Search Results - (( using self methods algorithm ) OR ( parameter optimization method algorithm ))
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1
SA-EVPS ALGORITHM FOR DISCRETE SIZE OPTIMIZATION OF THE 582-BAR SPATIAL TRUSS STRUCTURE
Published 2023“…Nowadays, approximate optimization methods are widely used. This study utilized the Self Adaptive Enhanced Vibrating Particle System (SA-EVPS) algorithm as an approximate optimization method, since the EVPS algorithm requires experimental parameters. …”
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2
Improving the Muskingum flood routing method using a hybrid of particle swarm optimization and bat algorithm
Published 2023“…Decision making; Disaster prevention; Floods; Routing algorithms; Water resources; Absolute deviations; Bat algorithms; Comparative analysis; Computational time; Flood routing; Muskingum models; Particle swarm optimization algorithm; Swarm algorithms; Particle swarm optimization (PSO); accuracy assessment; algorithm; comparative study; decision making; flood; flood forecasting; flood routing; numerical method; optimization; parameter estimation; water resource; United Kingdom; United States…”
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3
Improving the Muskingum flood routing method using a hybrid of particle swarm optimization and bat algorithm
Published 2018“…In this study, a hybrid of the bat algorithm (BA) and the particle swarm optimization (PSO) algorithm, i.e., the hybrid bat-swarm algorithm (HBSA), was developed for the optimal determination of these four parameters. …”
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4
Recent Evolutionary Algorithm Variants for Combinatorial Optimization Problem
Published 2023“…Hybridization in evolutionary algorithm mechanisms such as initialization methods, local searches, specific design operators, and self-adaptive parameters enhance the algorithm’s performance. …”
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Lithium-ion Battery State of Charge Estimation Method Using Optimized Deep Recurrent Neural Network Algorithm
Published 2023Conference Paper -
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Data Analysis using Particle Swarm Optimization Algorithm
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Final Year Project / Dissertation / Thesis -
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Kernerlized Correlation Filters Parameters Optimization For Enhanced Visual Tracking
Published 2017“…Until now, there are still no perfect algorithm to track the target flawlessly. In order to improve the performance, the main idea proposed is implementing optimization technique on the selected parameters and obtain a better performance. …”
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Monograph -
8
Two-stage feature selection using ranking self-adaptive differential evolution algorithm for recognition of acceleration activity
Published 2018“…An exhaustive searching process of finding an optimal parameter value is another challenge. Consequently, this paper proposes a ranking self-adaptive differential evolution (rsaDE) feature selection algorithm. …”
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Optimal tuning of sigmoid PID controller using nonlinear sine cosine algorithm for the automatic voltage regulator system --- KIV (status in press)
Published 2021“…This paper designed a sigmoid-based PID (SPID) controller for the AVR system in order to allow for an accelerated settling to rated voltage, as well as increasing the control accuracy. In addition, the parameters of the proposed SPID controller are obtained using an enhanced self-tuning heuristic optimization method called Nonlinear Sine Cosine Algorithm (NSCA), for achieving a better dynamic response, particularly with regards to the steady-state errors and overshoot of the system. …”
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Mobility management schemes based on multiple criteria for optimization of seamless handover in long term evolution networks
Published 2014“…The third scheme works on the self optimization of handover parameters using fuzzy logic control (FLC) and multiple preparation (MP) called FuzAMP. …”
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Thesis -
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Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…Therefore, feature selection using Relief-f with self-adaptive Differential Evolution (rsaDE) algorithm is proposed to select the most significant features. …”
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Thesis -
12
Utilizing self-organization systems for modeling and managing risk based on maintenance and repair in petrochemical industries
Published 2018“…Utilizing genetic algorithms, the structures of all self-organizing systems are optimized. …”
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Single Fitness Function to Optimize Energy using Genetic Algorithms for Wireless Sensor Network
Published 2024journal::journal article -
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Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh
Published 2015“…ARDE algorithm makes use of JADE strategy and the MDE_pBX parameters adaptive schemes as frameworks. …”
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Thesis -
15
Nature-Inspired Drone Swarming for Wildfires Suppression Considering Distributed Fire Spots and Energy Consumption
Published 2024“…Our quantitative tests show that the improved model has the best coverage (95.3%, 84.3% and 65.8%, respectively) compared to two other methods Levy Flight (LF) algorithm and Particle Swarm Optimization (PSO), which use the same initial parameter values. …”
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Self-Adaptive Autoreclosing Scheme usingI Artificial Neural Network and Taguchi's Methodology in Extra High Voltage Transmission Systems
Published 2009“…In addition, Taguchi's methodology is employed in optimizing the parameters of each algorithm used for training, and in deciding the number of hidden neurons of the neural network. …”
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Thesis -
17
Prediction and multi-criteria-based schemes for seamless handover mechanism in mobile WiMAX networks
Published 2013“…In the proposed HATSC scheme, the AHP method is uese for criteria weighting, while the TOPSIS method uses for the selection technique based on a multi-criteria decision-making algorithm is proposed. …”
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Thesis -
18
Deep continual learning for predicting blast-induced overbreak in tunnel construction / He Biao
Published 2024“…Third, the integration of metaheuristic algorithms further ascertains the optimal blasting parameters for overbreak minimization under specific rock sections. …”
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Thesis -
19
Observer-based fault detection approach using fuzzy adaptive poles placement system with real-time implementation
Published 2021“…These methods cannot achieve global optimal performance because of their fixed poles placement and it leads to an observer with constant parameters, which could be reducing the system performance. …”
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Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks
Published 2025thesis::doctoral thesis
