Research On Risk Assessment Technology Of Coal Chemical Enterprises Based On Industrial Process Data

With the rapid development of data collection technology and data mining algorithms,traditional risk assessment is gradually changing to intelligent risk assessment.In recent years,with the continuous increase in the rate of corporate bad debts,traditional static risk assessment can no longer meet the needs of today’s banks and other financial institutions.The research on intelligent risk assessment is often only aimed at personal credit assessment,but for corporate risks.There are few evaluation studies,and there is no detailed research plan for the risk evaluation of coal chemical industry and other process companies.In order to facilitate banks and other financial institutions to make corresponding decision-making analysis for process chemical companies before,during and after loans.This article mainly takes coal gasification manufacturing enterprises as an example.Through the analysis and monitoring of the key risk node data of the coal chemical process production process,the operation of the coal chemical process is judged,so as to make a real-time assessment of its risk.The specific research work is as follows:(1)Aiming at coal chemical companies,this paper proposes a new method of risk assessment for coal chemical companies.The process data of key risk nodes in the process of coal chemical companies is used to predict and model the key financial information of coal chemical companies.Real-time risk analysis of coal chemical companies.(2)Financial institutions collect coal chemical industry process data in a nonintrusive way,but because of the numerous sensor nodes in the coal chemical industry production process,considering operability and operating costs,it is impossible to select all industrial nodes for monitoring.Therefore,the selection of key risk nodes in the process flow is very necessary.Most of the traditional key node selection only considers the structural characteristics of the process network,without considering the relevant application background.For the first time,this article proposes various evaluation indicators for the selection of key nodes in the context of coal chemical enterprise risk,combining the characteristics of industrial complex networks and According to the risk requirements of enterprises,the key risk nodes of coal chemical enterprises are selected through multi-attribute decision-making algorithms.(3)Due to the working condition of the sensor itself,data missing problems often occur when collecting process data.Therefore,before the risk analysis and evaluation,the problem of filling the missing values of the process data is also one of the problems that need to be solved in the actual evaluation process.This paper considers the characteristics of the process data of coal chemical enterprises and the pros and cons of different methods for filling missing process data,and proposes a method for filling missing industrial data based on correlation factors.By introducing relevant factors,the traditional time series method is improved to improve the accuracy of the estimation of missing industrial data.