC nickel production enterprises,this article starts from the basic concept of material flow,and analyzes that the nickel-containing material flow in the production process of nickel metal production enterprises may be in actual enterprise production.The status of the material flow occurred;the analysis of the nickel-containing substances in the case of deviating from the reference material flow chart will affect the energy consumption of the company;the indicators that affect the overall energy consumption are determined.According to the determined indicators,the combination of the analytic hierarchy process and the coefficient of variation method is used to determine the relative magnitude of the impact of the index on the overall energy consumption of nickel,and the ranking is based on the correlation between the index and the overall energy consumption,and the cumulative contribution rate is calculated,and the The degree of importance put forward corresponding countermeasures and suggestions.In the establishment of energy consumption prediction model,taking the cumulative contribution rate of over 85%as input,an improved BP neural network was selected as a model for predicting comprehensive energy consumption.In this paper,a neural network combining genetic algorithm and vector machine is used to optimize the weights,thresholds and input data of BP neural network,which weakens some of the defects of BP neural network itself,making the BP neural network its own prediction and comprehensive energy.The accuracy of consumption can be improved,and the comprehensive energy consumption of metal nickel enterprises can be effectively predicted and its changing trend.Corporate management can take measures to save energy and reduce consumption with reference to the results of model predictions.