Search Results - (( parameter extraction method algorithm ) OR ( parameter extraction utilizing algorithm ))

Extraction of photovoltaic module model's parameters using an improved hybrid differential evolution/electromagnetism-like algorithm by Muhsen D.H., Ghazali A.B., Khatib T., Abed I.A.

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

“…Extraction of the photovoltaic (PV) model parameters is critical for forecasting these systems’ energy output. …”
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Development of hippocampus MRI image segmentation algorithm for progression detection of alzheimer’s disease (AD) by Gilani Mohamed, Mohamed Ahmed

“…The active contour method (Chan-Vese) was utilized to extract the ROI parameters (hippocampus). …”
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Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images by Adil Humayun, Khan

“…In the third classification algorithm, hybrid features are extracted using AlexNet and VGG-16 through a transfer learning approach where parameter manipulation is implemented to simplify the network. …”
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A meta-heuristic algorithm for the minimal high-quality feature extraction of online reviews by Mat Zin, Harnani, Mustapha, Norwati, Azmi Murad, Masrah Azrifah, Mohd Sharef, Nurfadhlina

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Characterization of PV panel and global optimization of its model parameters using genetic algorithm by Ismail M.S., Moghavvemi M., Mahlia T.M.I.

“…This paper details an improved modeling technique for a photovoltaic (PV) module; utilizing the optimization ability of a genetic algorithm, with different parameters of the PV module being computed via this approach. …”

Zero root-mean-square error for single- and double-diode photovoltaic models parameter determination by Mohammed Ridha, Hussein, Hizam, Hashim, Mirjalili, Seyedali, Othman, Mohammad Lutfi, Ya’acob, Mohammad Effendy

“…This may be extremely helpful both practically and theoretically in the PV system simulation, optimization, and evaluation. Numerous stochastic methods have been widely utilized in recent decades to tackle the parameter extraction optimization problem. …”
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A Meta-heuristic Algorithm for the Minimal High-Quality Feature Extraction of Online Reviews by Mat Zin, Harnani, Mustapha, Norwati, Azmi Murad, Masrah Azrifah, Mohd Sharef, Nurfadhlina

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Characterization of PV panel and global optimization of its model parameters using genetic algorithm by Ismail, M.S., Moghavvemi, Mahmoud, Mahlia, T.M.I.

“…This paper details an improved modeling technique for a photovoltaic (PV) module; utilizing the optimization ability of a genetic algorithm, with different parameters of the PV module being computed via this approach. …”
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Using a novel algorithm in ultrasound images to detect renal stones by Sania Eskandari, Saeed Meshgini, Ali Farzamnia

“…Fuzzy C-means, K-means, and Expectation–Maximization algorithms are used to segment the renal calculi from the kidney ultrasound image; further region parameters are extracted from the segmented region. …”
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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.

“…However, existing RUL prediction approaches have difficulties with variability and nonlinearity that occur during battery degradation, data extraction, feature extraction, hyperparameters optimization, and prediction model uncertainty. …”

CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING by ISLAM, BADAR UL ISLAM

“…To overcome these ANN problems, the Genetic Algorithm (GA) has been most frequently used for this purpose, however, some drawbacks of GA include, slow search speed and dependence on initial parameters. …”
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Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

“…In order to estimate the quality of ‘pruned’ features, self-adaptive DE algorithm is proposed. Two parameters (population size and generation numbers) are adaptively adopted from number of remaining ranking features. …”
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Finite Element Modeling Of Ballistic Penetration into Fabric Armor by Talebi, Hossein

“…These parameters were friction, boundary conditions, projectile nose diameter and projectile nose angle. …”
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Deriving the absorption coefficients of lattice mismatched InGaAs using genetic algorithm by Lee H.J., Ali Gamel M.M., Ker P.J., Jamaludin M.Z., Wong Y.H., Yap K.S., Willmott J.R., Hobbs M.J., David J.P.R., Tan C.H.

“…By selecting the best gene for the next iteration, the utilization of Genetic Algorithm has significantly reduced the number of iterations from a maximum of 10 000 to 300. …”

A new descriptor for smile classification based on cascade classifier in unconstrained scenarios by Hassen, Oday Ali, Abu, Nur Azman, Zainal Abidin, Zaheera, Saad, Mohamed Darwish

“…In this paper, an adaptive model for smile classification is suggested that integrates a row-transform-based feature extraction algorithm and a cascade classifier to increase the precision of facial recognition. …”
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Supervised neural network classifier for voice pathology by Murugesa Pandiyan, Paulraj, Prof. Madya Dr, Sazali, Yaacob, Prof. Dr., Sivanandam, S. N., Hariharan, Muthusamy

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Machine learning in botda fibre sensor for distributed temperature measurement by Nur Dalilla binti Nordin

“…An alternative method is proposed, utilizing machine learning algorithms. …”

IMPLEMENTATION OF A TIME SERIES PREDICTION ALGORITHM FOR COVID-19 CONFIRMED CASES IN MALAYSIA : A PRELIMANARY STUDY AFTER THE RECOVERY MOVEMENT CONTROL ORDER by Tee, Bee Lin

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Edge detection of MRI images using artificial neural network by Gunawan, Teddy Surya, Kartiwi, Mira, Abdul Malik, Noreha

“…To determine the final pixel edge value (0 or 1), an optimum threshold was utilized. Results To obtain the best parameters which produce optimum edge of MRI images, we varied the number of neurons in the hidden layer, as well as the threshold. …”
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