ANFIS structure.

<div><p>Enhancement prediction of load demand is crucial for effective energy management and resource allocation in modern power systems and especially in medical segment. Proposed method leverages strengths of ANFIS in learning complex nonlinear relationships inherent in load demand dat...

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Bibliographic Details
Main Author:	Ahmed G. Ismail (21519374) (author)
Other Authors:	Sayed H. A. Elbanna (21519377) (author), Hassan S. Mohamed (21519380) (author)
Published:	2025
Subjects:	Medicine Biotechnology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified varying data sizes modern power systems mean squared error incorporates sensitivity analysis including adaptive neuro improve predictive accuracy fuzzy inference systems ensure solving limitations effective energy management advanced developments rather achieving higher accuracy using performance metrics latin hypercube sampling combined predictive methodology anfis showing accuracy load demand data anfis </ p load demand anfis combined using python stratified sampling combined lhs simulink matlab risk assessment resource allocation research contribute reducing overfitting proposed approach previous research mse ). monte carlo medical segment lhs model lhs compared lhs ), leverages lhs input variables enhancing adaptability 1000 iterations
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ANFIS structure.

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