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RETRACTED ARTICLE: Fuzzy neural network model construction based on shortest path parallel algorithm

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This article was retracted on 05 December 2022

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Abstract

A fuzzy neural network model based on the shortest path parallel algorithm (FNNMSPPA) is proposed. With this model, the shortest path parallel programming on the basis of 0–1 coding can be realized. Moreover, in the method proposed in this paper, the individual passive fuzzy neural network is transformed into a model construction. At this time, the interaction between the system and the surrounding environment is carried out by using the fuzzy neural network. Therefore, it has better adaptability to the neural network environment. It can detect the changes in the environment in time, and can effectively track the shortest path using pole values in the space. And in this paper, the performance of this algorithm is verified by dynamic simulation experiment. The results of the study show that the algorithm designed in this paper can still guarantee the realization of stable model construction for the environment with more severe environmental changes, that is, the robustness of the algorithm is strong. And compared with the same method, this method has stronger dynamic search ability, and the extreme point tracking ability is also superior.

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Authors and Affiliations

  1. School of Physics and Electronic Engineering, Yuxi Normal University, Yuxi, 653100, China

    Junfeng Wang, Tao Zhong & Hongming Zhou

Authors
  1. Junfeng Wang
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  2. Tao Zhong
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  3. Hongming Zhou
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Correspondence to Junfeng Wang.

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This article has been retracted. Please see the retraction notice for more detail: https://doi.org/10.1007/s10586-022-03909-4

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Wang, J., Zhong, T. & Zhou, H. RETRACTED ARTICLE: Fuzzy neural network model construction based on shortest path parallel algorithm. Cluster Comput 22 (Suppl 2), 3413–3418 (2019). https://doi.org/10.1007/s10586-018-2188-x

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  • DOI: https://doi.org/10.1007/s10586-018-2188-x

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