editorial fuzzy methods for data analysis Exploratory data-driven methods such as Fuzzy clustering analysis (FCA) and Principal component analysis (PCA) may be considered as hypothesis-generating p... FD Martino,I Perfilieva,S Sessa,... 被引量: 0发表: 2019年 Fuzzy data envelopment analysis (DE...
Image segmentation is considered an important step in image processing. Fuzzy c-means clustering is one of the common methods of image segmentation. However, this method suffers from drawbacks, such as sensitivity to initial values, entrapment in local o
It also presents optimization techniques such as fuzzy linear and nonlinear programming, applications to graph problems and fuzzy combinatorial methods such as fuzzy dynamic programming. In addition, the book also accounts for advances in fuzzy data analysis, fuzzy statistics, and applications to ...
"Qualitative Comparative Analysis" (QCA) is an increasingly applied methodological tool in comparative social sciences. It is well suited for the analysis of causally complex claims framed in terms of necessity and sufficiency. This article presents the epistemology of QCA and discusses its applicability...
Surprisingly, however, the fact that these two interpretations also call for very different types of extensions of existing learning algorithms and methods for data analysis seems to be largely ignored in the literature. Under the ontic view, a variable can assume a fuzzy set as its “true ...
P Ghaderyan,A Abbasi,MH Sedaaghi - 《Journal of Neuroscience Methods》 被引量: 16发表: 2014年 An optimized feature selection technique based on incremental feature analysis for bio-metric gait data classification The classification of humanoid locomotion is a troublesome exercise because of non-linea...
This paper develops DEA models using imprecise data represented by fuzzy sets (i.e., “fuzzy DEA” models). It is shown that fuzzy DEA models take the form of fuzzy linear programming which typically are solved with the aid of some methods to rank fuzzy sets. As an alternative, a ...
“Fuzzy Management Methods” fuzzy logic is applied to extend portfolio analysis, scoring methods, customer relationship management, performance measurement, web reputation, web analytics and controlling, community marketing and other business domains to improve managerial decisions. Thus, fuzzy logic can ...
linear combination of the inputs. Examples include the multivariate linear regression models. Data-driven nonlinear regression is adopted when the input–output dependence is nonlinear and can not be covered by linear modeling. There is a plethora of methods for nonlinear regression, and its ...
A sensitivity analysis was performed by comparing the results obtained from different methods [65]. Hence, the decision matrix\({M}_{3}\)extracted from [70] was used. The results obtained from the Fuzzy-MACBETH, MACBETH, and Grey-MACBETH methods [70] are shown in Table8. Additionally, the...