U
Ujjwal Maulik
Researcher at Jadavpur University
Publications - 384
Citations - 13312
Ujjwal Maulik is an academic researcher from Jadavpur University. The author has contributed to research in topics: Cluster analysis & Fuzzy clustering. The author has an hindex of 46, co-authored 361 publications receiving 11711 citations. Previous affiliations of Ujjwal Maulik include Kalyani Government Engineering College & Indian Statistical Institute.
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Genetic algorithm-based clustering technique
TL;DR: The superiority of the GA-clustering algorithm over the commonly used K-means algorithm is extensively demonstrated for four artificial and three real-life data sets.
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Performance evaluation of some clustering algorithms and validity indices
TL;DR: This article evaluates the performance of three clustering algorithms, hard K-Means, single linkage, and a simulated annealing (SA) based technique, in conjunction with four cluster validity indices, namely Davies-Bouldin index, Dunn's index, Calinski-Harabasz index, andA recently developed index I.
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A Simulated Annealing-Based Multiobjective Optimization Algorithm: AMOSA
TL;DR: A simulated annealing based multiobjective optimization algorithm that incorporates the concept of archive in order to provide a set of tradeoff solutions for the problem under consideration that is found to be significantly superior for many objective test problems.
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Validity index for crisp and fuzzy clusters
TL;DR: A cluster validity index and its fuzzification is described, which can provide a measure of goodness of clustering on different partitions of a data set, and results demonstrating the superiority of the PBM-index in appropriately determining the number of clusters are provided.
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Genetic clustering for automatic evolution of clusters and application to image classification
TL;DR: The searching capability of genetic algorithms has been exploited for automatically evolving the number of clusters as well as proper clustering of any data set and the proposed technique is able to distinguish some characteristic landcover types in the image.