New and old kinetic energy conversion performance evaluation method and device based on BP neural network

Abstract

The invention relates to the technical field of computer data processing, in particular to a new and old kinetic energy conversion performance evaluation method and a device based on a BP neural network. The invention provides the new and old kinetic energy conversion performance evaluation method based on the BP neural network. The method comprises the steps of constructing an index system and performing centralized and standardized processing on collected data to form a training set and a test set; training the BP neural network model to obtain optimal BP neural network model parameters; determining a common index reference point through variable connection weight calculation and variable sensitivity analysis results; calculating the connection distance between the pre-estimated index and the index reference point through an improved K-means algorithm, obtaining the BP neural network model with the input variable importance through the strength, and obtaining the score and sequence of the new kinetic energy development level of the national key city through the output; and re-judging the new and old kinetic energy conversion performance evaluation according to the performance division basis and the new kinetic energy development level score and ranking.

Description

technical field [0001] The application relates to the technical field of computer data processing, in particular to a performance evaluation method and device for converting new and old kinetic energy based on BP neural network. Background technique [0002] The transformation of new and old kinetic energy is a process in which new kinetic energy formed in the new round of technological revolution and industrial transformation in society, such as the Internet and new energy industries, gradually replaces old kinetic energy with high energy consumption and high pollution in the traditional sense. In the process of adjusting the indicator, both its applicability and the difficulty of data collection need to be considered. The development of new kinetic energy tends to be static, expressing more the development status of new kinetic energy in a region; the conversion of old and new kinetic energy expresses the development status of new kinetic energy in a region, emphasizing th...

AI Technical Summary

Problems solved by technology

[0005] This application provides a performance evaluation method and device for new and old kinetic energy conversion based on BP neural network, which realizes the training of new and old kinetic energy conversion evaluation through BP neural network algorithm, and establishes the benchmark by ranking the co-existing importance in connection weight and sensitivity analysis results Points, and then use the improved K-means algorithm to determine the importance of the input variable indicators of the neural network model, to a certain extent, it can solve the inconsistency, poor interpretability, high, artificial interference of the usual neural network model due to the "black box" characteristics Too many questions

Images