Search Results - (( evolution optimisation based algorithm ) OR ( variable validation clustering algorithm ))
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Optimized clustering with modified K-means algorithm
Published 2021“…In order to obtain the optimum number of clusters and at the same time could deal with correlated variables in huge data, modified k-means algorithm was proposed. …”
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Thesis -
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Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…These algorithms mostly built upon the partitioning k-means clustering algorithm. …”
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Thesis -
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Statistical performance of agglomerative hierarchical clustering technique via pairing of correlation-based distances and linkage methods
Published 2025“…To validate the clustering model on real data, the Spearman-average algorithm was applied to cluster Juru river basin data based on five water quality parameters. …”
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Performance evaluation and benchmarking of an extended computational model of ant colony system for DNA sequence design
Published 2014“…Ant colony system (ACS) algorithm is one of the biologically inspired algorithms that have been introduced to effectively solve a variety of combinatorial optimisation problems. …”
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Prediction of Machine Failure by Using Machine Learning Algorithm
Published 2019“…Validation for the model is analyzed by using validation testing data and cross validation. …”
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Final Year Project -
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A competitive co-evolutionary approach for the nurse scheduling problem
Published 2026“…The competitive approach further exhibits smoother convergence behaviour across generations, indicating stronger optimisation dynamics and improved robustness. These findings demonstrate that competitive co-evolution provides an effective and practical alternative to static fitness-based evolutionary methods for nurse scheduling, with broader applicability to healthcare scheduling and constraint optimisation problems.…”
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Seed disperser ant algorithm for optimization / Chang Wen Liang
Published 2018“…In this research, we applied SDAA to solve the constrained engineering problems and introduce an efficient data clustering algorithm which is hybrid of K-means and SDAA. …”
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Application of Optimization Methods for Solving Clustering and Classification Problems
Published 2011“…Intuitively, samples within a valid cluster are more similar to each other than they are to a sample belonging to a different cluster. …”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding
Published 2025“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding
Published 2025“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed
Published 2012“…In conventional hard clustering approach, the number of clusters was determined by hierarchical clustering and two-step cluster analysis; then the sites were allocated to the appropriate cluster by k-means clustering method. …”
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3D surface roughness measurement for scaliness scoring of psoriasis lesions
Published 2013“…The algorithm has been validated with an accuracy of 94.12. …”
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Stock market turning points rule-based prediction / Lersak Photong … [et al.]
Published 2021“…Finally, rule-based optimisation techniques such as Particle Swarm Optimization (PSO), Differential Evolution (DE) and Grey Wolf Optimizer (GWO) were used to minimise the amount of time employed in the stock market turning points prediction. …”
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Book Section -
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Centre based evolving clustering framework with extended mobility features for vehicular ad-hoc networks
Published 2021“…This framework uses an evolving data clustering algorithm by adopting the concept of grid granularity to capture the features of a cluster more efficiently. …”
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Thesis -
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Independent And Dependent Job Scheduling Algorithms Based On Weighting Model For Grid Environment
Published 2018“…This thesis presents job weighting model using a Twostep clustering to assign the categorical and continuous variables of jobs into classes for both independent and dependent job scheduling. …”
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B-spline curve fitting with different parameterization methods
Published 2020“…After generating control points, distance between the generated and original data points is used to identify the error of the algorithm. Later, genetic algorithm and differential evolution optimization are used to optimise the error of the curve. …”
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Final Year Project / Dissertation / Thesis -
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Reliability assessment of power system generation adequacy with wind power using population-based intelligent search methods
Published 2017“…This study sought to examine the performance of three newly proposed techniques, for reliability assessment of the power systems, namely Disparity Evolution Genetic Algorithm (DEGA), Binary Particle Swarm Optimisation (BPSO), and Differential Evolution Optimization Algorithm (DEOA). …”
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Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level
Published 2024thesis::doctoral thesis -
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iBUST: An intelligent behavioural trust model for securing industrial cyber-physical systems
Published 2024“…In addition, a new optimisation model for finding optimum parameter values in the MEDF and an algorithm for transmuting a 1D quantitative feature into a respective categorical feature are developed to facilitate the model. …”
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