Improved multi-objective clustering with automatic determination of the number of clusters

No abstract is available for this paper.

• Publication year

  2017

• Venue

  Neural computing & applications (Print)

• Publication date

  2017-08-01

• Fields of study

  Mathematics, Computer Science

• Identifiers
  DOI 10.1007/s00521-016-2191-1
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• The irace package: Iterated racing for automatic algorithm configuration

  2016cited by this paper
• Multiobjective Evolutionary Algorithms in Aeronautical and Aerospace Engineering

  2012cited by this paper
• The irace Package: Iterated Race for Automatic Algorithm

  2011cited by this paper
• A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms

  2011cited by this paper
• A survey of Clustering Algorithms

  2010cited by this paper
• A Survey of Evolutionary Algorithms for Clustering

  2009cited by this paper
• Data clustering: 50 years beyond K-means

  2008cited by this paper
• A Node-Marking Technique for Dynamic Slicing of Aspect-Oriented Programs

  2007cited by this paper
• Evolution-Based Tabu Search Approach to Automatic Clustering

  2007cited by this paper
• MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition

  2007cited by this paper
• Multiobjective Genetic Fuzzy Clustering of Categorical Attributes

  2007cited by this paper
• An Evolutionary Approach to Multiobjective Clustering

  2007influential reference
• Multi-Objective Machine Learning

  2006cited by this paper
• Combining advantages of new chromosome representation scheme and multi-objective genetic algorithms for better clustering

  2006influential reference
• Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)

  2006cited by this paper
• Multi-Objective Evolutionary Clustering using Variable-Length Real Jumping Genes Genetic Algorithm

  2006cited by this paper
• An evolutionary clustering algorithm for gene expression microarray data analysis

  2006cited by this paper
• Data Mining And Knowledge Discovery Handbook

  2005cited by this paper
• Quantitative Evaluation of Clustering Results Using Computational Negative Controls

  2004cited by this paper
• Evolutionary Multiobjective Clustering

  2004cited by this paper
• Document Clustering into an Unknown Number of Clusters Using a Genetic Algorithm

  2003cited by this paper
• Evolutionary Algorithms for Solving Multi-Objective Problems

  2002influential reference
• A fast and elitist multiobjective genetic algorithm: NSGA-II

  2002cited by this paper
• Nonparametric genetic clustering: comparison of validity indices

  2001cited by this paper
• Multi-objective optimization using evolutionary algorithms

  2001cited by this paper
• SPEA2: Improving the strength pareto evolutionary algorithm

  2001cited by this paper
• PESA-II: region-based selection in evolutionary multiobjective optimization

  2001cited by this paper
• An Efficient Constraint Handling Method for Genetic Algorithms

  2000cited by this paper
• The Pareto Envelope-Based Selection Algorithm for Multi-objective Optimisation

  2000cited by this paper
• UCI Repository of machine learning databases

  1998cited by this paper
• Clustering with genetic algorithms

  1998cited by this paper
• Introduction to algorithms

  1996influential reference
• Direct multicriteria clustering algorithms

  1992cited by this paper
• Graphs : an introductory approach : a first course in discrete mathematics / Robin J. Wilson, John J. Watkins

  1989cited by this paper

• Inferring gene-pathway associations from consolidated transcriptome datasets: an interactive gene network explorer for Tetrahymena thermophila

  2025cites this paper
• A Multi-objective Genetic Approach to Clustering with Solution Recommendation

  2023cites this paper
• Vehicle Make and Model Recognition as an Open-Set Recognition Problem and New Class Discovery

  2023cites this paper
• A multi-objective vibrating particle system algorithm for data clustering

  2022cites this paper
• Multi-objective memetic differential evolution optimization algorithm for text clustering problems

  2022cites this paper
• Enhanced Connectivity Validity Measure Based on Outlier Detection for Multi-Objective Metaheuristic Data Clustering Algorithms

  2022cites this paper
• Multi-objective evolutionary clustering with complex networks

  2021cites this paper
• A Comprehensive Review of Evaluation and Fitness Measures for Evolutionary Data Clustering

  2021cites this paper
• The minimum latency in location routing fuzzy inventory problem for perishable multi-product materials

  2021cites this paper
• Multi-objective design optimization on building integrated photovoltaic with Trombe wall and phase change material based on life cycle cost and thermal comfort

  2021cites this paper
• A collaborative decision support system for multi-criteria automatic clustering

  2021cites this paper
• A multi-objective design optimization framework for wind turbines under altitude consideration

  2020cites this paper
• TSDCN: Traffic safety state deep clustering network for real‐time traffic crash‐prediction

  2020cites this paper
• Evolutionary multi-objective automatic clustering enhanced with quality metrics and ensemble strategy

  2020cites this paper
• Auto-weighted multi-view co-clustering with bipartite graphs

  2020cites this paper
• Multi-objective clustering algorithm using particle swarm optimization with crowding distance (MCPSO-CD)

  2020cites this paper
• A Deep Convolutional Neural Network Technique for Power Losses Estimation in Distribution Grid

  2020cites this paper
• Sustainable automatic data clustering using hybrid PSO algorithm with mutation

  2019cites this paper
• Word2Cluster: A New Multi-Label Text Clustering Algorithm with an Adaptive Clusters Number

  2019cites this paper
• A Multi-objective Clustering Ensemble Algorithm with Automatic k-Determination

  2019cites this paper
• A novel combinatorial merge-split approach for automatic clustering using imperialist competitive algorithm

  2019cites this paper
• A gene-level hybrid search framework for multiobjective evolutionary optimization

  2018cites this paper
• A Novel Method of Statistical Line Loss Estimation for Distribution Feeders Based on Feeder Cluster and Modified XGBoost

  2017cites this paper
• A Multi-Objective Approach to Fuzzy Clustering using ITLBO Algorithm

  2017influential citation