Search Results - (( parameter simulation tool algorithm ) OR ( parameter optimization based algorithm ))

A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models by ul Islam, B., Baharudin, Z.

“…These models are developed by integrating multilayer perceptron neural network and evolutionary optimization techniques. Genetic algorithm and simulated annealing techniques are used to optimize the control parameters of the neural network. …”
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OPTIMAL DESIGN AND ANALYSIS OF A DC–DC SYNCHRONOUS CONVERTER USING GENETIC ALGORITHM AND SIMULATED ANNEALING by K., S. Rama Rao., C. , -K, Chew

“…A constrained optimization on the objective function is performed using GA and SA, and optimal parameters are derived. …”
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OPTIMAL DESIGN AND ANALYSIS OF A DC–DC SYNCHRONOUS CONVERTER USING GENETIC ALGORITHM AND SIMULATED ANNEALING by K.S., Rama Rao, C. K., Chew

“…A constrained optimization on the objective function is performed using GA and SA, and optimal parameters are derived. …”
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Impact of evolutionary algorithm on optimization of nonconventional machining process parameters by B V, Raghavendra, R Annigiri, Anandkumar, Srikatamurthy, JS

“…This paper presents the optimization of laser beam machining in additive manufacturing of polymer-based material parameters, specifically focusing on cutting speed, gas pressure of nitrogen, and focal point locations, to achieve optimal mean surface roughness. …”
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Optimization-based simulation algorithm for predictive-reactive job-shop scheduling of reconfigurable manufacturing systems by Tan, Joe Yee

“…This study is aimed to formulate an optimization-based algorithm with simulation tool to reduce the throughput time of complex RMS, which can comply with complex product allocations and flexible routings of the system. …”
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Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm by Manoharan P., Ravichandran S., Kavitha S., Tengku Hashim T.J., Alsoud A.R., Sin T.C.

“…This approach demonstrates the ability of the GOOSE algorithm to simulate complex systems and enhances the robustness and adaptability of the simulation tool by integrating essential behaviours into the computational framework. …”

Fast and optimal tuning of fractional order PID controller for AVR system based on memorizable-smoothed functional algorithm by Ren Hao, Mok, Ahmad, Mohd Ashraf

“…Nevertheless, many existing optimization tools for tuning the FOPID controller, which are based on multi-agent based optimization, require large number of function evaluation in their algorithm that could lead to high computational burden. …”
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Design optimization of valve timing at various engine speeds using Multi-Objective Genetic Algorithm (MOGA) by Mohiuddin, A. K. M., Ashour, Ahmed Aly Ibrahim Shaaban, Yap, Haw Shin

“…This paper aims to demonstrate the effectiveness of Multi- Objective Genetic Algorithm Optimization and its robust practical application on the automobile engine valve timing where the variation of performance parameters required for finest tuning to obtain the optimal engine performances. …”
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Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems by Nor Sakinah, Abdul Shukor

“…Hence, a memory-based optimization tool has good potential to retain the optimal design parameter during the PID tuning process. …”
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Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems by Nor Sakinah, Abdul Shukor

“…Hence, a memory-based optimization tool has good potential to retain the optimal design parameter during the PID tuning process. …”
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Hybridization of nonlinear sine cosine and safe experimentation dynamics algorithms for solving control engineering optimization problems by Mohd Helmi, Suid

“…The empirical assessment of these proposed methods encompasses a diverse set of 23 benchmark functions, demonstrating their efficacy comparable to well-established metaheuristic algorithms such as as the Grey Wolf Optimizer (GWO), Multi-Verse Optimization (MVO), Sine Cosine Algorithm (SCA), Ant Lion Optimizer (ALO), Moth-Flame Optimization Algorithm (MFO), and Grasshopper Optimization Algorithm (GOA). …”
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Data-driven PID controller of wind turbine systems using safe experimentation dynamics algorithm by Islam, Muhammad Shafiqul, Mohd Ashraf, Ahmad, Mohd Riduwan, Ghazali, Mohd Helmi, Suid, Mohd Zaidi, Mohd Tumari

“…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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Data driven neuroendocrine pid controller for mimo plants based adaptive safe experimentation dynamics algorithm by Mohd Riduwan, Ghazali

“…Data-driven tools are an optimization method to find the optimal controller parameters using the system’s input and output data. …”
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A comparative study for parameter selection in online auctions by Gan, Kim Soon

“…Due to the complex and dynamic nature of the online auction, one of the strategies employed is using genetic algorithm to discover the best strategy. Hence, this work attempts to improve an existing bidding strategy by taking into accounts the evolution of various model of generic algorithm in optimizing the parameter of the bidding strategies. …”
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Bio-lubricant production based on optimum epoxidized oleic acid using in situ peracid mechanism / Tunku Arif Zafri Tunku Ozir by Tunku Ozir, Tunku Arif Zafri

“…Lastly, the kinetic reaction rates were determined using genetic algorithm MATLAB optimization tool and the experimental data was compared together with the simulation data.…”
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A memory-guided Jaya algorithm to solve multi-objective optimal power flow integrating renewable energy sources by Ahmadipour M., Ali Z., Ramachandaramurthy V.K., Ridha H.M.

“…To ensure fair comparisons, parameter configurations for all algorithms are automated using the parameter tuning tool iterated racing (irace). …”

Machine Learning Based Optimal Design of On-Road Charging Lane for Smart Cities Applications by Shanmugam Y., Narayanamoorthi R., Ramachandaramurthy V.K., Bernat P., Shrestha N., Son J., Williamson S.S.

“…The ML approach, which predicts optimal design parameters with a trained dataset, is more efficient with reduced duration than conventional finite element analysis (FEA) tools and stochastic methods. …”

Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm by Shahrizal, Saat, Mohd Ashraf, Ahmad, Mohd Riduwan, Ghazali

“…The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm by Shahrizal, Saat, Mohd Ashraf, Ahmad, Mohd Riduwan, Ghazali

“…The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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Enhancing quality of service in Multi-Radio Multi-Channel Wireless Mesh Networks by Raja Bongsu, Raja Hasyifah

“…This research utilizes the OmNET++ 4.6 simulator, an open-source tool in C++, to evaluate proposed algorithms effectively. …”
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