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Load Prediction of Exhaust Gas Treatment System Based on Genetic Algorithm Optimization Neural Network

Published: 28 June 2024 Publication History

Abstract

In practical work, in order to evaluate the health status and safety index of the exhaust gas system, the load data of the exhaust gas treatment system is predicted according to some experimental data. Based on genetic algorithm optimization neural network, the model and chart are established to predict the short-term load of the system. The results show that the BP algorithm optimized by the genetic algorithm combines the characteristics of the global optimal weight threshold of the genetic algorithm and the lowest error reduction of the BP algorithm. The optimized genetic neural network has more accurate prediction results and smaller errors than the unoptimized network. In the global scope, the results are more accurate; In the local area, there is still room for optimization. The results show that the optimized method improves the accuracy and stability of system load forecasting.

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      ICRSA '23: Proceedings of the 2023 6th International Conference on Robot Systems and Applications
      September 2023
      335 pages
      ISBN:9798400708039
      DOI:10.1145/3655532
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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      Published: 28 June 2024

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      Author Tags

      1. BP algorithm
      2. Genetic algorithms
      3. Genetic neural networks
      4. Load forecasting
      5. Optimize the network

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