Fuzzy inference system(FIS)is a process of fuzzy logic reasoning to produce the output based on fuzzified inputs.The system starts with identifying input from data,applying the fuzziness to input using membership func...Fuzzy inference system(FIS)is a process of fuzzy logic reasoning to produce the output based on fuzzified inputs.The system starts with identifying input from data,applying the fuzziness to input using membership functions(MF),generating fuzzy rules for the fuzzy sets and obtaining the output.There are several types of input MFs which can be introduced in FIS,commonly chosen based on the type of real data,sensitivity of certain rule implied and computational limits.This paper focuses on the construction of interval type 2(IT2)trapezoidal shape MF from fuzzy C Means(FCM)that is used for fuzzification process of mamdani FIS.In the process,upper MF(UMF)and lower MF(LMF)of the MF need to be identified to get the range of the footprint of uncertainty(FOU).This paper proposes Genetic tuning process,which is a part of genetic algorithm(GA),to adjust parameters in order to improve the behavior of existing system,especially to enhance the accuracy of the system model.This novel process is a hybrid approach which produces Genetic Fuzzy System(GFS)that helps to enhance fuzzy classification problems and performance.The approach provides a new method for the construction and tuning process of the IT2 MF,based on the FCM outcomes.The result is compared to Gaussian shape IT2 MF and trapezoid IT2 MF generated by the classic GA method.It is shown that the proposed approach is able to outperform the mentioned benchmarked approaches.The work implies a wider range of IT2 MF types,constructed based on FCM outcomes,and an optimum generation of the FOU so that it can be implemented in practical applications such as prediction,analytics and rule-based solutions.展开更多
An economic evaluation of a network of distributed energy resources （DERs） comprising a microgrid structure of power delivery system in an Indian scenario has been made. The mathematical analysis is based on the app...An economic evaluation of a network of distributed energy resources （DERs） comprising a microgrid structure of power delivery system in an Indian scenario has been made. The mathematical analysis is based on the application of tuned genetic algorithm （TGA）. The analyses for optimal power operation pertaining to minimum cost have been made for two cases in Indian power delivery system. The first case deals with the consumers＇ individual optimal operation of DERs, while in the second one, consumers altogether form a microgrid with the optimal supply of power from DERs. The total annual costs for these two cases are found to be economically competitive and encouraging. A reduction of approximately 5.7% in the annual cost has been obtained in the case of microgid system than that in the separately operating consumers＇ system for a small locality of India. It is observed that the application of TGA results in a reduction of the minimum cost depicting an improved outcome in terms of energy economy.展开更多
基金The works presented in this paper are part of an ongoing research funded by the Fundamental Research Grant Scheme(FRGS/1/2018/ICT02/UTP/02/1)a grant funded by the Ministry of Higher Education,Malaysia and the Yayasan Universiti Teknologi PETRONAS grant(015LC0-274 and 015LC0-311).
文摘Fuzzy inference system(FIS)is a process of fuzzy logic reasoning to produce the output based on fuzzified inputs.The system starts with identifying input from data,applying the fuzziness to input using membership functions(MF),generating fuzzy rules for the fuzzy sets and obtaining the output.There are several types of input MFs which can be introduced in FIS,commonly chosen based on the type of real data,sensitivity of certain rule implied and computational limits.This paper focuses on the construction of interval type 2(IT2)trapezoidal shape MF from fuzzy C Means(FCM)that is used for fuzzification process of mamdani FIS.In the process,upper MF(UMF)and lower MF(LMF)of the MF need to be identified to get the range of the footprint of uncertainty(FOU).This paper proposes Genetic tuning process,which is a part of genetic algorithm(GA),to adjust parameters in order to improve the behavior of existing system,especially to enhance the accuracy of the system model.This novel process is a hybrid approach which produces Genetic Fuzzy System(GFS)that helps to enhance fuzzy classification problems and performance.The approach provides a new method for the construction and tuning process of the IT2 MF,based on the FCM outcomes.The result is compared to Gaussian shape IT2 MF and trapezoid IT2 MF generated by the classic GA method.It is shown that the proposed approach is able to outperform the mentioned benchmarked approaches.The work implies a wider range of IT2 MF types,constructed based on FCM outcomes,and an optimum generation of the FOU so that it can be implemented in practical applications such as prediction,analytics and rule-based solutions.
文摘An economic evaluation of a network of distributed energy resources （DERs） comprising a microgrid structure of power delivery system in an Indian scenario has been made. The mathematical analysis is based on the application of tuned genetic algorithm （TGA）. The analyses for optimal power operation pertaining to minimum cost have been made for two cases in Indian power delivery system. The first case deals with the consumers＇ individual optimal operation of DERs, while in the second one, consumers altogether form a microgrid with the optimal supply of power from DERs. The total annual costs for these two cases are found to be economically competitive and encouraging. A reduction of approximately 5.7% in the annual cost has been obtained in the case of microgid system than that in the separately operating consumers＇ system for a small locality of India. It is observed that the application of TGA results in a reduction of the minimum cost depicting an improved outcome in terms of energy economy.
