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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.

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

“…In the hybrid scheme, the initial parameters of the modified BP neural network are optimized by using the global search ability of genetic algorithm, improved by cat chaotic mapping to enrich its optimization capability. …”
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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

“…In this work, a new improved arithmetic optimization method based on the adaption of Newton–Raphson and Levenberg–Marquardt damping parameter (IAOANRaLMp) is presented to globally extract the parameter of the single- and double-diode PV models. …”
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A buffer-based online clustering for evolving data stream by Islam, Md. Kamrul, Ahmed, Md. Manjur, Kamal Z., Zamli

“…This algorithm recursively updates the micro-cluster radius to its local optimal. …”
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Parameter extraction of solar photovoltaic modules using penalty-based differential evolution by Ishaque, K., Salam, Z., Mekhilef, Saad, Shamsudin, A.

“…The two diode model of a solar cell is used as the basis for the extraction problem. The analyses carried out using synthetic current-voltage (I-V) data set showed that the proposed P-DE outperforms other Evolutionary Algorithm methods, namely the simulated annealing (SA), genetic algorithm (GA), and particle swarm optimization (PSO). …”
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New global maximum power point tracking and modular voltage equalizer topology for partially shaded photovoltaic system / Immad Shams by Immad , Shams

“…In terms of controller-based, in this work, a new global maximum power point tracking (GMPPT) algorithm based on a modified butterfly optimization algorithm (MBOA) has been proposed. …”
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Modeling of road geometry and traffic accidents by hierarchical object-based and deep learning methods using laser scanning data by Sameen, Maher Ibrahim

“…There was a need for efficient segmentation algorithm, optimization strategy, feature extraction and classification, and robust statistical and computational intelligence models to accomplish the set aims. …”
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PREDICTIVE MAXIMUM POWER POINT TRACKING (MPPT) ALGORITHM FOR PERMANENT EXCHANGE MEMBRANE FUEL CELL (PEMFC) by MOHD RIZZWAN, MINGGU

“…A comparison of PEMFC performances based on the proposed technique with other existing MPPT algorithms will be done to validate the algorithm performance. …”
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An enhanced computational model based on social spider optimisation algorithm for EEG- based emotion recognition by Al-Qammaz, Abdullah Yousef Awwad

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Obso based fractional pid for mppt-pitch control of wind turbine systems by Mehedi, I.M., Al-Saggaf, U.M., Vellingiri, M.T., Milyani, A.H., Saad, N.B., Yahaya, N.Z.B.

“…The OBSO algorithm is derived from the integration of oppositional based learning (OBL) concept with the traditional BSO algorithm in order to improve the convergence rate, which is then applied to effectively choose the parameters involved in the FOPID controller. …”
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A novel MPPT approach for photovoltaic system using Pelican optimization and high-gain DC–DC converter by Akter, Khadiza, Motakabber, S. M. A., Alam, A. H. M. Zahirul, Yusoff, Siti Hajar, Pachauri, Rupendra Kumar, Malik, Hasmat, Jadoun, Vinay Kumar

“…As one of the most practical and widely used methods for meeting global clean energy demands, PV systems are integral to modern energy strategies. …”
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Hybrid indoor positioning utilizing multipath- assisted fingerprint and geometric estimation for single base station systems by Manap, Zahariah

“…When compared to a simple fingerprinting method, the median error for the hybrid method is observed to be 4.06 cm, which is substantially lower than the 538 cm median error of the fingerprinting method. …”
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Mathematical modelling and hybrid ACO-PSO technique for PV performance improvement by Ali Mahmood, Humada

“…Secondly, a hybrid Ant Colony Optimisation-Particle Swarm Optimisation (ACO-PSO) algorithm was proposed to optimally determine the MPPT parameters. …”
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MRFGRO: a hybrid meta-heuristic feature selection method for screening COVID-19 using deep features by Dey, Arijit, Chattopadhyay, Soham, Pawan Kumar Singh, Ahmadian, Ali, Ferrara, Massimiliano, Senu, Norazak, Sarkar, Ram

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Optimization of turning parameters using genetic algorithm method by Shah Izwandi, Mohd Zawawi

“…This study about development of optimization for turning parameters based on the Genetic Algorithm (GA). …”
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Parameters optimization of surface grinding process with particles swarm optimization, gravitational search, and sine cosine algorithms: a comparative analysis by Asrul, Adam

“…The efficiency of the three algorithms are evaluated and compared with previous results obtained by other optimization methods on similar studies. …”
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Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization by Nur Iffah, Mohamed Azmi

“…Particle swarm optimization algorithm (PSO) is one of the artificial intelligence methods. …”
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Optimization of turning parameters using ant colony optimization by Mohamad Nazri, Semoin

“…The project objectives are to develop Ant Colony Optimization (ACO) algorithm for CNC turning process and to optimize turning parameters for minimized production cost per unit. …”
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Parameter estimation in double exponential smoothing using genetic algorithm / Foo Fong Yeng, Lau Gee Choon and Zuhaimy Ismail by Foo, Fong Yeng, Lau, Gee Choon, Ismail, Zuhaimy

“…Trial and error often serves as the best method to determine the parameter. Therefore, a good optimization technique is required for identify the best parameter in minimizing the forecast errors. …”
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