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Sustainability Evaluation of Renewable Energy Incubators Using Interval Type-II Fuzzy AHP-TOPSIS with MEA-MLSSVM

Author

Listed:
  • Guangqi Liang

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China)

  • Dongxiao Niu

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China)

  • Yi Liang

    (School of Management, Hebei Geo University, Shijiazhuang 050031, China
    Strategy and Management Base of Mineral Resources in Hebei Province, Hebei GEO University, Shijiazhuang 050031, China)

Abstract

With the development of renewable energy, renewable energy incubators have emerged continuously. However, these incubators present a crude development model of low-level replication and large-scale expansion, which has triggered a series of urgent problems including unbalanced regional development, low incubation efficiency, low resource utilization, and vicious competition for resources. There are huge challenges for the sustainable development of incubators in the future. A scientific and accurate evaluation approach is of great significance for improving the sustainability of renewable energy incubators. Therefore, this paper proposes a novel method combining an interval type-II fuzzy analytic hierarchy process (AHP) with mind evolutionary algorithm-modified least-squares support vector machine (MEA-MLSSVM). The indicator system is established from two aspects: service capability and operational efficiency. TOPSIS integrated with an interval type-II fuzzy AHP is employed for index weighting and assessment. In the least-squares support vector machine (LSSVM), the traditional radial basis function is replaced with the wavelet transform function (WT), and the parameters are fine-tuned by the mind evolutionary algorithm (MEA). Accordingly, the establishment of a comprehensive sustainability evaluation model for renewable energy incubators is accomplished in this paper. The experimental study reveals that this novel technique has the advantages of scientificity and precision and provides a decision-making basis for renewable energy incubators to realize sustainable operation.

Suggested Citation

  • Guangqi Liang & Dongxiao Niu & Yi Liang, 2021. "Sustainability Evaluation of Renewable Energy Incubators Using Interval Type-II Fuzzy AHP-TOPSIS with MEA-MLSSVM," Sustainability, MDPI, vol. 13(4), pages 1-22, February.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:4:p:1796-:d:495317
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    Citations

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    Cited by:

    1. Alimuddin Alimuddin & Ria Arafiyah & Irma Saraswati & Rocky Alfanz & Partogi Hasudungan & Taufik Taufik, 2021. "Development and Performance Study of Temperature and Humidity Regulator in Baby Incubator Using Fuzzy-PID Hybrid Controller," Energies, MDPI, vol. 14(20), pages 1-21, October.
    2. Rui Ai & Yuhang Zheng & Serhat Yüksel & Hasan Dinçer, 2023. "Investigating the components of fintech ecosystem for distributed energy investments with an integrated quantum spherical decision support system," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-28, December.

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