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Genetic Algorithms in Search, Optimization and Machine Learning
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Pattern Recognition with Fuzzy Objective Function Algorithms
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Performance Evaluation of Some Clustering Algorithms and Validity Indices
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Simulated Annealing Using a Reversible Jump Markov Chain Monte Carlo Algorithm for Fuzzy Clustering
IEEE Transactions on Knowledge and Data Engineering
Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series)
Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series)
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Bioinformatics
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A Simulated Annealing-Based Multiobjective Optimization Algorithm: AMOSA
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A fuzzy k-modes algorithm for clustering categorical data
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Cancer Classification using SVM-boosted Multiobjective Differential Fuzzy Clustering
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Expert Systems with Applications: An International Journal
Unsupervised and Supervised Learning Approaches Together for Microarray Analysis
Fundamenta Informaticae
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ISMIS'11 Proceedings of the 19th international conference on Foundations of intelligent systems
Differential evolution for parameterized procedural woody plant models reconstruction
Applied Soft Computing
A grid-density based technique for finding clusters in satellite image
Pattern Recognition Letters
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Pattern Recognition
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Pattern Recognition
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SEMCCO'11 Proceedings of the Second international conference on Swarm, Evolutionary, and Memetic Computing - Volume Part II
Expert Systems with Applications: An International Journal
A novel differential evolution algorithm with adaptive of population topology
ICICA'12 Proceedings of the Third international conference on Information Computing and Applications
Differential Evolution for automatic rule extraction from medical databases
Applied Soft Computing
Optimized bi-dimensional data projection for clustering visualization
Information Sciences: an International Journal
Co-Evolutionary Algorithms Based on Mixed Strategy
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Rough set based fuzzy k-modes for categorical data
SEMCCO'12 Proceedings of the Third international conference on Swarm, Evolutionary, and Memetic Computing
Expert Systems with Applications: An International Journal
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The problem of classifying an image into different homogeneous regions is viewed as the task of clustering the pixels in the intensity space. In particular, satellite images contain landcover types some of which cover significantly large areas, while some (e.g., bridges and roads) occupy relatively much smaller regions. Detecting regions or clusters of such widely varying sizes presents a challenging task. A modified differential evolution based fuzzy clustering technique, is proposed in this article. Real-coded encoding of the cluster centres is used for this purpose. Results demonstrating the effectiveness of the proposed technique are provided for several synthetic and real life data sets as well as for some benchmark functions. Different landcover regions in remote sensing imagery have also been classified using the proposed technique to establish its efficiency. Statistical significance tests have been performed to establish the superiority of the proposed algorithm.