Research On Fuzzy Inference Algorithm For Big Data And Its Application

With the advent of the era of big data,data has exploded.Fuzzy neural network is often used in fuzzy inference operations.How to improve the traditional fuzzy inference algorithm to ensure the effectiveness of fuzzy inference in big data environment has become a problem that needs to be solved urgently in the field of intelligent information processing.The main work of this paper is as follows:1.According to the characteristics of chaotic motion,a chaos genetic algorithm(CGA)is proposed to solve the nonlinear system optimization problem.The algorithm introduces chaotic variables into the optimized variables of the genetic algorithm,maps the range of values of the two,and uses the updated chaotic variables to transform into "chromosomes" for genetic manipulation.At the same time,the chaotic disturbances are selected according to the size of the fitness.It makes the mutation operation oriented,and after many evolutions,the optimal solution of the problem is obtained.The experiment uses a variety of similar intelligent optimization search algorithms for comparison.Theoretical analysis and experimental results show that the algorithm guarantees the speed of the dynamic response of the nonlinear system optimization problem and the accuracy of the optimization result,and quantitatively evaluates the optimization effect of the chaotic genetic algorithm.2.Using the chaotic genetic algorithm proposed above to train a fuzzy neural network model used in this paper,it improves the problem that the traditional fuzzy neural network can not quantitatively analyze the parameters and membership functions.Experimental results show that the model speeds up the search for membership functions and fuzzy control rules,so that the fuzzy inference algorithm can efficiently calculate the optimal solution.Finally,the improved fuzzy inference algorithm is applied to the intelligent wastewater treatment system.The case shows that the model can efficiently and accurately obtain the corresponding wastewater treatment measures,achieve the purpose of intelligent analysis of data,reduce the manual decision and maintenance costs,and clarify the The practicality of development.After the system was delivered and used,it reduced the pressure on residents' water use and improved the convenience of people's lives.