Search Results - (( developing function model algorithm ) OR ( based optimization method algorithm ))

Long term energy demand forecasting based on hybrid, optimization: Comparative study by Musa, Wahab, Ku-Mahamud, Ku Ruhana, Yasin, Azman

“…The objective of this research is to develop a long term energy demand forecasting model that used hybrid optimization.To accomplish this goal, a hybrid algorithm that combined a genetic algorithm and a local search algorithm method has been developed to overcome premature convergence.Model performances of hybrid algorithm were compared with former single algorithm model in estimating parameter values of an objective function to measure the goodness-of-fit between the observed data and simulated results.Averages error between two models was adopt to select the proper model for future projection of energy demand.…”
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Data-driven continuous-time Hammerstein modeling with missing data using improved Archimedes optimization algorithm by Islam, Muhammad Shafiqul, Mohd Ashraf, Ahmad

“…Across all experiments, the IAOA-based method demonstrated superior performance compared to AOA and other methods, including a hybrid approach combining the average multi-verse optimizer and sine cosine algorithm, particle swarm optimizer, the sine cosine algorithm, multi-verse optimizer and grey wolf optimizer. …”
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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

“…To address the existing theoretical gap, this study focused on developing an objective function that accurately estimates the initial root parameters of Photovoltaic (PV) models. …”
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Simulated Kalman Filter algorithms for solving optimization problems by Nor Hidayati, Abdul Aziz

“…Its optimality has inspired the development of a metaheuristic algorithm called Heuristic Kalman Algorithm (HKA) in 2009. …”
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Neural network modeling and optimization for spray-drying coconut milk using genetic algorithm and particle swarm optimization by Lee, Jesee Kar Ming

“…Firstly, using MATLAB program, the ANN model is developed based on optimized topology and is then furthered optimized by genetic algorithm (GA) and particle swarm optimization (PSO) using MINITAB program. …”
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New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems by Nor Shuhada, Ibrahim

“…Firstly, it delves into the development of reservoir operation optimization problems (ROOPs), which focusing on Malaysia-based model. …”
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Modified multi-verse optimizer for nonlinear system identification of a double pendulum overhead crane by Julakha, Jahan Jui, Mohd Ashraf, Ahmad, Muhammad Ikram, Mohd Rashid

“…In the HMVOSCA algorithm, the new position updating mechanism of the traditional MVO method is modified based on the sine function and cosine function which is taken from the Sine Cosine Algorithm (SCA). …”
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Neural network algorithm-based fall detection modelling by Mohd Yusoff, Ainul Husna, Koh, Cheng Zhi, Ngadimon, Khairulnizam, Md Salleh, Salihatun

“…The algorithm is trained by network training function; LM, SCG and RP by collocation with threshold-based setting value. …”
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Improvement and application of particle swarm optimization algorithm by Deevi, Durga Praveen, Kodadi, Sharadha, Allur, Naga Sushma, Dondapati, Koteswararao, Chetlapalli, Himabindu, Perumal, Thinagaran

“…Finally, real-world tests are performed to verify the proposed Algorithm's efficacy compared to existing optimization methods. …”
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A holistic review on artificial intelligence techniques for well placement optimization problem by Islam, J., Vasant, P.M., Negash, B.M., Laruccia, M.B., Myint, M., Watada, J.

“…For future endeavor, combining optimization methods and exploiting multiple optimization processes for faster convergence and developing efficient proxy model is expected. …”
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Process Planning Optimization In Reconfigurable Manufacturing Systems by Musharavati, Farayi

“…Therefore, this study explores how to model reconfigurable manufacturing activities in an optimization perspective and how to develop and select appropriate non-conventional optimization techniques for reconfigurable process planning.In this study, a new approach to modeling Manufacturing Process Planning Optimization (MPPO) was developed by extending the concept of manufacturing optimization through a decoupled optimization method. …”
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Backtracking Search Algorithm Based Fuzzy Charging-Discharging Controller for Battery Storage System in Microgrid Applications by Faisal M., Hannan M.A., Ker P.J., Uddin M.N.

The compact genetic algorithm for likelihood estimator of first order moving average model by Al-Dabbagh, R.D., Baba, M.S., Mekhilef, Saad, Kinsheel, A.

“…In this paper compact Genetic Algorithm is used to optimize the maximum likelihood estimator of the first order moving avergae model MA(1). …”
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Optimization of RFID network planning for monitoring railway mechanical defects based on gradient-based Cuckoo search algorithm by Talib, Nihad Hasan

“…In conclusion, this study presented a novel hybrid evolutionary algorithm based on the combination of AHP with GBCS to specify optimal RFID reader positions and amount based on the working train station domain. …”
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Data-Driven control based on marine predators algorithm for optimal tuning of the wind plant by Mohd Zaidi, Mohd Tumari, Mohd Ashraf, Ahmad, Mohd Helmi, Suid, Mohd Riduwan, Ghazali

“…Comparative results alongside other existing metaheuristic-based algorithms further confirmed excellence of the proposed method through its superior performance against the slime mould algorithm (SMA), multi-verse optimizer (MVO), sine-cosine algorithm (SCA), grey wolf optimizer (GWO), and safe experimentation dynamics (SED) algorithm.…”
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Multi-objective pareto ant colony system based algorithm for generator maintenance scheduling by Shimailawi, Shatha Abdulhadi Muthana

“…Friedman test using GRG metric shows significant better performance (p-values<0.05) for PACS algorithm compared to benchmark algorithms. The proposed models and algorithm can be used to solve the multi-objective GMS problem while the new parameters’ values can be used to obtain optimal or near optimal maintenance scheduling of generators. …”
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New Quasi-Newton Equation And Method Via Higher Order Tensor Models by Gholilou, Fahimeh Biglari

“…Moreover, a new limited memory QN method to solve large scale unconstrained optimization is developed based on the modified BFGS updated formula. …”
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A Descent Three-Term Conjugate Gradient Direction For Problems Of Unconstrained Optimization With Application by Sulaiman M. Ibrahim, Nur Idalisa, Norhaslinda Zullpakka, P. Kaelo, Norrlaili Shapiee

“…The development of this new algorithm is based on the findings of recently introduced generalized RMIL CG technique. …”

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

“…Design of hydraulic structures, flood warning systems, evacuation measures, and traffic management require river flood routing. A common hydrologic method of flood routing is the Muskingum method. The present study attempted to develop a three-parameter Muskingum model considering lateral flow for flood routing, coupling with a new optimization algorithm namely, Improved Bat Algorithm (IBA). …”
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Parameter extraction of single, double, and three diodes photovoltaic model based on guaranteed convergence arithmetic optimization algorithm and modified third order Newton Raphson methods by Mohammed Ridha, Hussein, Hizam, Hashim, Mirjalili, Seyedali, Othman, Mohammad Lutfi, Ya'acob, Mohammad Effendy, Ahmadipour, Masoud

“…The proposed guaranteed convergence arithmetic optimization algorithm based on efficient modified third order Newton Raphson (GCAOAEmNR) method highlights important contributions to the literature in terms of methodology (explorer-exploiter phases) and objective function design. …”
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