Search Results - (( parameter evaluation case algorithm ) OR ( pattern optimization based algorithm ))
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Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm
Published 2018“…Seven performance indexes were examined to evaluate the performance of the proposed Muskingum model integrated with IBA, with other models that were also based on the Muskingum Model with three-parameters but utilized different optimization algorithms. …”
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Computational dynamic support model for social support assignments around stressed individuals among graduate students
Published 2020“…The algorithm complexity analysis was used to measure the execution time in the worst case. …”
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Modified word representation vector based scalar weight for contextual text classification
Published 2024“…To validate this algorithm, the modified word vectors are compared with original LLM-generated word vectors to evaluate their reflection of the intended context. …”
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Development of a multi criteria decision support system using convolutional neural network and jaya algorithm for water resources management / Chong Kai Lun
Published 2021“…The developed models were applied to three different case studies to evaluate the performance of the models. …”
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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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Interference reduction by null-forming optimization based MVDR technique using gravitational search algorithm
Published 2017“…In the present work, Gravitational Search Algorithm (GSA) is a new modern metaheuristic optimization technique used for optimizing the MVDR null-forming level by controlling the excitation weight coefficients in a linear antenna array radiation pattern synthesis. …”
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Mussels wandering optimization algorithmn based training of artificial neural networks for pattern classification
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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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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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10
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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T-way testing : a test case generator based on melody search algorithm
Published 2015“…Next, TTT-MS will be executed through main algorithms to generate Parameters Interaction List, Parameter Values Interaction List, and finally generate final Test Cases based on Melody Search Algorithm. …”
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Undergraduates Project Papers -
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Optimizing Central Pattern Generators (CPG) Controller For One Legged Hopping Robot By Using Genetic Algorithm (GA)
Published 2018“…Therefore,a computational stochastic optimization method; GA is designed to optimize the CPG controller parameters. …”
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Medical Image Analysis Using Deep Learning and Distribution Pattern Matching Algorithm
Published 2023Article -
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Improved flower pollination optimization algorithm based on swap operator and dynamic switch probability selection
Published 2023“…Furthermore, it is hybridized with the Pattern Search algorithm to ensure the optimality of the solution. …”
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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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Proceeding Paper -
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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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Artificial neural networks based optimization techniques: A review
Published 2023“…In the last few years, intensive research has been done to enhance artificial intelligence (AI) using optimization techniques. In this paper, we present an extensive review of artificial neural networks (ANNs) based optimization algorithm techniques with some of the famous optimization techniques, e.g., genetic algorithm (GA), particle swarm optimization (PSO), artificial bee colony (ABC), and backtracking search algorithm (BSA) and some modern developed techniques, e.g., the lightning search algorithm (LSA) and whale optimization algorithm (WOA), and many more. …”
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Hybrid Artificial Bees Colony Algorithms For Optimizing Carbon Nanotubes Characteristics
Published 2018“…Chemical Vapor Deposition (CVD) is the most efficient method for CNTs production.However,using CVD method encounters crucial issues such as customization,time and cost.Therefore,Response Surface Methodology (RSM) is proposed for modeling and the ABC-βHC is proposed for optimization purpose to address such issues.The selected CNTs characteristics are CNTs yield and quality represented by the ratio of the relative intensity of the D and G-bands (ID/IG).Six case studies are generated from collected dataset including four cases of CNTs yield and one case of ID/IG as single objective optimization problems,while the sixth case represents multi-objective problem.The input parameters of each case are a subset from the set of input parameters including reaction temperature,duration,carbon dioxide flow rate,methane partial pressure,catalyst loading,polymer weight and catalyst weight.The models for the first three case studies were mentioned in the original work.RSM is proposed to develop polynomial models for the output responses in the other three cases and to identi significant process parameters and interactions that could affect the CNTs output responses.The developed models are validated using t-test,correlation and pattern matching.The predictive results have a good agreement with the actual experimental data.The models are used as objective functions in optimization techniques.For multi-objective optimization,this study proposes Desirability Function Approach (DFA) to be integrated with other proposed algorithms to form hybrid techniques namely RSM-DFA,ABC-DFA and ABC-βHC-DFA.The proposed algorithms and other selected well-known algorithms are evaluated and compared on their CNTs yield and quality.The optimization results reveal that ABC-βHC and ABC-βHC-DFA obtained significant results in terms of success rate,required time,iterations,and function evaluations number compared to other well-known algorithms.Significantly,the optimization results from this study are better than the results from the original work of the collected dataset.…”
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