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The dataset was divided into a schooling group (90% of the info) and a tests team (ten% of the info) To guage the predictive abilities of varied fintech versions, like an adaptive community-based fuzzy inference system (ANFIS), a hybrid neural fuzzy inference process (HyFIS), a fuzzy process Together with the heuristic gradient descent (FS.HGD), and fuzzy inference rules While using the descent process (FIR.DM) models. the choice with the optimum product is contingent on evaluating its functionality In line with precise error standards. The HyFIS model outperformed Other people with lower mistakes in predicting LTRWAs. unbiased t-tests verified statistically sizeable discrepancies between primary and predicted LTRWA for all styles, with HyFIS showing closer predictions. This analyze supplies precious insights into LTRWA prediction applying Sophisticated statistical and equipment learning techniques, depending on a dataset from many countries and a long time. keyword phrases: Islamic banking companies; neural network; whole hazard-weighted belongings; money know-how Islamic banking institutions; neural network; total chance-weighted assets; financial more info know-how Share and Cite
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