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Titlebook: Hybrid Intelligent Systems Based on Extensions of Fuzzy Logic, Neural Networks and Metaheuristics; Oscar Castillo,Patricia Melin Book 2023

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發(fā)表于 2025-3-28 15:28:54 | 只看該作者
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發(fā)表于 2025-3-28 20:41:09 | 只看該作者
Application of Compensatory Fuzzy Logic in Diabetes Problem Using Pima-Indians Datasetaused by defects in insulin secretion, insulin action, or both. The effect of DM includes long term damage, dysfunction and failure of organs. DM is classified into four general categories: (1) the immune system destroys the cells in the pancreas that produces insulin, (2) the body does not properly
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發(fā)表于 2025-3-29 02:59:24 | 只看該作者
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發(fā)表于 2025-3-29 06:09:47 | 只看該作者
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發(fā)表于 2025-3-29 09:37:40 | 只看該作者
A New Selection and Class Prediction Using Type-1 Fuzzy Logic Applied to a Convolutional Neural Netwfunction, which predicts based on percentages of the image and shows which is more likely based on its predictions and its highest percentages. In the proposal, fuzzy logic is used and we show that its results and predictions are correct using Type-1 fuzzy logic when applied to a convolutional neura
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發(fā)表于 2025-3-29 14:47:23 | 只看該作者
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發(fā)表于 2025-3-29 16:27:25 | 只看該作者
Yutzil Poma,Patricia Melinie; die Zahl der kritischen Einw?nde dürfte derjenigen der Operationalisierungsversuche nicht nachstehen. Gleichwohl hat er Generationen von Lehrern gute Dienste geleistet, bedeutete es doch eine hocherwünschte Entlastung, die Ursache im Kind suchen — und natürlich auch finden — zu k?nnen, wenn die
48#
發(fā)表于 2025-3-29 22:03:55 | 只看該作者
Book 2023resented. In addition, the above-mentioned methods are presented in application areas such as, intelligent control and robotics, pattern recognition, medical diagnosis, decision-making, time series prediction and optimization of complex problems. The book contains a collection of papers focused on h
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發(fā)表于 2025-3-30 03:56:53 | 只看該作者
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發(fā)表于 2025-3-30 04:31:08 | 只看該作者
Fuzzy Dynamic Adaptation of an Artificial Fish Swarm Algorithm for the Optimization of Benchmark Fun to improve the performance on the results. The efficiency of the Fuzzy AFSA (FAFSA) demonstrate that it is an excellent algorithm to solve benchmark sets of functions. The FAFSA has proven to be successful in the implementation of various benchmarking optimization problems. A comparative with the original AFSA is presented.
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