Search Results - (( developing optimization means algorithm ) OR ( java application learning algorithm ))
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Optimized clustering with modified K-means algorithm
Published 2021“…Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
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Optimal neural network approach for estimating state of energy of lithium-ion battery using heuristic optimization techniques
Published 2023Conference Paper -
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Quantum-Behaved Lightning Search Algorithm to Improve Indirect Field-Oriented Fuzzy-PI Control for im Drive
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…The research starts with developing the hybrid deep learning model consisting of DNN and a K-Means Clustering Algorithm. …”
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Cluster optimization in VANET using MFO algorithm and K-Means clustering
Published 2023“…Proven to be an effective and efficient method for solving optimization problem. To design K-Means algorithm that portion nodes based on their proximities by optimize the distance between nodes within same cluster by assigning them to the closet cluster center. …”
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Data clustering using the bees algorithm
Published 2007“…The authors’ team have developed a new population based search algorithm called the Bees Algorithm that is capable of locating near optimal solutions efficiently. …”
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Development of bacteria foraging optimization algorithm for cell formation in cellular manufacturing system considering cell load variations
Published 2013“…In addition, for this purpose matrix-based bacteria foraging optimization algorithm traced constraints handling (MBATCH) is developed. …”
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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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Structural optimization of 4-DOF agricultural robot arm
Published 2024“…This study studies various optimization algorithms to compare the performance of algorithms that can achieve the optimal length with minimum errors. …”
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Hybrid particle swarm optimization algorithm with fine tuning operators
Published 2009“…This method combines the merits of the parameter-free PSO (pf-PSO) and the extrapolated particle swarm optimization like algorithm (ePSO). In order to accelerate the PSO algorithms to obtain the global optimal solution, three fine tuning operators, namely mutation, cross-over and root mean square variants are introduced. …”
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Modified archive update mechanism of multi-objective particle swarm optimization in fuzzy classification and clustering
Published 2022“…The objective of a multi-objective optimization algorithm is to define the collection of best trade-offs between objectives. …”
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An Educational Tool Aimed at Learning Metaheuristics
Published 2020“…In this paper, we introduce an education tool for learning metaheuristic algorithms that allows displaying the convergence speed of the corresponding metaheuristic upon setting/changing the dependable parameters. …”
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Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems
Published 2011“…The algorithm developed in this thesis contains three sub-algorithms. …”
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment
Published 2013“…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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Developing a hybrid model for accurate short-term water demand prediction under extreme weather conditions: a case study in Melbourne, Australia
Published 2024“…Post-optimization ANN model was trained using eleven different leaning algorithms. …”
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