Search Results - (( pattern optimization based algorithm ) OR ( based application optimization algorithm ))
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Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman
Published 2019“…In this study, a pattern based using Particle Swarm Optimization (PSO) is proposed named as Hexagon PSO (HPSO). …”
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Improving explicit aspects extraction in sentiment analysis using optimized ruleset / Mohammad Ahmad Jomah Tubishat
Published 2019“…In addition, extraction rules including either pattern-based or dependency-based rules should be selected in a correct way to remove the irrelevant rules and minimize the extraction errors Thus, in this study, to select the most effective extraction rules, an improved version of Whale Optimization Algorithm (IWOA) is developed and applied to a full set of rules. …”
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Mussels wandering optimization algorithmn based training of artificial neural networks for pattern classification
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A simulation based fly optimisation algorithm for swarms of mini autonomous surface vehicles application
Published 2011“…Present paper intends to provide a detailed description of a new bio-inspired Metaheuristic Algorithm. Based on the detailed study of the Drosophila, the flowchart behaviour for the algorithm, code implementation, methodologies and simulation analysis, a novel Fly Optimization Algorithm (FOA) approach is presented. …”
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Performance optimization on axial-flux permanent magnet coreless generator using novel hybrid computational method based on genetic algorithm and pattern search / Lok Choon Long
Published 2016“…Complex real-world problems can be solved by heuristic optimization efficiently. Improved hybrid optimization method using Pattern Search (PS) and Genetic Algorithm (GA) onto Axial-Flux Permanent Magnet (AFPM) Coreless generator is presented in this thesis, and the optimization is based on the popular multi-objective sizing equation. …”
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Clustering ensemble learning method based on incremental genetic algorithms
Published 2012“…In the first and second phases, a threshold fuzzy c-means clustering algorithm as a clusterer and a pattern ensemble learning method based on the incremental genetic-based algorithms are proposed respectively. …”
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Opposition Based Competitive Grey Wolf Optimizer For EMG Feature Selection
Published 2020“…Four state-of-the-art algorithms include particle swarm optimization, flower pollination algorithm, butterfly optimization algorithm, and CBGWO are used to examine the effectiveness of proposed methods in feature selection. …”
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Optimization of multipurpose reservoir operation using evolutionary algorithms / Mohammed Heydari
Published 2017“…To evaluate the hybrid algorithm, optimization of hydro-power energy of Karun dams were considered. …”
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Nature-Inspired Heuristic Frameworks Trends in Solving Multi-objective Engineering Optimization Problems
Published 2025“…These algorithms are inspired and modelled based on the searching behaviour of animals in real life. …”
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Toward heterogeneous computing to facilitate sequential OLAP real-time applications
Published 2016“…The optimized algorithm is dedicated to detect patterns over parallel data streams in Real-Time. …”
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A filtering algorithm for efficient retrieving of DNA sequence
Published 2009“…An optimal alignment process based on the dynamic programming algorithms has shown to have O(n m) time and space complexity. …”
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Optimal Charging Strategy for Plug-in Hybrid Electric Vehicle Using Evolutionary Algorithm
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Optimizing OLAP heterogeneous computing based on Rabin-Karp algorithm
Published 2013“…In this paper, through experimental results and based on Rabin-Karp Algorithm; we propose an optimized heterogeneous solution that takes into account the benefits and the boundaries in order to achieve a better OLAP performance in terms of response time with three times gain. …”
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Proceeding Paper -
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Multi-objective Binary Clonal Selection Algorithm In The Retrieval Phase Of Discrete Hopfield Neural Network With Weighted Systematic Satisfiability
Published 2024“…The proposed algorithm in the retrieval phase showed optimal performance as compared to the baseline algorithms. …”
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