Search Results - (( data collection methods algorithm ) OR ( parameter optimization model algorithm ))

Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics by Mohammad Jarrah, Mu'ath Ibrahim

“…Chemical Vapor Deposition (CVD) is the most efficient method for CNTs production.However,using CVD method encounters crucial issues such as customization,time and cost.Therefore,Response Surface Methodology (RSM) is proposed for modeling and the ABC-βHC is proposed for optimization purpose to address such issues.The selected CNTs characteristics are CNTs yield and quality represented by the ratio of the relative intensity of the D and G-bands (ID/IG).Six case studies are generated from collected dataset including four cases of CNTs yield and one case of ID/IG as single objective optimization problems,while the sixth case represents multi-objective problem.The input parameters of each case are a subset from the set of input parameters including reaction temperature,duration,carbon dioxide flow rate,methane partial pressure,catalyst loading,polymer weight and catalyst weight.The models for the first three case studies were mentioned in the original work.RSM is proposed to develop polynomial models for the output responses in the other three cases and to identi significant process parameters and interactions that could affect the CNTs output responses.The developed models are validated using t-test,correlation and pattern matching.The predictive results have a good agreement with the actual experimental data.The models are used as objective functions in optimization techniques.For multi-objective optimization,this study proposes Desirability Function Approach (DFA) to be integrated with other proposed algorithms to form hybrid techniques namely RSM-DFA,ABC-DFA and ABC-βHC-DFA.The proposed algorithms and other selected well-known algorithms are evaluated and compared on their CNTs yield and quality.The optimization results reveal that ABC-βHC and ABC-βHC-DFA obtained significant results in terms of success rate,required time,iterations,and function evaluations number compared to other well-known algorithms.Significantly,the optimization results from this study are better than the results from the original work of the collected dataset.…”
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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

“…Numerous research have reviewed and presented approaches for figuring out the PV models parameter optimization problem in the literature. …”
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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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Adaptive Fast Orthogonal Search (FOS) algorithm for forecasting streamflow by Osman A., Afan H.A., Allawi M.F., Jaafar O., Noureldin A., Hamzah F.M., Ahmed A.N., El-shafie A.

Optimization of ANFIS with GA and PSO estimating α ratio in driven piles by Moayedi, Hossein, Raftari, Mehdi, Sharifi, Abolhasan, Wan Jusoh, Wan Amizah, A. Rashid, Ahmad Safuan

“…This study aimed to optimize Adaptive Neuro-Fuzzy Inferences System (ANFIS) with two optimization algorithms, namely, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) for the calculation friction capacity ratio (α) in driven shafts. …”
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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 purpose of this study is to evaluate and compare the performance of these algorithms in terms of accuracy. The methodology used includes data collection, preprocessing, and algorithm implementation with evaluation using crossvalidation techniques. …”
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Photogrammetric low-cost unmanned aerial vehicle for pothole detection mapping / Shahrul Nizan Abd Mukti by Abd Mukti, Shahrul Nizan

“…For volume estimation purpose, a Digital Elevation Models (DEM) were generated from photogrammetric method with flight parameters of three (3) different camera focal length and ten (10) UAV altitude. …”
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3D prediction of tunneling-induced ground movements based on a hybrid ANN and empirical methods by Hajihassani, M., Kalatehjari, R., Marto, A., Mohamad, H., Khosrotash, M.

“…To overcome these problems, the use of optimization algorithms to train ANNs is of advantage. …”
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3D prediction of tunneling-induced ground movements based on a hybrid ANN and empirical methods by Hajihassani, M., Kalatehjari, R., Marto, A., Mohamad, H., Khosrotash, M.

“…To overcome these problems, the use of optimization algorithms to train ANNs is of advantage. …”
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Development of wwm system using mlnn-ga for ph prediction of water quality in catchment area by Muhammad Aznil, Ab Aziz

“…Data samples need to be collected and evaluated in the laboratory. …”
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Neural Network Modeling And Optimization For Enzymatic Hydrolysis Of Xylose From Rice Straw by Norhalim, Nur’atiqah

“…In this thesis, enzymatic hydrolysis was utilized in the production of xylose from rice straw. The process model was developed by the modeling techniques using feed-forward artificial neural network (FANN) and optimized using both particle swarm optimization (PSO) and genetic algorithm (GA). …”
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Prediction of building damage induced by tunnelling through an optimized artificial neural network by Moosazadeh, S., Namazi, E., Aghababaei, H., Marto, A., Mohamad, H., Hajihassani, M.

“…This paper predicts the building damage based on a model obtained from artificial neural network and a particle swarm optimization algorithm. …”
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Prediction of building damage induced by tunnelling through an optimized artificial neural network by Moosazadeh, S., Namazi, E., Aghababaei, H., Marto, A., Mohamad, H., Hajihassani, M.

“…This paper predicts the building damage based on a model obtained from artificial neural network and a particle swarm optimization algorithm. …”
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Development of cost reduction mathematical model for natural gas transmission network system by Mehrdad, Nikbakht Eliaderany

“…Thus, the total cost of the network was decreased. Therefore, the data clearly exhibit that the proposed method provides a solution that was nearer to an optimized network.…”
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PID controller based on bird mating optimizer for vibration cancellation of horizontal flexible plate by Muhammad Farith Nazreen, Abu Samah, Muhamad Sukri, Hadi, Abdul Malek, Abdul Wahab, Nadzirah, Mohd Mokhtar, Intan Zaurah, Mat Darus

“…Then, the linear autoregressive with exogenous (ARX) model is selected as a model structure for model development using system identification method via bird mating optimizer (BMO) algorithm. …”
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Power prediction using the wind turbine power curve and data-driven approaches / Ehsan Taslimi Renani by Ehsan Taslimi , Renani

“…To evaluate the performance of the Weibull parameters’ estimator methods, two sets of data are considered, one based on simulated data with different random variable size and the other based on actual data collected from a wind farm in Iran. …”
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Improved genetic algorithm for direct current motor high speed controller implemented on field programmable gate array by Alkhafaji, Falih Salih

“…There are many researches have been done to optimize PI controller based evolutionary algorithm, such as Genetic Algorithm (GA). …”
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Modeling of cupping suction system based on system identification method by Kavindran, Suresh

“…By minimizing integral square errors, fractional order model parameters were optimized (ISE). The results reveal that the better the precision of the modelling cupping system parameter, the lower the error. …”
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Development of tool life prediction model of TiAlN coated tools during the high speed hard milling of AISI H13 steel by Amin, A. K. M. Nurul, Hafiz, A.M. Khalid, Lajis, M. A.

“…Öktem et al. [6] incorporated RSM with developed genetic algorithm to optimize cutting parameters for better surface quality in case of Inconel 718. …”
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Classification of labour pain using electroencephalogram signal based on wavelet method / Sai Chong Yeh by Sai , Chong Yeh

“…The training and parameters selection of the machine learning algorithms are conducted using EEG data collected from ten subjects in the laboratory. …”
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