Translations Of Neural Networks based on Fuzzy Weights for Binary Keys within Delayed and Actual Time

Abstract

The Key facts of Translations are meant to validated the Fuzzy Weights. Moreover, In our case Fuzzy weights are based on Logical Reasoning and Logical Thinking, even though fuzzy logics are not concerned with data rather it depends on thought process based on human brain Imitation. Generally, at some point mankind depends on his own creations and tries to understand its usage through Machine Language or so called Machine Teaching and this is were humans try to understand fuzzy concepts based on binary language, moreover this translations are meant to become complicated the more we go deeper but here comes our originality of introducing fuzzy weights or logic based on Switching Theory Logical design which produces binary keys instead of values, we concentrated on reducing complexity of Machine Teaching through fuzzy weights.