Exploration and Mining Evaluation System and Price Prediction of Uranium Resources

J. Chen¹, Y. Zhao¹, Q. Song¹, Z. Zhou¹, S. Yang¹

¹Central South University, Changsha, China

Min. miner. depos. 2018, 12(1):85-94

https://doi.org/10.15407/mining12.01.085

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ABSTRACT

Purpose. The paper introduces the development of the Uranium Resources Technical and Economic Evaluation Expert System (URTEEES) from the viewpoint of requirement analysis, system design, functional structure and application etc.

Methods. The system is based on C/B/S mixed mode and applies ASP.NET technology with .Net Framework being selected as the development platform as well as the uranium resources database providing data support at the bottom layer. The paper also proves the efficiency of the system in the context of certain case studies.

Findings. Since the system can performs the functions of scenario analysis, sensitivity analysis, shareholder’s returns analysis, horizontal comparison of different projects, it can improve the ability of project senior decision-makers for rapid response to the rivals and meet the demand of pricing negotiations. Moreover, the system demonstrates its efficiency in the context of case studies as the system incorporates a number of advanced methods, e.g. the Quantum Particle Swarm Optimization (QPSO) Back Propagation (BP) QPSO-BP model which can improve the generalization ability of BP network to predict the uranium price.

Originality. Technical and economic evaluation model can be set up by users independently according to the current stage of a project (mainly, these are exploration stage, development stage and production stage) as well as according to the selected mining method (e.g. underground mining, surface mining, or in-situ leaching mining). Then, the technical and economic evaluation parameters can be generated. By means of inputting the value of each parameter in a simple and convenient way, the evaluation results can be calculated directly and shown in the form of diagrams; moreover, feasibility evaluation report can be generated automatically, making the process of technical and economic evaluation accurate and efficient.

Practical implications. URTEEES performs the functions of decision-making analysis, metal resources database management, data management, comprehensive query etc. The system is a good basis for further development of other expert systems.

Keywords: uranium resources, expert system, C/B/S mixed mode, quantum particle swarm optimization, algorithm, QPSO-BP model

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