2014Keji daobaoRequires access

Mineral Resources Predication and Evaluation Methods Based on Uncertainty Measure Theory

HE Huju

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Abstract

The significance of quantitative prediction of mineral resources and uncertainty evaluation was analyzed. Based on theiruncertainty characteristics, uncertainty measure theory was introduced into quantitative prediction of mineral resources anduncertainty evaluation in this paper, and a prediction and evaluation model was proposed. Based on practical geological conditions,seven factors that influence the mineralizing favorability degree were taken into account and uncertainty measure function wasestablished based on the in-situ data. The uncertainty problems in quantitative prediction of mineral resources and uncertaintyevaluation were solved by qualitative analysis and quantitative analysis, respectively. Information entropy theory was used to calculatethe index weight of factors, credible degree recognition criteria were used to judge the mineralizing favorability degree, and the orderwas arranged. This model was employed to evaluate three ore belts in Hutouya mine field in Qinghai. The results show thatuncertainty measure method is reasonable and can provide reference for quantitative prediction of mineral resources and uncertaintyevaluation in the future.

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What this paper is about

The significance of quantitative prediction of mineral resources and uncertainty evaluation was analyzed. Based on theiruncertainty characteristics, uncertainty measure theory was introduced into quantitative prediction of mineral resources anduncertainty evaluation in this paper, and a prediction and evaluation model was proposed. Based on practical geological conditions,seven factors that influence the mineralizing favorability degree were taken into account and uncertainty measure function wasestablished based on the in-situ data. The uncertainty problems in quantitative prediction of mineral resources and uncertaintyevaluation were solved by qualitative analysis and quantitative analysis, respectively. Information entropy theory was used to calculatethe index weight of factors, credible degree recognition criteria were used to judge the mineralizing favorability degree, and the orderwas arranged. This model was employed to evaluate three ore belts in Hutouya mine field in Qinghai. The results show thatuncertainty measure method is reasonable and can provide reference for quantitative prediction of mineral resources and uncertaintyevaluation in the future.

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Available abstract

The significance of quantitative prediction of mineral resources and uncertainty evaluation was analyzed. Based on theiruncertainty characteristics, uncertainty measure theory was introduced into quantitative prediction of mineral resources anduncertainty evaluation in this paper, and a prediction and evaluation model was proposed. Based on practical geological conditions,seven factors that influence the mineralizing favorability degree were taken into account and uncertainty measure function wasestablished based on the in-situ data. The uncertainty problems in quantitative prediction of mineral resources and uncertaintyevaluation were solved by qualitative analysis and quantitative analysis, respectively. Information entropy theory was used to calculatethe index weight of factors, credible degree recognition criteria were used to judge the mineralizing favorability degree, and the orderwas arranged. This model was employed to evaluate three ore belts in Hutouya mine field in Qinghai. The results show thatuncertainty measure method is reasonable and can provide reference for quantitative prediction of mineral resources and uncertaintyevaluation in the future.

Key concepts: Measure (data warehouse), Entropy (arrow of time), Data mining, Computer science, Field (mathematics), Degree (music), Mineral resource classification, Statistics

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