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
A theory of reverse triple I method with sustention degree is presented by using the implication operator R0 in every step of the fuzzy reasoning. Its computation formulas of supremum for fuzzy modus ponens and infimu...A theory of reverse triple I method with sustention degree is presented by using the implication operator R0 in every step of the fuzzy reasoning. Its computation formulas of supremum for fuzzy modus ponens and infimum for fuzzy modus tollens are given respectively. Moreover, through the generalization of this problem, the corresponding formulas of α-reverse triple I method with sustention degree are also obtained. In addition, the theory of reverse triple I method with restriction degree is proposed as well by using the operator R0, and the computation formulas of infimum for fuzzy modus ponens and supremum for fuzzy modus tollens are shown.展开更多
文摘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.
基金This work was supported by the National Natural Science Foundation of China (Grant Nos.60074015, 60004010) and Basal Research Foundations of Tsinghua University (Grant No. JC2001029) and 985 Basic Research Foundation of the School of Information Sc
文摘A theory of reverse triple I method with sustention degree is presented by using the implication operator R0 in every step of the fuzzy reasoning. Its computation formulas of supremum for fuzzy modus ponens and infimum for fuzzy modus tollens are given respectively. Moreover, through the generalization of this problem, the corresponding formulas of α-reverse triple I method with sustention degree are also obtained. In addition, the theory of reverse triple I method with restriction degree is proposed as well by using the operator R0, and the computation formulas of infimum for fuzzy modus ponens and supremum for fuzzy modus tollens are shown.
