Research on Regional Differentiation Allocation Mode of Energy Finance based on Attention Mechanism and Support Vector Machine

This paper studies the prediction method of regional differentiated allocation mode of energy finance based on attention mechanism and support vector machine to provide scientific guidance for the future development direction of energy finance in each region. Analysis of the key factors influencing the energy consumption, through the attention mechanism to extract the regional factors such features constitute the details of the sample set, the characteristics of the sample set after implementation of fusion and normalized processing, gain new characteristics of sample set as input to construct support vector machine forecasting model, prediction of energy consumption in each region of the output. According to the results, the differentiated allocation patterns of energy finance in each region are predicted. The results show that the prediction model of this method has high training and test prediction accuracy, and the prediction results are consistent with the actual data in historical statistics. Compared with the existing methods, the method of this study can more scientifically and effectively predict the sustainable and stable development of energy finance in various regions of the city in the future. The energy consumption of the experimental city predicted in this study in the next nine years is from high to low in the order of region C, region a and region B. from this, it is predicted that the regions A, B and C of this city in the future will be applicable to the government market dual oriented Government oriented and market-oriented energy finance allocation models. The prediction results can provide scientific guidance for the sustainable and stable development of energy finance in various regions of the city in the future.

@article{Sun2022,
  title     = {Research on Regional Differentiation Allocation Mode of Energy Finance based on Attention Mechanism and Support Vector Machine},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {13},
  number    = {8},
  year      = {2022},
  publisher = {The Science and Information Organization},
  author    = {Ling Sun and Hao Wu},
  doi       = {10.14569/IJACSA.2022.0130807},
  url       = {https://doi.org/10.14569/IJACSA.2022.0130807}
}