# Singleton Type 1 Fuzzy Logic Systems: No Uncertainties

## Introduction

There is uncertainty in every real application, and when faced with high levels of uncertainty, its performance may not be true. So it's important that these usage systems are worth dealing with these uncertainties. Fuzzy set (FS) and fuzzy logic system (FLS) are existing concepts and techniques that have been chosen as the methodology of tower systems that can unleash new performance in uncertainty and inaccuracies. There are many sources of uncertainty faced by FLS, such as the presence of noise in training data, well- represented inputs and outputs of noise, and linguistic uncertainty related to the linguistic terminology of rule based protectors (Hagras, 2007).

The non-singleton fuzzy logic system (NSFLS) was introduced to model the uncertainty of the input signal as an extension of the singleton fuzzy logic system (SFLS), which is not an issue when the input data is corrupted due to measurement noise. In NSFLS, the inputs are modeled as FSs and are no longer well-performing values. NSFLS has been used successfully in a variety of applications, and new advances in the development of new types of NSFLS have shown excellent results (Aladi et al., 2016).

## Rules

Fuzzy rules are the confusion of verbal statements that describe how a fuzzy inference system (FIS) creates visualizations with regard to classifying inputs or executives as outputs. Fuzzy rules are written unchanged in trace format.

(inputl is membership functionl) and/or (input2 is membership function). Then (output к is the output membership function k).

For example, you could create a rule like "High temperature and high humidity make the room hot."

It should have a membership function that finds out exactly what the upper temperature (inputl), upper humidity (input2), and hot room (out- putl) mean. This process of taking an input like temperature and processing it through a member function to determine the middle point with a "high" temperature is tapped fuzzification. Also, in the fuzzy rule, you need to find exactly the middle point with "and"/"or". This is a tab-delimited fuzzy combination.