Search Results - (( using computational model algorithm ) OR ( based optimization method algorithm ))
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Sizing optimization of large-scale grid connected photovoltaic system using dolphin echolocation algorithm / Muhammad Zakyizzuddin Rosselan
Published 2018“…Later, an Iterative-based Sizing Algorithm (ISA) was developed to determine the optimal sizing solution which was later used as benchmark for sizing algorithms using optimization methods. …”
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Firefly algorithm for optimal sizing of Standalone Photovoltaic System / Nurizzati Abdul Aziz
Published 2016“…Therefore, optimization methods are often used in the sizing algorithms for such systems. …”
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Firefly algorithm for optimal sizing of stand-alone photovoltaic system / Nur Izzati Abdul Aziz
Published 2016“…Therefore, optimization methods are often used in the sizing algorithms for such systems. …”
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Benchmarking routing algorithms in NoC-based MPSoCs using guaranteed convergence arithmetic optimization with artificial neural networks and fuzzy MCDM
Published 2024“…This study proposed a prediction model-based Artificial Neural Network (ANN) with a Metaheuristic Optimization approach for predicting the utilized routing algorithm by the NoC-based MPSoC platform in order to reduce the time required to specify the NoC-based MPSoC platform configurations. …”
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Ideal combination feature selection model for classification problem based on bio-inspired approach
Published 2020“…The aim of this paper is to exploit the capability of bio-inspired search algorithms, together with wrapper and filtered methods in generating optimal set of features. …”
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Enhancing Wearable-Based Human Activity Recognition with Binary Nature-Inspired Optimization Algorithms for Feature Selection
Published 2026“…The experiment results show how these algorithms could be used to improve methods for recognizing human activities using wearables technology, such as feature selection, parameter adjustment, and model optimization.…”
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Optimization of attribute selection model using bio-inspired algorithms
Published 2019“…The aim of this paper is to investigate the use of bio-inspired search algorithms in producing optimal attribute set. This is achieved in two stages; 1) create attribute selection models by combining search method and feature selection algorithms, and 2) determine an optimized attribute set by employing bio-inspired algorithms.Classification performance of the produced attribute set is analyzed based on accuracy and number of selected attributes. …”
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Data-driven continuous-time Hammerstein modeling with missing data using improved Archimedes optimization algorithm
Published 2024“…Across all experiments, the IAOA-based method demonstrated superior performance compared to AOA and other methods, including a hybrid approach combining the average multi-verse optimizer and sine cosine algorithm, particle swarm optimizer, the sine cosine algorithm, multi-verse optimizer and grey wolf optimizer. …”
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Fuzzy C-Mean And Genetic Algorithms Based Scheduling For Independent Jobs In Computational Grid
Published 2006“…Our model presents the method of the jobs classifications based mainly on Fuzzy C-Mean algorithm and mapping the jobs to the appropriate resources based mainly on Genetic algorithm. …”
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Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms
Published 2020“…The IEM algorithm uses the attraction-repulsion mechanism to change the positions of solutions towards the optimality. …”
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Lexicon-based and immune system based learning methods in Twitter sentiment analysis
Published 2016“…In future work, the accuracy of proposed model can be strengthened by comparative study with other heuristic based searching algorithms such as genetic algorithm, ant colony optimization, swam algorithms and etc.…”
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Conference or Workshop Item -
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Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…The proposed population-based SKF algorithm and the single solution-based SKF algorithm use the scalar model of discrete Kalman filter algorithm as the search strategy to overcome these flaws. …”
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Multilevel optimization for dense motion estimation
Published 2011“…We evaluated the performance of different optimization techniques developed in the context of optical flow computation with different variational models.In particular, based on truncated Newton methods (TN) that have been an effective approach for large-scale unconstrained optimization, we developed the use of efficient multilevel schemes for computing the optical flow.More precisely, we evaluated the performance of a standard unidirectional multilevel algorithm - called multiresolution optimization (MR/Opt), to a bidrectional multilevel algorithm - called full multigrid optimization (FMG/Opt).The FMG/Opt algorithm treats the coarse grid correction as an optimization search direction and eventually scales it using a line search. …”
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Monograph -
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An enhanced segment particle swarm optimization algorithm for kinetic parameters estimation of the main metabolic model of Escherichia coli
Published 2020“…This method was proposed to increase the exploration and the exploitation of the Segment Particle Swarm Optimization algorithm (Se-PSO). …”
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Therefore, in this paper, we proposed Dynamic tasks scheduling algorithm based on attribute reduction with an enhanced hybrid Genetic Algorithm and Particle Swarm Optimization for optimal device selection. …”
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The influence of sentiments in digital currency prediction using hybrid sentiment-based Support Vector Machine with Whale Optimization Algorithm (SVMWOA)
Published 2021“…The proposed Hybrid Sentiment-based Support Vector Machine with a Whale Optimization Algorithm (SVMWOA). will be evaluated and compared based on performance measures. …”
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Proceeding Paper -
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Optimization and discretization of dragonfly algorithm for solving continuous and discrete optimization problems
Published 2024“…Hence, optimization algorithms, consisting of exact and heuristic methods, are crucial for a myriad of real-world applications. …”
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