Wide usage of various-valued logic functions with help of neural networks in decision-making systems

In this paper we propose a method for representing various-valued logic function in a logical neural network. This logical neural network will keep the totality of cause-and-effect relationships identified using various-valued logic functions within a given specified area. Thus, it becomes possible to transfer a logical algorithm to detect hidden patterns in a given specified area, in case when the values of logical variables are not well-defined and values obscured between zero and one are present. These logic operations are implemented by special logic neural cells–conjunctors and disjunctors.