Hotspots Detection in Spatial Analysis via the Extended Gustafson-Kessel Algorithm
نویسندگان
چکیده
منابع مشابه
Type-2 Projected Gustafson-Kessel Clustering Algorithm
We propose a type-2 based clustering algorithm to capture data points and attributes relationship embedded in fuzzy subspaces. It is a modification of Gustafson Kessel clustering algorithm through deployment of type-2 fuzzy sets for high dimensional data. The experimental results have shown that type-2 projected GK algorithm perform considerably better than the comparative techniques. General T...
متن کاملGustafson-Kessel-like clustering algorithm based on typicality degrees
Typicality degrees were defined in supervised learning as a tool to build characteristic representatives for data categories. In this paper, an extension of these typicality degrees to unsupervised learning is proposed to perform clustering. The proposed algorithm constitutes a GustafsonKessel variant and makes it possible to identify ellipsoidal clusters with robustness as regards outliers.
متن کاملRecursive clustering based on a Gustafson-Kessel algorithm
In this paper an on-line fuzzy identification of Takagi Sugeno fuzzy model is presented. The presented method combines a recursive Gustafson–Kessel clustering algorithm and the fuzzy recursive least squares method. The on-line Gustafson–Kessel clustering method is derived. The recursive equations for fuzzy covariance matrix, its inverse and cluster centers are given. The use of the method is pr...
متن کاملApplication of Gustafson-Kessel clustering algorithm in the pattern recognition for GIS
This paper simulates four typical defects in GIS for PD detection, and uses the pulse, amplitude, phase and number of PD to form the three-dimensional PQN matrix. Based on the PQN, three two-dimensional distributions of Hqmax~Phi, Hqmean~Phi and Hn~Phi can be achieved. Then the new G-K clustering method is introduced to separate the four different defects according to the parameters of Sk, Ku, ...
متن کاملImprovement of Fault Identification and Localization Using Gustafson-Kessel Algorithm In Adaptive Neuro-Fuzzy Inference System
Most of the techniques on identifying fault location depend on parameters of power transmission line. Thus, a complex mathematical solution will be considered which at such conditions, the dependence on line parameters will limit performance of algorithms. An independent or parameters free algorithm is an option to overcome this problem by using an artificial intelligent technique. This paper p...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Advances in Fuzzy Systems
سال: 2013
ISSN: 1687-7101,1687-711X
DOI: 10.1155/2013/876073