Search Results - (( initial optimization based algorithm ) OR ( parametric classification using algorithm ))
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Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms
Published 2018“…Hence, this research has proposed three enhanced frameworks, namely, Optimized Gravitational-based (OGC), Density-Based Particle Swarm Optimization (DPSO), and Variance-based Differential Evolution with an Optional Crossover (VDEO) frameworks for data clustering. …”
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Hybrid conjugate gradient using exact line search in photovoltaic system / Muhammad Ariiq Iqbaal Azizul Firdaus
Published 2025“…There are a few classifications of CG method such as classical, hybrid, three-term and parametric CG methods. …”
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Development of compound clustering techniques using hybrid soft-computing algorithms
Published 2006“…Previously, there is limited work on the clustering and classification of biologically active compounds into their activity based classes using fuzzy and neural network. …”
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Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification
Published 2020“…Nevertheless, AC is not required for LCM if the original multi-spectral image is used. The last phase involves developing a new fusion algorithm using SVM and Fuzzy K-Means Clustering (FKM) algorithms for Sentinel 2 data to enhance LCM accuracy. …”
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Comparative Analysis of Low Discrepancy Sequence-Based Initialization Approaches Using Population-Based Algorithms for Solving the Global Optimization Problems
Published 2021“…For an optimization problem, population initialization plays a significant role in metaheuristic algorithms. …”
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Validation on an enhanced dendrite cell algorithm using statistical analysis
Published 2017“…In this study, we evaluated the performance of the enhanced algorithm called dendrite cell algorithm using sensitivity, specificity, false positive rate, and accuracy and validated the result using parametric and non parametric statistical significant tests. …”
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Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman
Published 2019“…In this HPSO algorithm, totally seven particles positions are initialized. …”
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A firefly algorithm based hybrid method for structural topology optimization
Published 2020“…In this paper, a firefly algorithm based hybrid algorithm through retaining global convergence of firefly algorithm and ability to generate connected topologies of optimality criteria (OC) method is proposed as an alternative method to solve stress-based topology optimization problems. …”
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Enhanced Harris's Hawk algorithm for continuous multi-objective optimization problems
Published 2020“…Harris’s hawk multi-objective optimizer (HHMO) algorithm is a MOSIbased algorithm that was developed based on the reference point approach. …”
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Greedy-assisted teaching-learning-based optimization algorithm for cost-based hybrid flow shop scheduling
Published 2025“…However, limited attention has been given to CHFS when considering holistic cost models using efficient algorithms. This paper presents a novel Greedy-Assisted Teaching-Learning-Based Optimization (GTLBO) algorithm for CHFS. …”
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Novel initialization strategy: Optimizing conventional algorithms for global maximum power point tracking
Published 2024“…The major advantages of this approach are eliminating the need to modify the original algorithm, hybridizing with other algorithms, or employing any complex procedures, as in metaheuristic and optimization MPPT algorithms. …”
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Studying the Impact of Initialization for Population-Based Algorithms with Low-Discrepancy Sequences
Published 2021“…Population initialization plays a prominent role in meta-heuristic algorithms for the problem of optimization. …”
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Artificial neural networks based optimization techniques: A review
Published 2023“…The entire set of such techniques is classified as algorithms based on a population where the initial population is randomly created. …”
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An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction
Published 2023“…The cuckoo search algorithm (CSA) is used in this study for optimizing WNNs. …”
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An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction
Published 2023“…The cuckoo search algorithm (CSA) is used in this study for optimizing WNNs. …”
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An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction
Published 2023“…The cuckoo search algorithm (CSA) is used in this study for optimizing WNNs. …”
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An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction
Published 2023“…The cuckoo search algorithm (CSA) is used in this study for optimizing WNNs. …”
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