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The research presented in this book shows how combining deep neural networks with a special class of fuzzy logical rules and multi-criteria decision tools can make deep neural networks more interpretable – and even, in many cases, more efficient.
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It also examines approximations of four notable probability distributions (Weibull, exponential, logistic and normal) using a uni?ed probability distribution function, and presents a fuzzy arithmetic-based time series model that provides an easy-to-use forecasting technique.