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Research on application potential prediction method for urban energy system based on decision tree

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  • Gu Jiale

Abstract

In order to overcome the problems of low accuracy and low operational efficiency of application potential prediction methods for traditional urban energy system, an application potential prediction method for urban energy system based on decision tree is proposed. The method classifies the energy system data using evidence weight model. According to the classification results, the attributes of urban energy system are classified by using spatial similarity principle, and the spatial topology, orientation and distance relationships of urban energy variables and evaluation units in the scene are extracted. The decision tree is built with the attributes of urban energy system as the sample set. The decision tree is improved by using the probability-based ranking method and Laplace transform. The application potential prediction model for urban energy system is constructed by the improved decision tree. The experimental results show that the method has high accuracy, high efficiency and reliability.

Suggested Citation

  • Gu Jiale, 2020. "Research on application potential prediction method for urban energy system based on decision tree," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 42(3/4), pages 144-161.
    • Handle: RePEc:ids:ijgeni:v:42:y:2020:i:3/4:p:144-161
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    Cited by:

    1. Mehmet Efe Biresselioglu & Muhittin Hakan Demir, 2022. "Constructing a Decision Tree for Energy Policy Domain Based on Real-Life Data," Energies, MDPI, vol. 15(7), pages 1-15, March.

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