Search Results - (( parameters deviations methods algorithm ) OR ( time optimization method algorithm ))*

Improving the Muskingum flood routing method using a hybrid of particle swarm optimization and bat algorithm by Ehteram M., Othman F.B., Yaseen Z.M., Afan H.A., Allawi M.F., Malek M.B.A., Ahmed A.N., Shahid S., Singh V.P., El-Shafie A.

“…Decision making; Disaster prevention; Floods; Routing algorithms; Water resources; Absolute deviations; Bat algorithms; Comparative analysis; Computational time; Flood routing; Muskingum models; Particle swarm optimization algorithm; Swarm algorithms; Particle swarm optimization (PSO); accuracy assessment; algorithm; comparative study; decision making; flood; flood forecasting; flood routing; numerical method; optimization; parameter estimation; water resource; United Kingdom; United States…”

A hybrid metaheuristic algorithm for identification of continuous-time Hammerstein systems by Jui, Julakha Jahan, Mohd Ashraf, Ahmad

“…The proposed hybrid method also achieved better performance in modeling of the twin-rotor system as well as the flexible manipulator system and provided better solutions compared to other optimization methods including Particle Swarm Optimizer, Grey Wolf Optimizer, Multi-Verse Optimizer and Sine Cosine Algorithm.…”
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Improving the Muskingum flood routing method using a hybrid of particle swarm optimization and bat algorithm by Ehteram, Mohammad, Othman, Faridah, Yaseen, Zaher Mundher, Afan, Haitham Abdulmohsin, Allawi, Mohammed Falah, Malek, Marlinda Abdul, Ahmed, Ali Najah, Shahid, Shamsuddin, Singh, Vijay P., El-Shafie, Ahmed

“…In this study, a hybrid of the bat algorithm (BA) and the particle swarm optimization (PSO) algorithm, i.e., the hybrid bat-swarm algorithm (HBSA), was developed for the optimal determination of these four parameters. …”
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An Optimized PID Parameters for LFC in Interconnected Power Systems Using MLSL Optimization Algorithm by Najeeb, Mushtaq, Shahooth, Mohammed, Mohaisen, Arrak, Ramdan, Razali, Hamdan, Daniyal

“…In order to enhance the dynamic performance, the optimal parameters of the PID scheme which optimized by the proposed MLSL algorithm are compared with that one’s obtained by GA algorithm. …”
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PID Parameters Improvement for AGC in Three Parallel-Connected Power Systems by Mushtaq, Najeeb, Ramdan, Razali, K. G., Mohammed, Hamdan, Daniyal, Ali, M. Humada

“…The optimal parameters of the PID scheme optimized by the proposed MS algorithm are compared with that one’s obtained by GA algorithm, and the proposed method has proven that its performance is more efficient and improved as well. …”
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Real-Time Optimal Trajectory Correction (ROTC) for autonomous quadrotor / Noorfadzli Abdul Razak by Abdul Razak, Noorfadzli

“…However, existing algorithm seems too complicated to be applied. Since there is no technique can enable the quadrotor to implement precision navigation application, the research proposed a Real-Time Optimal Trajectory Correction (ROTC) algorithm. …”
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Metaheuristic Algorithm for Wellbore Trajectory Optimization by Biswas, K., Vasant, P.M., Vintaned, J.A.G., Watada, J.

“…Later this parameter can be effectively fixed to tune different algorithm. …”
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Identification of continuous-time model of hammerstein system using modified multi-verse optimizer by Most. Julakha, Jahan Jui

“…his thesis implements a novel nature-inspired metaheuristic optimization algorithm, namely the modified Multi-Verse Optimizer (mMVO) algorithm, to identify the continuous-time model of Hammerstein system. …”
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Investigation of firefly algorithm and chaos firefly algorithm for load prequency control / Zaid Najid by Zaid, Najid

“…In order to obtain the best controller parameter values for LFC, Firefly Algorithm (FA) and Chaos Firefly Algorithm (CFA) are used. …”
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Comparison of mabsa, PSO and GWO of PI-PD controller for dc motor by Nur Naajihah, Ab Rahman

“…The swarm intelligence group selected Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), and Modified Adaptive Bats Sonar Algorithms (MABSA) to optimize the parameters of the PI-PD controller. …”
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Design and Implementation of PID Controller for the Cooling Tower?s pH Regulation Based on Particle Swarm Optimization PSO Algorithm by Al-Najari B.M.A., Hen C.K., Paw J.K.S., Marhoon A.F.

