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Study on fasART neuro-fuzzy networks for distinguishing the difficulty degree of top coal caving in steep seam 被引量:1
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作者 冯涛 赵伏军 林剑 《Journal of Coal Science & Engineering(China)》 2005年第2期5-8,共4页
Distinguishing the difficulty degree of top coal caving was a precondition of the popularization and application of the roadway sub-level caving in steep seam. Because of complexity and uncertainty of the coal seam, t... Distinguishing the difficulty degree of top coal caving was a precondition of the popularization and application of the roadway sub-level caving in steep seam. Because of complexity and uncertainty of the coal seam, the expression of influence factors was diffi-culty with exact data. According to the fuzzy and uncertainty of influence factors, triangular fuzzy membership functions were adopted to carry out the factors ambiguity, of which the factors not only have the consistency of semantic meaning, but also dissolve sufficiently expert knowledge. Based on the properties and structures of fasART fuzzy neural net-works of fuzzy logic system and practical needs, a simplified fasART model was put for-ward, stability and reliability of the network were improved, the deficiency of learning sam-ples and uncertainty of the factors were better treated. The method is of effective and practical value was identified by experiments. 展开更多
关键词 steep coal seam difficulty degree of top coal caving AMBIGUITY membershipfunction fuzzy reasoning fasART fuzzy neural networks
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