In this regard, various defuzzification methods viz. max-membership, centroid, weighted-average and mean-max methods are discussed here. This chapter also contains few MATLAB defuzzification programs.Concepts of Soft Computingdoi:10.1007/978-981-13-7430-2_7Snehashish Chakraverty...
Advanced Concepts in Fuzzy Logic and Systems with Membership Uncertainty Janusz T. Starczewski Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 284)) 1420 Accesses Abstract At the present time, the only deficiency in developing efficient realizations of general ...
Defuzzification methods; Inference mechanisms; Construction of data base and rule base of FLC; The ball and beam problem; Aggregation in fuzzy system modelin... R Fullér - 《Advances in Soft Computing》 被引量: 401发表: 2000年 Simulation-based evaluation of defuzzification-based approaches to fu...
The purpose of research is to examine the hypothesis that the area ratio method can be used to compensate for the defuzzification interval narrowing error inherent in traditional models, such as center of gravity sums, height models, first maxima, mean maxima, and last maxima. Methods . A fuzzy...
This study here proposes a data-driven algorithm of fuzzy model build on a new parameterized defuzzification method, called Mid Variation Method (MVM), with fuzzy time series that integrates a soft computing technique, termed as Particle Swarm Optimization (PSO). The performance of the algorithm ...
doi:10.1080/10798587.2005.10642892Jorge S. Benitez-ReadInstituto National de Investigaciones Nucleares & Institute Tecnologico de TolucaRegulo Lopez-CallejasJoel O. Pacheco-SoteloLuis C. Loncoria-GandaraTaylor & FrancisIntelligent Automation & Soft Computing...
Couso I, Sanchez L (2008) Defuzzification of fuzzy p -values. In: Advances in soft computing, vol 48 (Soft methods for handling variability and imprecision). Springer, Heidelberg, pp 126–132I. Couso, L. S´anchez. Defuzzification of Fuzzy p- Values. Advances in Soft Computing (2008) ...
The main objective of this investigation is to propose a defuzzification process of a trapezoidal type-2 fuzzy variable centred on critical value-based reduction method and nearest interval approximation, i.e. 伪-cut of fuzzy number. In this context, this paper proposes some ...
Most methods constituting the soft computing concept can not handle data with missing or unknown feature values. Neural networks are able to perfectly fit to data and fuzzy logic systems use interpretable knowledge. In the paper we incorporate rough set theory to neuro-fuzzy system of very ...
These indicate that the presented hybrid model has advantages in granting flexibility to the preferences of decision makers.doi:10.1016/j.asoc.2020.106207Hai LiWei WangLei FanQingzhao LiXuezhen ChenApplied Soft Computing