Search Results - (( storage optimization method algorithm ) OR ( variable machine learning algorithm ))

Optimizing dam and reservoir operations using machine learning by Mohammad Abdullah Adib Almubaidin

Review of optimal methods and algorithms for sizing energy storage systems to achieve decarbonization in microgrid applications by Hannan M.A., Faisal M., Jern Ker P., Begum R.A., Dong Z.Y., Zhang C.

“…Carbon; Decarbonization; Electric energy storage; Fossil fuels; Global warming; Renewable energy resources; Carbon emissions; Decarbonisation; Energy storage system; Method; Microgrid; Optimal energy; Optimization algorithms; Sizing; Storage systems; System sizings; Cost effectiveness…”

Optimal allocation of battery energy storage system using whale optimization algorithm by Wong L.A., Ramachandaramurthy V.K.

“…Battery storage; Electric batteries; Battery energy storage systems; Firefly algorithms; Loss reduction; Meta-heuristic methods; Optimal allocation; Optimization algorithms; Overall system loss reduction; Performance; System loss; Whale optimization algorithm; Particle swarm optimization (PSO)…”

Prediction of Machine Failure by Using Machine Learning Algorithm by Fakhrurazi, Nur Amalina

Get full text
Get full text

Optimization algorithms for energy storage integrated microgrid performance enhancement by Roslan M.F., Hannan M.A., Ker P.J., Muttaqi K.M., Mahlia T.M.I.

“…Controllers; Electric power transmission; Electric power utilization; Energy management systems; Energy resources; Energy storage; Iterative methods; Learning algorithms; Microgrids; Operating costs; Particle swarm optimization (PSO); Scheduling; Scheduling algorithms; Stochastic systems; Storage management; Two term control systems; Charge-discharge; Day-ahead; Distributed Energy Resources; Microgrid; Optimization algorithms; Optimized controllers; Optimized scheduling; Performance enhancements; Scheduling controllers; Storage systems; Energy management…”

Ensemble-based machine learning algorithms for classifying breast tissue based on electrical impedance spectroscopy by Rahman, Sam Matiur, Ali, Md. Asraf, Altwijri, Omar, Alqahtani, Mahdi, Ahmed, Nasim, Ahamed, Nizam Uddin

“…Therefore, we aimed to classify six classes of freshly excised tissues from a set of electrical impedance measurement variables using five ensemble-based machine learning (ML) algorithms, namely, the random forest (RF), extremely randomized trees (ERT), decision tree (DT), gradient boosting tree (GBT) and AdaBoost (Adaptive Boosting) (ADB) algorithms, which can be subcategorized as bagging and boosting methods. …”
Get full text
Get full text
Get full text

Depression prediction using machine learning: a review by Abdul Rahimapandi, Hanis Diyana, Maskat, Ruhaila, Musa, Ramli, Ardi, Norizah

“…The aim of this study is to identify important variables used in depression prediction, recent depression screening tools adopted, and the latest machine learning algorithms used. …”
Get full text
Get full text
Get full text

Backtracking Search Algorithm Based Fuzzy Charging-Discharging Controller for Battery Storage System in Microgrid Applications by Faisal M., Hannan M.A., Ker P.J., Uddin M.N.

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. …”
Get full text
Get full text

Prediction of hydropower generation via machine learning algorithms at three Gorges Dam, China by Sattar Hanoon M., Najah Ahmed A., Razzaq A., Oudah A.Y., Alkhayyat A., Feng Huang Y., kumar P., El-Shafie A.

“…In this study, different supervised and unsupervised machine learning algorithms are proposed: artificial neural network (ANN), AutoRegressive Integrated Moving Aveage (ARIMA) and support vector machine (SVM). …”

Machine learning classifications of multiple organ failures in a malaysian intensive care unit by Norliyana, Nor Hisham Shah, Normy Norfiza, Abdul Razak, Athirah, Abdul Razak, Asma’, Abu-Samah, Fatanah, M. Suhaimi, Ummu Kulthum, Jamaludin

“…This study demonstrates the performances of different machine learning algorithms in the classification of multiple organ failures. …”
Get full text
Get full text
Get full text

Particle Swarm Optimization in Machine Learning Prediction of Airbnb Hospitality Price Prediction by Masrom, S., Baharun, N., Razi, N.F.M., Rahman, R.A., Abd Rahman, A.S.

“…Particle Swarm Optimization is useful to optimize the best variables combination for automating the features selection in machine learning models. …”
Get full text
Get full text

Grey Wolf Optimizer Based Battery Energy Storage System Sizing for Economic Operation of Microgrid by Sukumar S., Marsadek M., Ramasamy A., Mokhlis H.

Predicting dengue transmission rates by comparing different machine learning models with vector indices and meteorological data by Ong, Song Quan, Pradeep Isawasan, Ahmad Mohiddin Mohd Ngesom, Hanipah Shahar, As’malia Md Lasim, Gomesh Nair

“…Machine learning algorithms (ML) are receiving a lot of attention in the development of predictive models for monitoring dengue transmission rates. …”
Get full text
Get full text
Get full text
Get full text

Optimal planning of energy storage system for hybrid power system considering multi correlated input stochastic variables by ALAhmad A.K., Verayiah R., Ramasamy A., Marsadek M., Shareef H.

Subjects:

Weather prediction in Kota Kinabalu using linear regressions with multiple variables by Teong, Khan Vun, Chung, Gwo Chin, Jedol Dayou

“…Numerical weather prediction is the process of using existing numerical data on weather conditions to forecast the weather using machine learning algorithms. This study employs machine learning algorithms, a linear regression model using statistics, and two optimization approaches, the normal equation approach, and gradient descent approach to predict the weather based on a few variables. …”
Get full text
Get full text
Get full text
Get full text

Feasibility analysis for predicting the compressive and tensile strength of concrete using machine learning algorithms by Ziyad Sami B.H., Ziyad Sami B.F., Kumar P., Ahmed A.N., Amieghemen G.E., Sherif M.M., El-Shafie A.

Subjects:

Machine Learning Classifications of Multiple Organ Failures in a Malaysian Intensive Care Unit by Shah N.N.H., Razak N.N.A., Razak A.A., Abu-Samah A., Suhaimi F.M., Jamaluddin U.

“…This study demonstrates the performances of different machine learning algorithms in the classification of multiple organ failures. …”

Optimal placement and sizing of battery energy storage system considering the duck curve phenomenon by Wong L.A., Ramachandaramurthy V.K., Walker S.L., Ekanayake J.B.

Dynamic Bayesian Networks and Variable Length Genetic Algorithm for Dialogue Act Recognition by Ali Yahya, Anwar

“…Motivating by these drawbacks, this research proposes a new model of dialogue act recognition in which dynamic Bayesian machine learning is applied to induce dynamic Bayesian networks models from task-oriented dialogue corpus using sets of lexical cues selected automatically by means of new variable length genetic algorithm. …”
Get full text
Get full text