Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: , a systematic multi-objective Mamdani fuzzy modeling approach is proposed, which can be vied as an extended version of the previously proposed Singleton fuzzy modeling paradigm. A set of new back-error propagation (BEP) updating formulas are derived so that they can replace the old set developed in the singleton version. With the substitution, the extension to the multi-objective Mamdani Fuzzy Rule-Based Systems (FRBS) is almost endemic. Due to the carefully chosen output membership functions, the inference and the defuzzification methods, a closed form integral can be deducted for the defuzzification method, which ensures the efficiency of the developed Mamdani FRBS. Some important factors, such as the variable length coding scheme and the rule alignment, are also discussed. Experimental results for a real data set from the steel industry suggest that the proposed approach is capable of eliciting not only accurate but also transparent FRBS with good generalization ability.
['Jun Chen', 'Mahdi Mahfouf']
I am writing a research paper on a idea An artificial immune systems based predictive modelling approach for the multi-objective elicitation of mamdani fuzzy rules: A special application to modelling Alloys
[{"from": "human", "value": "I am writing a research paper on a idea An artificial immune systems based predictive modelling approach for the multi-objective elicitation of mamdani fuzzy rules: A special application to modelling Alloys"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: , a systematic multi-objective Mamdani fuzzy modeling approach is proposed, which can be vied as an extended version of the previously proposed Singleton fuzzy modeling paradigm. A set of new back-error propagation (BEP) updating formulas are derived so that they can replace the old set developed in the singleton version. With the substitution, the extension to the multi-objective Mamdani Fuzzy Rule-Based Systems (FRBS) is almost endemic. Due to the carefully chosen output membership functions, the inference and the defuzzification methods, a closed form integral can be deducted for the defuzzification method, which ensures the efficiency of the developed Mamdani FRBS. Some important factors, such as the variable length coding scheme and the rule alignment, are also discussed. Experimental results for a real data set from the steel industry suggest that the proposed approach is capable of eliciting not only accurate but also transparent FRBS with good generalization ability."}]