Intuitionistic Neuro-Fuzzy Optimization in the Management of Medical Diagnosis
Intuitionistic Neuro-Fuzzy Optimization in the Management of Medical Diagnosis作者机构：Department of Mathematics S. S. V. (P. G.) College Hapur India Department of Mathematics Keshav Mahavidyalaya University of Delhi New Delhi India Department of Mathematics Chaudhary Charan Singh University Meerut India
出 版 物：《Applied Mathematics》 (应用数学（英文）)
年 卷 期：2021年第12卷第11期
页 面：993-1020页
学科分类：0711[理学-系统科学] 07[理学] 08[工学] 081101[工学-控制理论与控制工程] 0811[工学-控制科学与工程] 071102[理学-系统分析与集成] 081103[工学-系统工程]
主 题：Intuitionistic Fuzzy Set Neural Network Neuro-Fuzzy System Intuitionistic Neuro-Fuzzy System Optimization Medical Diagnosis
摘 要：Diabetes has become a major concern nowadays and its complications are affecting various organs of a diabetic patient. Therefore, a multi-dimensional technique including all parameters is required to detect the cause, its proper diagnostic procedure and its prevention. In this present work, a technique has been introduced that seeks to build an implementation for the intelligence system based on neural networks. Moreover, it has been described that how the proposed technique can be used to determine the membership together with the non-membership functions in the intuitionistic environment. The dataset has been obtained from Pima Indians Diabetes Database (PIDD). In this work, a complete diagnostic procedure of diabetes has been introduced with seven layered structural frameworks of an Intuitionistic Neuro Sugeno Fuzzy System (INSFS). The first layer is the input, in which six factors have been taken as an input variable. Subsequently, a neural network framework has been developed by constructing IFN for all the six input variables, and then this input has been fuzzified by using triangular intuitionistic fuzzy numbers. In this work, we have introduced a novel optimization technique for the parameters involved in the INSFS. Moreover, an inference system has also been framed for the neural network known as INFS. The results have also been given in the form of tables, which describe each concluding factor.
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