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Application Research About Aircraft Readiness Rate Evaluation Based on Improved Neural Network

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Advances in Computational Science and Computing (ISCSC 2018 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 877))

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Abstract

The paper gave the idea, the method and the process about the aircraft readiness rate evaluation based on improved neural network. It constructed the tunable activation function neural network to evaluate the aircraft readiness rate and replaced conventional transfer function with mutative function to extend the evaluation capability, and used the improved algorithm to increase the evaluation precision. The application indicated the evaluation effect was perfect and exact.

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Author information

Authors and Affiliations

  1. Aviation Maintenance NCO Academy of Air Force Engineering University, Xinyang, 464000, Henan, China

    Zhengwu Wang & Shenjian Yao

Authors
  1. Zhengwu Wang
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  2. Shenjian Yao
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Corresponding author

Correspondence to Zhengwu Wang .

Editor information

Editors and Affiliations

  1. Division of Intelligent Future Technologies, Mälardalen University, Västerås, Sweden

    Ning Xiong

  2. School of Information Science and Technology, Hunan University, Changsha, Hunan, China

    Zheng Xiao

  3. School of Computer Science, Hunan Normal University, Changsha, Hunan, China

    Zhao Tong

  4. Hunan University of Chinese Medicine, School of Computer Science, Changsha, Hunan, China

    Jiayi Du

  5. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore

    Lipo Wang

  6. Design and Physical Sciences Brunel, Electronic and Computer Engineering, College of Engineering, Uxbridge, Middlesex, UK

    Maozhen Li

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Wang, Z., Yao, S. (2019). Application Research About Aircraft Readiness Rate Evaluation Based on Improved Neural Network. In: Xiong, N., Xiao, Z., Tong, Z., Du, J., Wang, L., Li, M. (eds) Advances in Computational Science and Computing. ISCSC 2018 2018. Advances in Intelligent Systems and Computing, vol 877. Springer, Cham. https://doi.org/10.1007/978-3-030-02116-0_34

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