A new variable structure DC motor controller using geneticalgorithms by Al-Hamouz, Z.M.

“…This paper presents a new application of the genetic algorithm for the selection of the variable structure controller (VSC) feedback gains and switching vector for a separately excited DC motor. …”
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A simulated evolution approach to task-matching and scheduling in heterogeneous computing environments by Barada, Hassan

“…The performance of SE is compared with a genetic algorithm approach for the same problem with respect to the quality of solutions generated, and timing requirements of the algorithms. r 2003 Elsevier Science Ltd. …”
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Test bus assignment, sizing, and partitioning for system-on-chip by Harmanani, Haidar M.

“…In this paper, an efficient genetic algorithm for designing test access architectures while investigating test bus sizing and concurrently assigning cores to test buses is proposed. …”
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A Novel Centrality-Based Approach for Link Prediction by El Khoury, Elissa Lichaa

“…Namely, we consider weighted betweenness, closeness and Katz centralities, in addition to the Resource Allocation and Adamic-Adar indices. We also use a genetic algorithm to optimize the weights of these metrics, reflecting their contributions to link prediction. …”
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DSCE: Comparative Analysis of Heuristic Computational Techniques by Bany Muhammad, Nooh

“…Various HCTs are also compared, including genetic algorithms (GAs), particle swarm optimization (PSO), differential evolution (DE), cat swarm optimization (CSO), bee colony optimization (BCO), hybrid GA-PSO (HGP), and the cuckoo search algorithm (CSA). …”
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Analysis of power system stability enhancement via excitation and FACTS-based stabilizers by Abido, M. A.

“…Then, a real-coded genetic algorithm is employed to search for optimal controller parameters. …”
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AI-Augmented Metasurface Synthesis for Dynamic Beam Steering in Reconfigurable Antenna Arrays by Bostani, Ali

“…As compared to the conventional heuristic methods, for example, genetic algorithms (GA), particle swarm optimization (PSO), the approach based on DRLs has rapid policy convergence, has relatively less computational latency, and is autonomous to adapt to dynamic wireless conditions. …”
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Investigating the Impact of Skylights and Atrium Configurations on Visual Comfort and Daylight Performance in Dubai Shopping Malls by SANAD, AYMAN ADEL AHMED

“…Annual simulations are used to assess seasonal variations, while sensitivity analysis identifies key parameters. A genetic algorithm and multi-objective optimisation (MOO) simulations are used to generate optimal configurations, summarised in the form of a Pareto front selection criteria guide the choice of the optimum solution, which is then applied and analysed in a case study. …”
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A new bi-objective model of the urban public transportation hub network design under uncertainty by Firoozeh Kaveh (14150877)

“…Since exact values of some parameters are not known in advance, a fuzzy multi-objective programming based approach is proposed to optimally solve small-sized problems. For medium and large-sized problems, a meta-heuristic algorithm, namely multi-objective particle swarm optimization is applied and its performance is compared with results from the non-dominated sorting genetic algorithm. …”

Design of a vibration absorber for harmonically forced damped systems by Issa, Jimmy

“…Two different numerical approaches are used in solving the problem; the first is based on the genetic algorithm technique and the second on the downhill simplex method. …”
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Power system stability enhancement via coordinated design of a PSS and an SVC-based controller by Abido, M.A.

“…The real-coded genetic algorithm (RCGA) is employed to search for optimal controller parameters. …”
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Coordinated design of robust excitation and TCSC-based damping controllers by Abido, M.A.

“…The real-coded genetic algorithm (RCGA) is employed to search for optimal controller parameters. …”
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Analysis and Assessment of STATCOM-Based Damping Stabilizers for Power System Stability Enhancement by Abido, M. A.

“…Then, a real-coded genetic algorithm (RCGA) is employed to search for optimal stabilizer parameters. …”
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Improving passenger satisfaction at Kuwait International Airport by using multi-objective optimisation by Alsaber, Ahmad

“…The proposed methods employ optimisation techniques such as mixed integer goal programming (MIGP) and genetic algorithm (GA) to offer a comparative multi-solution outcome towards optimising the passenger quality of services at airport departure check-in. …”
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Dynamic single node failure recovery in distributed storage systems by Itani, M.

“…To minimize the system repair cost, we formulate our problem using incidence matrices and solve it heuristically using genetic algorithms for all possible cases of single node failures. …”
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A Dual Vibration Absorber for Vibration Suppression of Harmonically Forced Systems by El Khoury, Elie

“…Then, a numerical technique based on both the genetic algorithm and the search simplex method is used to calculate the optimal system parameters. …”
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Hybridizing rule-based power system stabilizers with geneticalgorithms by Abido, M.A.

“…The proposed approach uses genetic algorithms (GA) to search for optimal settings of rule-based power system stabilizer (RBPSS) parameters. …”
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Inferential sensing techniques in industrial applications by Shakil,, Muhammad

“…System delays are obtained by approximating the model by a linear model. Genetic algorithm, which is a heuristic optimization technique, is used to ¯nd the system delays of the linear model, which are used in dynamical neural network model. …”
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Vibration suppression in a cantilever beam using a string-type vibration absorber by Issa, Jimmy S.

“…In the first, the spring stiffness, the position of the second attachment point of the string and a preliminary damping constant are calculated using a genetic algorithm approach where the objective function is the maximum displacement on the beam. …”
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Multi-Modal Emotion Aware System Based on Fusion of Speech and Brain Information by M. Ghoniem, Rania

“…For classifying unimodal data of either speech or EEG, a hybrid fuzzy c-means-genetic algorithm-neural network model is proposed, where its fitness function finds the optimal fuzzy cluster number reducing the classification error. …”
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