基于模糊综合评判的金矿评价模型

论文编号:XXLW107 论文字数:9534,页数:29

摘   要
 本文将二级模糊综合评判模型应用于对托孜库巴依金矿资源禀赋优势的评价，分别建立了主因素决定型、主因素突出型和加权平均三类共四个模型，四个模型的评判结果一致为“满意”。
 通过参考相关文献并听取专家的意见，本文选取了“储量资源”、“矿床开采技术条件”、“选冶条件”和“自然经济地理”四类总共20个指标作为评判的因素集，以“很满意”、“满意”、“一般”、“不满意”和“很不满意”五个评语建立评判集（评语集）。对数据进行统计和归一化处理后，得到了各一级指标和总目标的权重以及评判矩阵。在完成这些准备工作后，首先对各一级指标进行评判，将评判结果组合作为新的评判矩阵，并对矿产资源禀赋优势进行评判。   根据这样的思路，本文用C语言编写了一个求解该问题的程序，给出了二级模糊综合评判的解法，并进行实际应用。应用结果表明，该模型便捷、有效，具有一定的应用性。
 
关键词：模糊综合评判 金矿 C语言
Abstract

    Second-index fuzzy comprehensive judgment model was applied to the mineral resource endowments advantage evaluation of the TuoZiKuBaYi gold mine in this paper. Three kinds of four models --the main factors determination, the main factors highlighted and the weighted average -- were established. The four models attained a consistent result as "satisfactory."     Referenced to relevant literatures and experts’ advices, a total of 20 indicators of four types--" resource reserves ", "deposit mining technical conditions", " mineral separation and smelting conditions " and " Physical and economic geography"-- of evaluation factors was selected as factor set . A set to " very satisfied "or" satisfied "," fair "," unsatisfactory "and" very dissatisfied " was established as evaluation set (reviews set). After statistical data was normalized, the weight of level one indicators and the overall goal were achieved, as well as the evaluation matrix. After completed these preparations, the judges of level one indicator were carried out, and, the results of assessments can be combined as a new evaluation matrix. Then, mineral resource endowment advantage was evaluated. According to the above thoughts, a C language program to solve second-index fuzzy comprehensive judgment was written, which solved the problem and achieved results. Application results show that the model is efficient, effective and has a certain application value.
Keywords: fuzzy comprehensive judgment; gold mine; C language
 
目录
摘   要 i
Abstract ii
目录 iii
第一章 前 言 1
第二章 模糊综合评判 2
2.1  模糊综合评判综述 2
2.2  模糊综合评判的优缺点 2
2.3  模糊综合评判的步骤 2
2.4  模糊综合评判数学模型的改进 3
2.4.1 多层次模型 4
2.4.2 广义模糊运算的综合决策模型M(∧*,∨*) 5
第三章 模型应用 7
3.1　评价指标体系的构建 7
3.2　指标数据的采集和处理 9
3.2.1 评判矩阵的确定 9
3.2.2 指标权重向量的确定 10
3.4  四个模糊综合评判模型 12
3.4.1 模型I:  M(∧,∨) 12
3.4.2 模型II: M(·, ∨) 12
3.4.3 模型III: M(∧,⊕) 12
3.4.4 模型IV: M(·,⊕) 13
第四章 结果分析 13
致  谢 14
参考文献 16
附录1 17
附录2 24

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