Fuzzy If-Then rules
Introduction
In this section, the definition and examples of linguistic variables are given first. Then we explain two interpretations of fuzzy if-then rules and how to obtain a fuzzy relation that represents the meaning of a given fuzzy rule.
Linguistic Variables
As was pointed out by Zadeh [1], conventional techniques for system analysis are intrinsically unsuited for dealing with humanistic system, whose behavior is strongly influenced by human judgment, perception, and emotions. This is a manifestation of what might be called the principle of incompatibility "As the complexity of a system increases, our ability to make precise and yet significant statements about its behavior diminishes until a threshold is reached beyond which precision and significance become almost mutually exclusive characteristics". It was because of this belief that Zadeh proposed the concept of linguistic variables as an alternative approach to model human thinking. This is an approach that, in an approximate manner, serves to summarize information and express it in terms of fuzzy sets in stead of crisp numbers.
Latest Post
- Dependency injection
- Directives and Pipes
- Data binding
- HTTP Get vs. Post
- Node.js is everywhere
- MongoDB root user
- Combine JavaScript and CSS
- Inline Small JavaScript and CSS
- Minify JavaScript and CSS
- Defer Parsing of JavaScript
- Prefer Async Script Loading
- Components, Bootstrap and DOM
- What is HEAD in git?
- Show the changes in Git.
- What is AngularJS 2?
- Confidence Interval for a Population Mean
- Accuracy vs. Precision
- Sampling Distribution
- Working with the Normal Distribution
- Standardized score - Z score
- Percentile
- Evaluating the Normal Distribution
- What is Nodejs? Advantages and disadvantage?
- How do I debug Nodejs applications?
- Sync directory search using fs.readdirSync