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Optimized Neural Network for Research Evaluation of Mineral Resources Carrying Capacity in Southern Shaanxi

Author

Listed:
  • Li YiCan
  • Wei JunHao
  • Ali Arshaghi
  • Araz Darba

Abstract

Evaluation of the carrying capacity of mineral resources is one of the important research content in the implementation of sustainable development. Based on analyzing the metallogenic geological characteristics, distribution, and resource status of mineral resources in southern Shaanxi, this paper establishes an analysis model of mineral resources and mineral advantages based on the analytic hierarchy process and applies them to evaluate the advantages of mineral resources. To provide optimal and efficient results, an improved model of an artificial neural network based on the bat optimization algorithm has been utilized. Through model analysis, the potential value and carrying capacity of mineral resources in three major prefecture-level cities in southern Shaanxi are comprehensively evaluated and analyzed. The results show that the main dominant minerals in southern Shaanxi are gold, lead zinc, and molybdenum ore. There are three grades of mineral resources carrying capacity: Shangluo City is an excellent grade, Hanzhong City is a good grade, and Ankang City is a general grade.

Suggested Citation

  • Li YiCan & Wei JunHao & Ali Arshaghi & Araz Darba, 2022. "Optimized Neural Network for Research Evaluation of Mineral Resources Carrying Capacity in Southern Shaanxi," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-10, August.
    • Handle: RePEc:hin:jnlmpe:7311245
    DOI: 10.1155/2022/7311245
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