logic. Both the simulation and the control of the aforementioned device have been done by using MATLAB’s fuzzy logic toolbox. Keywords: Fuzzy Logic, Washing Machine, MatLab, Optimization, Automatic Sensing 1. Introduction Fuzzy logic is a concept which helps computers in ...
Type-2 fuzzy logic refers to a fuzzy logic system that has gained popularity in various applications, especially in pattern recognition and classification problems within the field of Computer Science. AI generated definition based on: Expert Systems with Applications, 2013 ...
Institute of Electric and Electronic EngineerWESCON/94. Idea/Microelectronics.: Western Electronic Show and Convention, 1994Banks W (1994) Mixing crisp and fuzzy logic in applications. In: WESCON’94 idea microelectronics Conference record, Anaheim, CA, pp 94–97...
Du et al. [7] used the random forest (RF) algorithm to build a mapping model between NLSR terms and topological and metric variables. As these crisp models translate one geometric representation to one and only one term, they cannot handle the mapping of multiple terms, let alone different ...
In general, fuzzy inference is a method that interprets the values in the input vector and, based on some set of rules, assigns values to the output vector. Fuzzy Sets Fuzzy logic starts with the concept of a fuzzy set. Afuzzy setis a set without a crisp, clearly defined boundary. It...
When m is close to 1, the cluster center closest to the example is given a much larger weight than the others, and the algorithm is most similar to k-means. The fuzzy c-means algorithm (Algorithm 12.6) is similar to the crisp k-means algorithm (Algorithm 12.4). It minimizes the intra...
Including Fuzzy logic in decision-making enables considering ambiguous aspects, uncertainty, or indecision permeating real-world problems [69]. By mathematically formalizing such imprecisions, [77] expanded the image set of the characteristic function of a classic (or crisp) set, in which the Fuzzy...
Interpretability is the dominant feature of a fuzzy model in security-oriented fields. Traditionally fuzzy models based on expert knowledge have obtained well interpretation innately but imprecisely. Numerical data based fuzzy models perform well in prec
To address these disturbances this work present a novel approach utilizing fuzzy logic (FL) to develop multi-feeder interline unified power-quality conditioners (MF-IUPQCs). The MF-IUPQC has three legs and three levels, each of which has four diode-clamped inverters. Switching is carried out ...
An adaptive neuro-fuzzy inference system is defined as an intelligent synthesis of neural networks and fuzzy logic, combining the robustness and learning capabilities of neural networks with the ability to model imprecise knowledge using fuzzy logic. ...