Search Results - (( model evaluation means algorithm ) OR ( panel reservation system algorithm ))*

Techno-economic analysis of an optimized photovoltaic and diesel generator hybrid power system for remote houses in a tropical climate by Ismail M.S., Moghavvemi M., Mahlia T.M.I.

“…The optimal tilt angle of the PV panels in order to increase the generated energy was obtained using genetic algorithm. …”

Switching algorithm for leakage current reduction in a PV- no transformer inverter system by Khan, M.N.H., Hasan, M.R., Alam, M.K.

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Genetic algorithm based optimization on modeling and design of hybrid renewable energy systems by Ismail M.S., Moghavvemi M., Mahlia T.M.I.

“…A sizing optimization of a hybrid system consisting of photovoltaic (PV) panels, a backup source (microturbine or diesel), and a battery system minimizes the cost of energy production (COE), and a complete design of this optimized system supplying a small community with power in the Palestinian Territories is presented in this paper. …”

An electromagnetism-like mechanism algorithm approach for photovoltaic system optimization by Tan J.D., Koh S.P., Tiong S.K., Ali K., Koay Y.Y.

“…In this paper, an artificial intelligent approach is proposed for the optimization of a photovoltaic solar energy harvesting system. An Electromagnetism-Like Mechanism Algorithm (EM) has been developed to search for the hourly optimum tilt angles for photovoltaic panels. …”

Optimization of Off-Centre bracing system using Genetic Algorithm by Yazdi, H.A. Mosalman, Ramli Sulong, Nor Hafizah

“…This type of bracing system is mostly used in seismic areas and it allows architects to have more openings in the panel area. …”
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Modeling and Analysis of New Hybrid Clustering Technique for Vehicular Ad Hoc Network by Abdulrazzak H.N., Hock G.C., Mohamed Radzi N.A., Tan N.M.L., Kwong C.F.

“…The evaluation process was implemented on RK-Means, K-Means++, and OK-Means models. …”

Neural Networks Ensemble: Evaluation of Aggregation Algorithms for Forecasting by HASSAN, SAIMA

“…The performances ofthese aggregation algorithms ofNNs ensemble were evaluated with the mean absolutepercentage error and symmetric mean absolute percentage error. …”
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Implementation of a modified incremental conductance MPPT algorithm with direct control based on a fuzzy duty cycle change estimator using dSPACE by Radjai, T., Rahmani, L., Mekhilef, Saad, Gaubert, J.P.

“…The results obtained confirm the advantages of the proposed algorithm. (C) 2014 Elsevier Ltd. All rights reserved.…”
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Analysis and evaluation of various aspects of solar radiation in the Palestinian territories by Ismail M.S., Moghavvemi M., Mahlia T.M.I.

Evaluation of MLP-ANN Training Algorithms for Modeling Soil Pore-Water Pressure Responses to Rainfall by Mustafa, M.R., Rezaur, R.B., Saiedi, Saied, Rahardjo, H., Isa, M.H.

“…The performance of the training algorithms was evaluated using standard performance evaluation measures—root mean square error, coefficient of efficiency, and the time and number of epochs required to reach a predefined accuracy. …”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

“…The research starts with developing the hybrid deep learning model consisting of DNN and a K-Means Clustering Algorithm. …”
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Algorithmic approaches in model selection of the air passengers flows data by Ismail, Suzilah, Yusof, Norhayati, Tuan Muda, Tuan Zalizam

“…Algorithm is an important element in any problem solving situation.In statistical modelling strategy, the algorithm provides a step by step process in model building, model testing, choosing the ‘best’ model and even forecasting using the chosen model.Tacit knowledge has contributed to the existence of a huge variability in manual modelling process especially between expert and non-expert modellers.Many algorithms (automated model selection) have been developed to bridge the gap either through single or multiple equation modelling.This study aims to evaluate the forecasting performances of several selected algorithms on air passengers flow data based on Root Mean Square Error (RMSE) and Geometric Root Mean Square Error (GRMSE).The findings show that multiple models selection performed well in one and two step-ahead forecast but was outperformed by single model in three step-ahead forecasts.…”
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Optimal neural network approach for estimating state of energy of lithium-ion battery using heuristic optimization techniques by Lipu M.S.H., Hussain A., Saad M.H.M., Hannan M.A.

A static jobs scheduling for independent jobs in Grid Environment by using Fuzzy C-Mean and Genetic algorithms by Lorpunmanee, Siriluck, Md. Sap, Mohd. Noor, Abdullah, Abdul Hanan, Srinoy, Surat

“…We present a static job scheduling algorithm by using Fuzzy C-Mean and Genetic algorithms. …”
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Suspended sediment load prediction using artificial neural network and ant lion optimization algorithm by Banadkooki F.B., Ehteram M., Ahmed A.N., Teo F.Y., Ebrahimi M., Fai C.M., Huang Y.F., El-Shafie A.

Application and evaluation of the evolutionary algorithms combined with conventional neural network to determine the building energy consumption of the residential sector by Wang G., Mukhtar A., Moayedi H., Khalilpoor N., Tt Q.

“…The results of the evaluation demonstrated varying performances among the three evolutionary algorithms. …”

All-pass filtered x least mean square algorithm for narrowband active noise control by Mondal (Das), Kuheli, Das, Saurav, Abu, Aminudin, Hamada, Nozomu, Toh, Hoong Thiam, Das, Saikat, Faris, Waleed Fekry

“…Most available ANC uses the secondary path modelling including filtered x least mean square (FxLMS) algorithm. …”
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Neural network ensemble: Evaluation of aggregation algorithms in electricity demand forecasting by Hassan, S., Khosravi, A., Jaafar, J.

“…These algorithms include equal-weights combination of Best NN models, combination of trimmed forecasts, and Bayesian Model Averaging (BMA). …”
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Neural network ensemble: Evaluation of aggregation algorithms in electricity demand forecasting by Hassan, S., Khosravi, A., Jaafar, J.

“…These algorithms include equal-weights combination of Best NN models, combination of trimmed forecasts, and Bayesian Model Averaging (BMA). …”
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Neural network ensemble: Evaluation of aggregation algorithms in electricity demand forecasting by Hassan, S., Khosravi, A., Jaafar, J.

“…These algorithms include equal-weights combination of Best NN models, combination of trimmed forecasts, and Bayesian Model Averaging (BMA). …”
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