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A characteristic standardization method for circuit input vectors based on Hash algorithm

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Abstract

The lengths of input vectors corresponding to different circuits are often quite different, which makes it difficult to standardize them. This paper proposes a characteristic standardization method for circuit input vectors based on hash algorithm. First, the collision rates of different hash algorithms are analyzed, and four representative hash algorithms are selected to process the input vectors. Then, based on the given dataset, their performance is analyzed from collision rate, stability and distribution characteristics, and the best performing RSHash algorithm is selected for further research. Next, we deal with the input vectors using RSHash mapping and partitioning strategy, respectively, and then apply processed input vectors to the deep autoencoder network to perform experiments. The experimental results show that the characteristic standardization method for circuit input vectors based on RSHash algorithm has better performance.

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Acknowledgements

This work was supported in part by Natural Science Foundation of Zhejiang Province under Grant LR20F020002, in part by the National Natural Science Foundation of China under Grant 61802123, in part by the Primary Research and Development Plan of Zhejiang Province under Grant 2020C01097.

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Authors and Affiliations

  1. Qiuzhen College, Huzhou University, Huzhou, 313000, China

    Ying Shi

  2. Zhejiang Province Key Laboratory of Smart Management and Application of Modern Agricultural Resources, Huzhou University, Huzhou, 313000, China

    Ying Shi, Shuyi Huang & Jungang Lou

  3. School of Information Engineering, Huzhou University, Huzhou, 313000, China

    Ying Shi, Shuyi Huang & Jungang Lou

Authors
  1. Ying Shi
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  2. Shuyi Huang
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  3. Jungang Lou
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Correspondence to Shuyi Huang.

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Shi, Y., Huang, S. & Lou, J. A characteristic standardization method for circuit input vectors based on Hash algorithm. J Ambient Intell Human Comput 13, 1505–1513 (2022). https://doi.org/10.1007/s12652-020-02873-4

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  • DOI: https://doi.org/10.1007/s12652-020-02873-4

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