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The Improved Least Square Support Vector Machine Based on Wolf Pack Algorithm and Data Inconsistency Rate for Cost Prediction of Substation Projects

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  • Haichao Wang
  • Yi Liang
  • Wei Ding
  • Dongxiao Niu
  • Si Li
  • Fenghua Wang

Abstract

Accurate and stable cost forecasting of substation projects is of great significance to ensure the economic construction and sustainable operation of power engineering projects. In this paper, a forecasting model based on the improved least squares support vector machine (ILSSVM) optimized by wolf pack algorithm (WPA) is proposed to improve the accuracy and stability of the cost forecasting of substation projects. Firstly, the optimal features are selected through the data inconsistency rate (DIR), which helps reduce redundant input vectors. Secondly, the wolf pack algorithm is used to optimize the parameters of the improved least square support vector machine. Lastly, the cost forecasting method of WPA-DIR-ILSSVM is established. In this paper, 88 substation projects in different regions from 2015 to 2017 are chosen to conduct the training tests to verify the validity of the model. The results indicate that the new hybrid WPA-DIR-ILSSVM model presents better accuracy, robustness, and generality in cost forecasting of substation projects.

Suggested Citation

  • Haichao Wang & Yi Liang & Wei Ding & Dongxiao Niu & Si Li & Fenghua Wang, 2020. "The Improved Least Square Support Vector Machine Based on Wolf Pack Algorithm and Data Inconsistency Rate for Cost Prediction of Substation Projects," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-14, December.
    • Handle: RePEc:hin:jnlmpe:6663006
    DOI: 10.1155/2020/6663006
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    Cited by:

    1. Wei Ding & Xuguang Zhao & Weigao Meng & Haichao Wang, 2022. "Smart Evaluation of Sustainability of Photovoltaic Projects in the Context of Carbon Neutrality Target," Sustainability, MDPI, vol. 14(22), pages 1-18, November.
    2. Yi Liang & Yingying Fan & Yongfang Peng & Haigang An, 2022. "Smart Grid Project Benefit Evaluation Based on a Hybrid Intelligent Model," Sustainability, MDPI, vol. 14(17), pages 1-20, September.
    3. Yanhua Chang & Yi Liang, 2023. "Intelligent Risk Assessment of Ecological Agriculture Projects from a Vision of Low Carbon," Sustainability, MDPI, vol. 15(7), pages 1-21, March.

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