Search Results - (( parallel optimization method algorithm ) OR ( parameter optimization new algorithm ))

Development of optimization Alghorithm for uncertain non-linear dynamical system by Abdul Aziz, Mohd. Ismail, Yaacob, Nazeeruddin, Mohd. Said, Norfarizan, Hamzah, Nor Hazadura

“…An algorithm that definitely can satisfy the objectives is the Dynamic Integrated Systems Optimization and Parameter Estimation (DISOPE) algorithm. …”
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Intelligent classification algorithms in enhancing the performance of support vector machine by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…This paper presents two intelligent algorithms that hybridized between ant colony optimization (ACO) and SVM for tuning SVM parameters and selecting feature subset without having to discretize the continuous values. …”
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Design of low order quantitative feedback theory and H-infinity-based controllers using particle swarm optimisation for a pneumatic actuator system by Ali, Hazem I.

“…The particle swarm optimization (PSO) method is used to tune the parameters of the controller and weighting functions subject to QFT and/or constraints. …”
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Hybrid intelligent methods for parameter identification and load frequency control in power system by Aqeel Sakhy, Jaber

“…A new method from the improvement of Particle Swarm Optimization (PSO) is developed in order to find the best global optimal value. …”
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Development of a multi-objective optimization model for transport and environment in a closed-loop automotive supply chain by Sadrnia, Abdolhossein

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Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks by Ukasyah bin Mahamod

A new method for decreasing cell-load variation in dynamic cellular manufacturing systems by Delgoshaei, Aidin, Mohd Ariffin, Mohd Khairol, Baharudin, Btht Hang Tuah, Leman, Zulkiflle

“…The Taguchi method (an L_9 orthogonal optimization) is used to estimate parameters of GA in order to solve experiments derived from literature. …”
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A multi-period scheduling of dynamic cellular manufacturing systems in the presence of cost uncertainty by Delgoshaei, Aidin, Ali, Ahad, Ariffin, Mohd Khairol Anuar, Gomes, Chandima

“…In continue a Taguchi method (an orthogonal optimization) is used to estimate parameters of the proposed method in order to solve experiments derived from literature. …”
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Scheduling dynamic cellular manufacturing systems in the presence of cost uncertainty using heuristic method by Delgoshaei, Aidin

“…Then, design of experiments is used to examine the sensitivity of the parameters of each solving algorithm using Taguchi method. …”
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Voting algorithms for large scale fault-tolerant systems by Karimi, Abbas

“…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures by Koohi, Sina Zangbari

“…Any optimization algorithm is suitable for only a specific domain of optimization problems. …”
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Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms by Loo, C.K., Liew, W.S., Seera, M., Lim, Einly

“…This was achieved by mitigating convergence in the genetic algorithms by employing a hierarchical parallel architecture. …”
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Investigation on the dynamic of computation of semi autonomous evolutionary computation for syntactic optimization of a set of programming codes by Mohammad Sigit Arifianto, Tze, Kenneth Kin Teo, Liau, Chung Fan, Liawas Barukang, Zaturrawiah Ali Omar

“…Genetic Algorithm as one of the Evolutionary Computation method improve the execution of parallel programming codes by optimizing the number of processors and the distribution of data. …”
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Improved black-winged kite algorithm and finite element analysis for robot parallel gripper design by Haohao, Ma, As’arry, Azizan, Yanwei, Feng, Lulu, Cheng, Delgoshaei, Aidin, Ismail, Mohd Idris Shah, Ramli, Hafiz Rashidi

“…This paper presents a comprehensive study on the design optimization of a robotic gripper, focusing on both the gripper modeling and the optimization of its parallel mechanism structure. …”
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Sequential and parallel multiple tabu search algorithm for multiobjective urban transit scheduling problems by Uvaraja, Vikneswary

“…Additionally, the MTS algorithm is also implemented in parallel computing to produce parallel MTS for generating comparable solutions in shorter computational times. …”
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Analysis of evolutionary computing performance via mapreduce parallel processing architecture / Ahmad Firdaus Ahmad Fadzil by Ahmad, Ahmad Firdaus

“…Examples of EC such as Genetic Algorithm (GA) and PSO (Particle Swarm Optimization) are prevalent due to their efficiency and effectiveness. …”
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Distributed parallel deep learning with a hybrid backpropagation-particle swarm optimization for community detection in large complex networks by Shing, Chiang Ta, Mohammed Al-Andoli, Mohammed Nasser, Wooi, Ping Cheah

“…Next, the method is integrated with two optimization algorithms: (1) backpropagation (BP), which optimizes deep learning locally within each local chunk of the CN; (2) particle swarm optimization (PSO), which is used to improve the BP optimization involving all CN chunks. …”
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Finite impulse response optimizers for solving optimization problems by Tasiransurini, Ab Rahman

“…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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Fitness-guided particle swarm optimization with adaptive Newton-Raphson for photovoltaic model parameter estimation by Premkumar M., Ravichandran S., Hashim T.J.T., Sin T.C., Abbassi R.

“…This study introduces a new approach for parameter optimization in the four-diode photovoltaic (PV) model, employing a Dynamic Fitness-Guided Particle Swarm Optimization (DFGPSO) algorithm and Enhanced Newton-Raphson (ENR) method. …”

Finite impulse response optimizers for solving optimization problems by Ab Rahman, Tasiransurini

“…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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