Search Results - (( dynamic simulation techniques algorithm ) OR ( based optimization method algorithm ))
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Process Planning Optimization In Reconfigurable Manufacturing Systems
Published 2008“…The five (5) AADTs include; a variant of the simulated annealing algorithm that implements heuristic knowledge at critical decision points, two (2) cooperative search schemes based on a “loose hybridization” of the Boltzmann Machine algorithm with (i) simulated annealing, and (ii) genetic algorithm search techniques, and two (2) modified genetic algorithms. …”
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Optimal design of power system stabilizer for multimachine power system using farmland fertility algorithm
Published 2020“…In this research, the effective application and performance assessment of genetic algorithm (GA), particle swarm optimization (PSO) and a new metaheuristic-based farmland fertility algorithm (FFA) search algorithm for designing of coordinated multi PSSs in an interconnected multimachine power systems are presented and the limitations of the existing techniques (GA and PSO) are disclosed. …”
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A conceptual framework for multi-objective optimization of building performance: Integrating intelligent algorithms, simulation tools, and climate adaptation
Published 2025“…A thematic analysis of 40 peer-reviewed articles was conducted using ATLAS.ti, revealing three dominant research themes: intelligent algorithms, building performance simulation techniques, and adaptive design for climate change. …”
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Modeling of static and dynamic components of bio-nanorobotic systems
Published 2012“…In addition, a graph algorithm based on greedy methods is employed to compute a new set of optimal weighted electronic properties of the fullerenes via computing their Minimum Weight Spanning Trees (MWSTs). …”
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System performances analysis of reservoir optimization–simulation model in application of artificial bee colony algorithm
Published 2018“…Particle swarm optimization, genetic algorithm and neural network-based stochastic dynamic programming are also used in a view of comparing model performances. …”
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Investigating the Performance of Deep Reinforcement Learning-Based MPPT Algorithm under Partial Shading Condition
Published 2024“…In this study, MATLAB models of a DRL-based MPPT algorithm were developed, tested, and compared to simulation based on two established MPPT algorithms-the Particle Swarm Optimization (PSO), and the Perturb and Observe (P&O). …”
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Data-driven PID controller of wind turbine systems using safe experimentation dynamics algorithm
Published 2024“…These results underscore the efficacy of the SEDA method in providing optimal PID control parameters while reducing computational burdens by 52% compared to other multi-agent optimization-based methods.…”
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Conference or Workshop Item -
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Development of optimized damage prediction method for health monitoring of ultra high performance fiber-reinforced concrete communication tower
Published 2018“…The modal frequencies of the tower are evaluated under various conditions of damage in concrete and connection in different parts of the tower by using finite element simulation. The results are used to develop the hybrid learning algorithm based on the AdaBoost, Bagging, and RUSBoost methods to predict the damage in the tower based on dynamic frequency domain. …”
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A novel single parent mating technique in genetic algorithm for discrete - time system identification
Published 2024“…A typical rule is that the model must have a good balance between parsimony and accuracy in estimating a dynamic system. As a popular search method, genetic algorithm (GA) is used for selecting a model structure. …”
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Application of intelligent optimization techniques and investigating the effect of reservoir size in calibrating the reservoir operating policy
Published 2023“…Particle swarm optimization, genetic algorithm and neural network-based stochastic dynamic programming are used to compare the model performances. …”
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Optimal placement of unified power flow controller by dynamic implementation of system-variable-based voltage-stability indices to enhance voltage stability
Published 2016“…Furthermore, to verify the suitability of the explored locations, a comparative study has been conducted after placing UPFC in the present locations and other locations obtained using optimization techniques like particle swarm optimization (PSO), differential evolution (DE), genetic algorithm (GA), and bacteria foraging algorithm (BFA). …”
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Application of Multi-objective Genetic Algorithm (MOGA) optimization in machining processes
Published 2020“…Multi-objectives Genetic Algorithm (MOGA) is one of many engineering optimization techniques, a guided random search method. …”
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Book Chapter -
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HSO: A hybrid swarm optimization algorithm for reducing energy consumption in the cloudlets
Published 2018“…With the proposed model, the performance of the Hybrid swarm algorithm was significantly increased, as observed by optimizing the number of tasks through simulation, (power consumption was reduced by 42%). …”
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Efficiency improvement of a standalone photovoltaic system using fuzzy-based maximum power point tracking algorithm
Published 2016“…MPPT algorithms can be categorized into classical methods and artificial intelligence-based methods. …”
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A study of acceleration techniques in training neural networks - local adaptive techniques / Norpah Mahat
Published 2011“…Till today, it has been a great challenge in optimizing the training time in neural networks. This paper presents Local Adaptive Techniques and Dynamic Adaptation Methods as acceleration techniques for neural networks. …”
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Unsupervised Deep Learning Algorithm to Solve Sub-Surface Dynamics for Petroleum Engineering Applications
Published 2020“…In the present study, the solution for the initial condition and boundary value problems in ordinary and partial differential equation by deep learning method have been analyzed. The propsed algorithm could be valuable aid for analyzing the fluid flow and reservoir simulation in an effective manner. …”
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Space allocation for examination scheduling using Genetic Algorithm / Alya Kauthar Azman
Published 2025“…To further enhance the scheduling system, future work should focus on integrating additional optimization techniques such as Particle Swarm Optimization or Simulated Annealing to refine scheduling accuracy. …”
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