The generalized inductive logic causal model that can synthetically process fuzzy indeterminacy and random indeterminacy was proposed in this paper. On this basis, the new logic indeterminacy causalinductive automati...
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ISBN:
(纸本)9780878492329
The generalized inductive logic causal model that can synthetically process fuzzy indeterminacy and random indeterminacy was proposed in this paper. On this basis, the new logic indeterminacy causalinductive automatic reasoning mechanism based on fuzzy state description was put forward. At the end of this paper its application on the development of intelligent controller was discussed.
Aiming at the research that using more new knowledge to develope knowledge system with dynamic accordance, and under the background of using Fuzzy language field and Fuzzy language values structure as description fram...
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Aiming at the research that using more new knowledge to develope knowledge system with dynamic accordance, and under the background of using Fuzzy language field and Fuzzy language values structure as description framework, the generalized cell Automation that can synthetically process fuzzy indeterminacy and random indeterminacy and generalized inductive logic causal model is brought forward. On this basis, a kind of the new method that can discover causal association rules is provded. According to the causal information of standard sample space and commonly sample space, through constructing its state （abnormality） relation matrix, causal association rules can be gained by using inductive reasoning mechanism. The estimate of this algorithm complexity is given,and its validiw is proved through case.
Based on cellular automata theory, inductivelogiccausalmodel is proposed. Then the generalizedcausal cellular automata, which can deal with both random uncertainty and fuzzy uncertainty, is proposed by integrating...
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ISBN:
(纸本)0780394224
Based on cellular automata theory, inductivelogiccausalmodel is proposed. Then the generalizedcausal cellular automata, which can deal with both random uncertainty and fuzzy uncertainty, is proposed by integrating the inductivelogiccausalmodel and language field theory. Based on the generalizedcausal cellular automata, the generalizedcausalinductive reasoning model is presented. Comparisons with ordinary fuzzy reasoning are listed. Finally, the applications of proposed methods are discussed in brief.
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