“…The methodology is to calculate the transfer function of the PH loop using the system identification toolbox of MATLAB, to design and implement a PID controller, to optimize the PID controller response using particle swarm optimization PSO algorithm, and to make a comparison among several tuning methods such as Ziegler Nichols (ZN) tuning method, MATLAB tuner method, and PSO algorithm tuning method. …”

A Hybrid of Particle Swarm Optimization and Harmony Search to Estimate Kinetic Parameters in Arabidopsis thaliana by Mohamad Saufie, Rosle, Mohd Saberi, Mohamad, Yee, Wen Choon, Zuwairie, Ibrahim, González-Briones, Alfonso, Chamoso, Pablo, Corchado, Juan Manuel

“…The proposed algorithm outperformed the other two methods, namely Simulated Annealing and the downhill simplex method, and proved that PSOHS is a more suitable algorithm for estimating kinetic parameter values.…”
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Novel farmland fertility algorithm based PIDPSS design for SMIB angular stability enhancement by Sabo, Aliyu, Abdul Wahab, Noor Izzri, Othman, Mohammad Lutfi, Mohd Jaffar, Mai Zurwatul Ahlam

“…A new metaheuristics method called Farmland Fertility Algorithm (FFA) inspired by nature is proposed for optimal design of PIDPSS using a robust ISTSE objective function which had to be minimized. …”
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Optimal Location And Sizing Of Distrubuted Generator Using PSO And GA Algorithms In Power Systems by Hassan, Ayat Saleh

“…Some existing algorithms need to be improved while others, need to add a new parameter for improving the performance of optimization methods and making it more effective and efficient. …”
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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

“…To summarise, metaheuristic algorithms can give a superior optimization approach than the traditional artificial neural network method, providing the computing time is within an acceptable range. …”
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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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Modeling and control of a Pico-satellite attitude using Fuzzy Logic Controller by Zaridah, Mat Zain

“…The performances obtained show that the optimized APFLC is better than the non-optimize APFLC in terms of RMSE and the settling time.…”
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Estimation of transformers health index based on condition parameter factor and hidden Markov model by Mohd Selva, Amran, Yahaya, Muhammad Sharil, Azis, Norhafiz, Ab Kadir, Mohd Zainal Abidin, Jasni, Jasronita, Yang Ghazali, Young Zaidey

“…Next, the emission probabilities for each of the condition parameter factors were derived based on frequency of occurrence method. …”
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Automatic load frequency control of a multi-area dynamic interconnected power system using a hybrid PSO-GSA-tuned PID controller by Veerasamy, Veerapandiyan, Abdul Wahab, Noor Izzri, Ramachandran, Rajeswari, Vinayagam, Arangarajan, Othman, Mohammad Lutfi, Hizam, Hashim, Satheeshkumar, Jeevitha

“…This paper proposes a new population-based hybrid particle swarm optimized-gravitational search algorithm (PSO-GSA) for tuning the parameters of the proportional-integral-derivative (PID) controller of a two-area interconnected dynamic power system with the presence of nonlinearities such as generator rate constraints (GRC) and governor dead-band (GDB). …”
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Optimization of Microbial Electrolysis Cell for Sago Mill Wastewater Derived Biohydrogen via Modeling and Artificial Neural Network by Mohamad Afiq, Mohd Asrul

“…The model reliability describes the second sub-objective, which is to determine the feasible operating window of the MEC using multiple-objective optimization based on the nonlinear convex method using gradient descent algorithm as the objective function in maximizing the percentage efficiency of the MEC after validating the mathematical model. …”
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