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Iterative Design and Implementation of Rapid Gradient Descent Method

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Artificial Intelligence and Soft Computing (ICAISC 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11508))

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Abstract

Solvers of nonlinear systems of equations are important in software engineering. There are various methods which use gradient approach to find the solution in accordance to gradient descent. This paper presents software testing for proposed implementation of rapid gradient descent method. Results show that implementation is able to solve problems better than classic approach. The gradient path is smooth and faster converge to the final location.

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Acknowledgements

This work is supported by the National key R&D Program of China under Grant NO. 2018YFB0203900 and the Key Research and Development Program of Shaanxi Province (No. 2018ZDXM-GY-036). This job is also supported by Scientific Research Program Funded by Shaanxi Provincial Education Department (Program No. 2013JK1139) and Supported by China Postdoctoral Science Foundation (No. 2013M542370) and the Specialized Research Fund for the Doctoral Program of Higher Education of China (Grant No. 20136118120010).

Author information

Authors and Affiliations

  1. School of Computer Science and Engineering, Xi’an University of Technology, Xi’an, 710048, China

    Wei Wei

  2. College of Science, Southwest Petroleum University, Chengdu, 610500, China

    Bin Zhou

  3. Faculty of Informatics, Kaunas University of Technology, 51368, Kaunas, Lithuania

    Rytis Maskeliūnas & Robertas Damaševičius

  4. Institute of Mathematics, Faculty of Applied Mathematics, Silesian University of Technology, 44100, Gliwice, Poland

    Dawid Połap & Marcin Woźniak

Authors
  1. Wei Wei
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  2. Bin Zhou
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  3. Rytis Maskeliūnas
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  4. Robertas Damaševičius
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  5. Dawid Połap
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  6. Marcin Woźniak
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Corresponding author

Correspondence to Wei Wei .

Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Częstochowa, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Częstochowa, Poland

    Rafał Scherer

  3. Częstochowa University of Technology, Częstochowa, Poland

    Marcin Korytkowski

  4. University of Alberta, Edmonton, AB, Canada

    Witold Pedrycz

  5. AGH University of Science and Technology, Kraków, Poland

    Ryszard Tadeusiewicz

  6. University of Louisville, Louisville, KY, USA

    Jacek M. Zurada

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Wei, W., Zhou, B., Maskeliūnas, R., Damaševičius, R., Połap, D., Woźniak, M. (2019). Iterative Design and Implementation of Rapid Gradient Descent Method. In: Rutkowski, L., Scherer, R., Korytkowski, M., Pedrycz, W., Tadeusiewicz, R., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2019. Lecture Notes in Computer Science(), vol 11508. Springer, Cham. https://doi.org/10.1007/978-3-030-20912-4_48

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  • DOI: https://doi.org/10.1007/978-3-030-20912-4_48

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-20911-7

  • Online ISBN: 978-3-030-20912-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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