Prediction method for explosion characteristics of organic mixture based on support vector machine

Abstract

A method for predicting the combustion and explosion characteristics of organic mixtures based on support vector machines. Aiming at the problem of predicting the combustion and explosion characteristics of organic mixtures under different components and different ratios in industrial production and optimizing the design of industrial processes, it uses known organic mixtures The component content and conventional physical property experimental data are used as input variables, and the corresponding combustion and explosion characteristics experimental data are used as output variables. The powerful machine learning algorithm support vector machine method is used to analyze the nonlinearity, uncertainty and existing between the two. Effective training and prediction based on the inherent quantitative relationship of complexity, thereby establishing a stable and efficient support vector machine prediction model. The established support vector machine model is used to predict the combustion and explosion characteristics of other unknown mixtures, which has the advantages of high prediction accuracy, quickness and convenience. The invention can not only predict the combustion and explosion characteristics of organic mixtures with different components and proportions, effectively solve the problem of lack of experimental data of various mixtures in actual industrial production, but also has good application in industrial process design and fire and explosion prevention. Application prospects.

Description

technical field [0001] The invention relates to the technical field of organic chemical industry, in particular to a method for predicting the explosion characteristics of organic mixtures, in particular to a method for predicting the explosion characteristics of organic mixtures based on support vector machines. Background technique [0002] With the continuous development of the chemical industry and the diversification of chemical products, various chemical products have been widely used in various sectors of the national economy. At present, more than 30 million chemical substances have been discovered and synthesized, among which there are more than 80,000 chemical products used by human beings daily, and this number is increasing at a rate of nearly 1,000 each year. Among the many chemical substances, there are many substances with dangerous characteristics such as flammability and explosion, and there are possibilities of fire and explosion accidents in the process of...

AI Technical Summary

Problems solved by technology

[0013] The present invention aims at the problems that the explosion characteristics of organic mixtures with different components and different proportions need to be determined through experiments in the actual industrial production, which has a long cycle, high risk and high cost, and proposes a method based on existing known organic compounds. Based on the combustion and explosion characteristics of the mixture, with a small amount of conventional physical property experiments, the prediction method of the combustion and explosion characteristics of organic mixtures based on support vector machines can be obtained without large-scale combustion and explosion experiments

Images