Search Results - (( parameter optimization method algorithm ) OR ( using systematic method algorithm ))*

Robust Portfolio Mean-Variance Optimization for Capital Allocation in Stock Investment Using the Genetic Algorithm: A Systematic Literature Review by Diandra Chika Fransisca, Sukono, Diah Chaerani, Nurfadhlina Abdul Halim

PROPOSED METHODOLOGY FOR OPTIMIZING THE TRAINING PARAMETERS OF A MULTILAYER FEED-FORWARD ARTIFICIAL NEURAL NETWORKS USING A GENETIC ALGORITHM by ABDALLA, OSMAN AHMED

“…To overcome these limitations, there have been attempts to use genetic algorithm (GA) to optimize some of these parameters. …”
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Stability augmentation system of active suspension system in electric vehicle conversion: Towards optimal ride comfort performance by Saiful Anuar, Abu Bakar, Ryosuke, Masuda, Hiromu, Hashimoto, Takeshi, Inaba, Hishamuddin, Jamaluddin, Roslan, Abd Rahman, Pakharuddin, Mohd Samin

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SYSTEMATIC DESIGN ALGORITHM FOR ENERGY EFFICIENT AND COST EFFECTIVE HYDROGEN PRODUCTION FROM PALM WASTE by INAYAT, ABRAR

“…In the current study, a systematic autonomous algorithm incorporating reaction kinetics model, flowsheet calculations, heat integration analysis and economic evaluation, has been developed to calculate optimum parameters giving minimum hydrogen production cost using optimization strategies. …”
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Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm by Reza M.S., Hannan M.A., Mansor M., Ker P.J., Rahman S.A., Jang G., Mahlia T.M.I.

“…The effectiveness of the proposed LSA + LSTM model is assessed using battery aging data from the NASA dataset. In addition, to validate the prediction performance of the proposed LSA + LSTM model, extensive comparisons are performed with other popular optimization-based deep learning methods including artificial bee colony (ABC) based LSTM (ABC + LSTM), gravitational search algorithm (GSA) based LSTM (GSA + LSTM), and particle swarm optimization (PSO) based LSTM (PSO + LSTM) model using different error matrices. …”

A decision support system for improving forecast using genetic algorithm and tabu search by Ismail, Zuhaimy

“…The search for the best parameter value of ?, ? and ? and their combinations using trial and error method is time consuming. …”
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Marine Predator Algorithm and Related Variants: A Systematic Review by Philibus, Emmanuel, Mohd Zain, Azlan, Prasetya, Didik Dwi, Bahari, Mahadi, Yusup, Norfadzlan, Abdul Jalil, Rozita, Abdul Majid, Mazlina, A Samah, Azurah

“…The Marine Predators Algorithm (MPA) is classified under swarm intelligence methods based on its type of inspiration. …”
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Marine Predator Algorithm and Related Variants: A Systematic Review by Emmanuel, Philibus, Azlan, Mohd Zain, Didik Dwi, Prasetya, Mahadi, Bahari, Norfadzlan, Yusup, Rozita, Abdul Jalil, Mazlina, Abdul Majid, Azurah, A Samah

“…—The Marine Predators Algorithm (MPA) is classified under swarm intelligence methods based on its type of inspiration. …”
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Analysis of Shrinkage on Thick Plate Part using Genetic Algorithm by Najihah, S. N., Shayfull, Z., Nasir, S. M., Mohd Sazli, Saad, Rashidi, M. M., Fathullah, M., Noriman, N. Z.

“…Genetic Algorithm (GA) method was proposed to optimise the process parameters that would result in optimal solutions of optimisation goals. …”
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Improvement on rooftop classification of worldview-3 imagery using object-based image analysis by Norman, Masayu

“…The accuracy of each algorithm was evaluated using LibSVM, Bayes network, and Adaboost classifier. …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Alzaeemi, Shehab Abdulhabib, Tay, Kim Gaik, Huong, Audrey, Sathasivam, Saratha, Majahar Ali, Majid Khan

“…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

“…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majid Khan bin Majahar Ali, Majid Khan bin Majahar Ali

“…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

“…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

“…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Alzaeemi, Shehab Abdulhabib, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

“…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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Sequential and parallel multiple tabu search algorithm for multiobjective urban transit scheduling problems by Uvaraja, Vikneswary

“…This thesis studies multiobjective UTSP consisting of frequency setting, timetabling, simultaneous bus and driver scheduling by applying Multiple Tabu Search (MTS) algorithm. Metaheuristic methods have been widely applied to solve UTSP which is a NP-hard problem. …”
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Optimized scheduling for an airconditioning system based on indoor thermal comfort using the multiobjective improved global particle swarm optimization by Haniff, Mohamad Fadzli, Selamat, Hazlina, Khamis, Nuraqilla, Alimin, Ahmad Jais

“…However, most scheduling methods lack a systematic approach to ensuring optimal power consumption reduction and comfort experienced by occupants. …”
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CT reconstruction algorithm and low contrast detectability of phantom study: a systematic review and meta-analysis by Yusof, Nur Aimi Adibah, Abdul Karim, Muhammad Khalis, Mohd Asikin, Nursyazalina, Paiman, Suriati, Awang Kechik, Mohd Mustafa, Abd Rahman, Mohd Amiruddin, Mohd Noor, Noramaliza

“…Methods: In this study, a systematic review and a meta-analysis study were conducted on CT phantom for resolution study especially based on the low contrast detectability (LCD). …”
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A controller based on Optimal Type-2 Fuzzy Logic: Systematic design, optimization and real-time implementation by Fayek, H.M., Elamvazuthi, I., Perumal, N., Venkatesh, B.

“…The main scheme is to optimize the gains of the controller using Particle Swarm Optimization (PSO), then optimize only two parameters per type-2 membership function using Genetic Algorithm (GA). …”
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