Search Results - (( storage optimization means algorithm ) OR ( java application optimisation algorithm ))

Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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Optimal Algorithms for Energy Storage Systems in Microgrid Applications: An Analytical Evaluation Towards Future Directions by Reza M.S., Rahman N., Wali S.B., Hannan M.A., Ker P.J., Rahman S.A., Muttaqi K.M.

Investigating dam reservoir operation optimization using metaheuristic algorithms by Lai V., Essam Y., Huang Y.F., Ahmed A.N., El-Shafie A.

Enhancing reservoir operations with charged system search (CSS) algorithm: Accounting for sediment accumulation and multiple scenarios by Almubaidin M.A.A., Ahmed A.N., Malek M.A., Mahmoud M.A., Sherif M., El-Shafie A.

“…Optimization methods vary depending on objectives, reservoir type, and algorithms used. …”

Development of multi-objective optimization methods for integrated scheduling of handling equipment (AGVs, QCs, SP-AS/RS) in automated container terminals by Homayouni, Seyed Mahdi

“…Therefore, two meta-heuristic algorithms, namely genetic algorithm (GA) and simulated annealing (SA) algorithm, were developed to optimize the integrated scheduling of handling equipment. …”
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Optimizing dam and reservoir operations using machine learning by Mohammad Abdullah Adib Almubaidin

Enhancing reservoir operations with charged system search (CSS) algorithm: Accounting for sediment accumulation and multiple scenarios by Almubaidin, Mohammad Abdullah Abid, Ali, Najah Ahmed *, Marlinda, Abdul Malek, Moamin, A. Mahmoud, Sherif, Mohsen, El-Shafie, Ahmed

“…Optimization methods vary depending on objectives, reservoir type, and algorithms used. …”
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Wind power forecasting with metaheuristic-based feature selection and neural networks by Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Mohd Mawardi, Saari, Mohammad Fadhil, Abas

“…Specifically, five distinct algorithms - Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Teaching-Learning-Based Optimization (TLBO), and Evolutionary Mating Algorithm (EMA) - are integrated with NN model to identify optimal feature subsets from a comprehensive dataset of 18 diverse features. …”
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Towards large scale unconstrained optimization by Abu Hassan, Malik

“…However for other problems the MF-BFGS method is more competitive because of its rapid convergence. The matrix- storage methods can be gread accelerated by means of a simple scaling. …”
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Globalization of Barzilai and Borwein Method for Unconstrained Optimization by Farid, Mahboubeh

“…Due to BB method’s simplicity, low storage and numerical efficiency, the Barzilai and Borwein method has received a good deal of attention in the optimization community but despite all these advances, stepsize of BB method is computed by means of simple approximation of Hessian in the form of scalar multiple of identity and especially the BB method is not monotone, and it is not easy to generalize the method to general nonlinear functions. …”
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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.

“…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. …”

Energy band gap modeling of doped bismuth ferrite multifunctional material using gravitational search algorithm optimized support vector regression by Owolabi, Taoreed O., Abd Rahman, Mohd Amiruddin

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Quasi-Newton type method via weak secant equations for unconstrained optimization by Lim, Keat Hee

“…In this thesis, variants of quasi-Newton methods are developed for solving unconstrained optimization problems. These quasi-Newton type methods are differed from the standard quasi-Newton methods in the calculation and storage of the approximate Hessian matrix at every iteration. …”
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Web-based expert system for material selection of natural fiber- reinforced polymer composites by Ahmed Ali, Basheer Ahmed

“…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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State of charge estimation of lithium-ion batteries in an electric vehicle using hybrid metaheuristic - deep neural networks models by Zuriani, Mustaffa, Mohd Herwan, Sulaiman, Isuwa, Jeremiah

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Predicting the optimum compositions of a transdermal nanoemulsion system containing an extract of Clinacanthus nutans leaves (L.) for skin antiaging by artificial neural network mo... by Che Sulaiman, Intan Soraya, Basri, Mahiran, Masoumi, Hamid Reza Fard, Ashari, Siti Efliza, Basri, Hamidon, Ismail, Maznah

“…The optimum topologies were selected among the learning algorithms trained with lowest root mean square values. …”
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Meta-heuristic approaches for reservoir optimisation operation and investigation of climate change impact at Klang gate dam by Lai, Vivien Mei Yen

“…The monthly storage capacity fails in 2077, substantially earlier than the other three algorithms in Scenario 2. …”
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IoT based Song Recognition for FM Radio Station Broadcasting by Murtadha Arif Sahbudin, Chakib Chaouch, Marco Scarpa, Salvatore Serrano

Conceptual Sim-Heuristic optimization algorithm to evaluate the climate impact on reservoir operations by Lai V., Huang Y.F., Koo C.H., Najah Ahmed A., El-Shafie A.

A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

“…When noise exists in training data, the decision boundary of SVM would deviate from the optimal hyperplane severely. To overcome SVM drawback for noise data problem, WSVM using KPCM algorithm was used but WSVM using kernel-based learning algorithm such as KPCM algorithm suffer from training complexity, expensive computation time and storage memory when noise data contaminate training data. …”
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