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Clustering ensemble learning method based on incremental genetic algorithms
Published 2012“…Firstly, an architecture for the clustering ensemble based on incremental genetic-based algorithms is proposed consisting of two phases: (i) to produce cluster partitions as initial populations, (ii) to combine cluster partitions and to generate final clustering solution by incremental genetic based clustering ensemble learning algorithm. …”
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Thesis -
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An investigation towards hostel space allocation problem with stochastic algorithms
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Enhanced segment particle swarm optimization for large-scale kinetic parameter estimation of escherichia coli network model
Published 2021“…Initially, PSO algorithm was adapted to find the globally optimal result based on unorganized particle movement in the search space toward the optimal solution. …”
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Thesis -
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GENETIC ALGORITHM WITH DEEP NEURAL NETWORK SURROGATE FOR THE OPTIMIZATION OF ELECTROMAGNETIC STRUCTURE
Published 2020“…The behavior of Genetic Algorithm (GA) where it generates and evolves the parameters towards a high-quality solution gives an advantage in obtaining ideal combination of parameters to fit in with the simulation. …”
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Final Year Project -
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An improved bat algorithm with artificial neural networks for classification problems
Published 2016“…Then, the proposed BAGD algorithm is frnther hybridized with Simulated Annealing (SA) and Genetic Algorithm (GA) to perform two stage optimization in which the former algorithm finds the optimal solution and the latter algorithm starts from where the first one is converged. …”
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Application Of Genetic Algorithms For Robust Parameter Optimization
Published 2010“…Factors in a parameter design can be expressed as a genetic analogue in a pool of sub-optimal random solutions. Allowing this pool of sub-optimal solutions to evolve over several generations produces fitter generations converging to a pre-defined engineering optimum. …”
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A Tabu Search Approach with Embedded Nurse Preferences for Solving Nurse Rostering Problem
Published 2020“…The methodology consists of two phases: initialization and neighborhood. The semi-random initialization is employed for finding a good initial solution during the initialization phase which avoids the violation of hard constraints, while the neighborhood phase is established for further improving the solution quality with a special representation and innovative neighborhood generations within TS algorithm. …”
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A tabu search approach with embedded nurse preferences for solving nurse rostering problem
Published 2020“…The methodology consists of two phases: initialization and neighborhood. The semi-random initialization is employed for finding a good initial solution during the initialization phase which avoids the violation of hard constraints, while the neighborhood phase is established for further improving the solution quality with a special representation and innovative neighborhood generations within TS algorithm. …”
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A hybrid SP-QPSO algorithm with parameter free adaptive penalty method for constrained global optimization problems
Published 2018“…Further, the algorithm’s performance is improved by Centroidal Voronoi Tessellations method of point initialization promise to visit the entire search space. …”
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A Modified ACO-based Search Algorithm for Detecting Protein Functional Module From Protein Interaction Network
Published 2015“…The search process of ACO-PFMDM has converged effectively compared to some state-of-art algorithms. Moreover, the proposed dynamic update of the heuristic parameters based on entropy has generated high quality tours and it can guide ants toward the effective solutions space in the initial search stages.…”
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Partial examination assignment approaches for solving examination timetabling problems
Published 2016“…However, these traditional approaches bias toward the initial timetable where the improvement algorithms (sometimes) are affected and unable to produce a quality timetable. …”
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Thesis -
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Guidance system based on Dijkstra-ant colony algorithm with binary search tree for indoor parking system
Published 2021“…Dijkstra and ACO are integrated to produce the smart guidance algorithm for the indoor parking system. Dijkstra algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
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A Hybrid ACO-Graph Entropy for Functional Modules Detection From Protein-Protein Interaction Network
Published 2018“…The search process of ACO-PFMDM has converged effectively compared to some state-of-art algorithms. Moreover, the proposed dynamic update of the heuristic parameters based on entropy has generated high quality tours and it can guide ants toward the effective solutions space in the initial search stages.…”
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Improved cuckoo search based neural network learning algorithms for data classification
Published 2014“…In the proposed HACPSO algorithm, initially accelerated particle swarm optimization (APSO) algorithm searches within the search space and finds the best sub-search space, and then the CS selects the best nest by traversing the sub-search space. …”
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Thesis -
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Ball surface representations using partial differential equations
Published 2015“…Hence, this new algorithm is a viable alternative for constructing generalized Ball surfaces. …”
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Potential of data minimization techniques approach in improving DNA sequences alignment and comparison / Syed Abdul Mutalib Al Junid … [et al.]
Published 2012“…This study will initially involve algorithm modification, mathematical formulation, logic design and simulation for data minimization and existing DNA sequences alignment algorithm. …”
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Research Reports -
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Dual optimization approach in discrete Hopfield neural network
Published 2024“…Quantitative evaluations show that the proposed model successfully enhances the optimization of both phases, ranking first compared to 10 recent algorithms for all metrics. In terms of convergence analysis, the proposed model progressed fast towards the optimal solution with only one iteration for all cases. …”
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Study towards real time precise point positioning systems using GPS engine receiver
Published 2004“…The precise single point positioning using single frequency GPS receiver is one of the challenging researches. This study was to initial study towards development of the precise single point position solution with accuracy better than 2 m using a low cost single frequency GPS receiver. …”
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