Search Results - (( using optimization based algorithm ) OR ( parameter evaluation study algorithm ))

Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study by Li Yu Yab, Li Yu Yab, Wahid, Noorhaniza, A Hamid, Rahayu

“…—Whale Optimization Algorithm (WOA) and Grey Wolf Optimizer (GWO) are well-perform metaheuristic algorithms used by various researchers in solving feature selection problems. …”
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Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study by Li Yu Yab, Li Yu Yab, Wahid, Noorhaniza, A Hamid, Rahayu

“…Whale Optimization Algorithm (WOA) and Grey Wolf Optimizer (GWO) are well-perform metaheuristic algorithms used by various researchers in solving feature selection problems. …”
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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

“…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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Using the evolutionary mating algorithm for optimizing deep learning parameters for battery state of charge estimation of electric vehicle by Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Nor Farizan, Zakaria, Mohd Mawardi, Saari

“…To show the effectiveness of EMA-DL, comparison studies were conducted among other metaheuristic optimizers that were also used to optimize the DL parameters viz, Particles Swarm Optimization (PSO), Genetic Algorithm (GA), Differential Evolution (DE) as well as the Adaptive Moment Estimation (ADAM). …”
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A Preliminary Study on Camera Auto Calibration Problem Using Bat Algorithm by Mohd Annuar, Khalil Azha, Selamat, Nur Asmiza, Jaafar, Hazriq Izzuan, Mohamad, Syahrul Hisham

“…This paper attempts to implement a stochastic optimization algorithm called Bat Algorithm in order to find optimal values of the intrinsic parameters. …”
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Impact of evolutionary algorithm on optimization of nonconventional machining process parameters by B V, Raghavendra, R Annigiri, Anandkumar, Srikatamurthy, JS

“…Using a Python environment, three evolutionary algorithms such as, Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Firefly Algorithm (FA), were simulated to evaluate their effectiveness in minimizing surface roughness (Ra). …”
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An Improved Hybrid of Particle Swarm Optimization and the Gravitational Search Algorithm to Produce a Kinetic Parameter Estimation of Aspartate Biochemical Pathways by Ahmad Muhaimin, Ismail, Mohd Saberi, Mohamad, Hairudin, Abdul Majid, Khairul Hamimah, Abas, Safaai, Deris, Zaki, Nazar, Siti Zaiton, Mohd Hashim, Zuwairie, Ibrahim, Muhammad Akmal, Remli

“…The results show that the proposed algorithm outperformed other standard optimization algorithms in terms of accuracy and near-optimal kinetic parameter estimation. …”
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Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm by Farzin, Saeed, Singh, Vijay, Karami, Hojat, Farahani, Nazanin, Ehteram, Mohammad, Kisi, Ozgur, Allawi, Mohammed Falah, Mohd, Nuruol Syuhadaa, El-Shafie, Ahmed

“…Seven performance indexes were examined to evaluate the performance of the proposed Muskingum model integrated with IBA, with other models that were also based on the Muskingum Model with three-parameters but utilized different optimization algorithms. …”
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An alternative approach to normal parameter reduction algorithms for decision making using a soft set theory / Sani Danjuma by Sani , Danjuma

“…However, they require much time to repeatedly run the algorithms to reduce unnecessary parameters using either parameter important degree or oriented parameter sum. …”
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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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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

“…However, existing optimization tools, especially those using multi-agent optimization, often entail a high computational burden due to a large number of function evaluations (NFE). …”
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Comparison of Logistic Regression, Random Forest, SVM, KNN Algorithm for Water Quality Classification Based on Contaminant Parameters by Teguh, Sutanto, Muhammad Rafli, Aditya, Haldi, Budiman, M.Rezqy, Noor Ridha, Usman, Syapotro, Noor, Azijah

“…The methodology used includes data collection, preprocessing, and algorithm implementation with evaluation using crossvalidation techniques. …”
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Application and evaluation of the evolutionary algorithms combined with conventional neural network to determine the building energy consumption of the residential sector by Wang G., Mukhtar A., Moayedi H., Khalilpoor N., Tt Q.

“…The primary objectives were to assess the performance of three evolutionary algorithms ? Heap-Based Optimizer (HBO), Multiverse Optimizer (MVO), and Whale Optimization Algorithm (WOA) ? …”

Estimation of photovoltaic models using an enhanced Henry gas solubility optimization algorithm with first-order adaptive damping Berndt-Hall-Hall-Hausman method by Ramachandran, Murugan, Sundaram, Arunachalam, Ridha, Hussein Mohammed, Mirjalili, Seyedali

“…A reliable methodology is essential for accurately estimating the parameters of PV models, enabling reliable performance evaluations, effective control studies, accurate analysis of partial shading effects, and optimal optimization of Photovoltaic (PV) systems. …”
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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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Fractional chaotic ensemble particle swarm optimizer for identifying the single, double, and three diode photovoltaic models� parameters by Yousri D., Thanikanti S.B., Allam D., Ramachandaramurthy V.K., Eteiba M.B.

Enhanced genetic algorithm optimization model for a single reservoir operation based on hydropower generation: case study of Mosul reservoir, northern Iraq by Al‑Aqeeli, Yousif H., Lee, Teang Shui, Abd Aziz, Samsuzana

“…The performances of these two algorithms were evaluated through the comparison of their optimal values of annual hydropower generation during the 20 scenarios of operating. …”
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Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems by Din, Fakhrud, Khalid, Shah, Fayaz, Muhammad, Gwak, Jeonghwan, Kamal Z., Zamli, Mashwani, Wali Khan

“…To overcome these drawbacks and to achieve an appropriate percentage of exploitation and exploration, this study presents a new modified teaching learning-based optimization algorithm called the fuzzy adaptive teaching learning-based optimization algorithm. …”
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An Intelligent Voltage Controller for a PV Inverter System Using Simulated Annealing Algorithm-Based PI Tuning Approach by Najeeb, Mushtaq, Muhamad, Mansor, Ramdan, Razali, Hamdan, Daniyal, Ali, Mahmood

“…This study associates an intelligent voltage controller based PI approach for PV electrical inverter by employing a meta-heuristic optimization algorithmic called a Simulated Annealing (SA) algorithm. …”
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