Intelligent air quality detection based on genetic algorithm and neural network: An urban China case study

摘要

Scientific and objective evaluations of atmospheric quality have become a primary task forresearchers with the continuous development of modern industrial processes. At present, variousapproaches are used in monitoring air quality. The core factors of these approaches are theselection and establishment of an intelligent evaluation model. In this study, we designed a fuzzygenetic neural network model that fuses data based on the characteristics of autonomic learningand self-organization and optimizes the fuzzy system by using the neural network model. A simulationwasconducted to verify the feasibility of the algorithm. Results indicate that the proposedalgorithm is not only a highly objective, scientific, and accurate method for detecting atmosphericenvironmental quality but also a practical solution.