Search Results - machine ((loading problem) OR (learning problems))

Daily maximum load forecasting of consecutive national holidays using OSELM-based multi-agents system with weighted average strategy by Yap K.S., Yap H.J.

Subjects:

Comparison of Electricity Load Prediction Errors Between Long Short-Term Memory Architecture and Artificial Neural Network on Smart Meter Consumer by Salleh N.S.M., Suliman A., J�rgensen B.N.

“…Brain; Errors; Forecasting; Learning algorithms; Mean square error; Memory architecture; Network architecture; Smart meters; Time series; Demand-side; Electricity load; Error values; Load predictions; Machine learning algorithms; Mean absolute error; Mean squared error; Prediction errors; Regression problem; Times series; Long short-term memory…”

Multi-step time series prediction using recurrent kernel online sequential extreme learning machine / Liu Zongying by Liu , Zongying

“…Besides, concept drift problem in on-line learning model is solved by Drift Detection Machine (DDM). …”
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Sediment load prediction in Johor river: deep learning versus machine learning models by Latif S.D., Chong K.L., Ahmed A.N., Huang Y.F., Sherif M., El-Shafie A.

“…The statistical results showed that, despite their ability (deep learning and machine learning) to provide sediment predictions based on historical input datasets, machine learning, such as ANN, might be more prone to overfitting or being trapped in a local optimum than deep learning, evidenced by the worse in all metrics score. …”

Distributed learning based energy-efficient operations in small cell networks by Mughees, Amna

“…The thesis proposed a solution that employs unique characteristics of machine learning and game-theoretic framework to enable a model-free and energy-efficient small cell network. …”
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Application of artificial neural network for voltage stability monitoring / Valerian Shem by Shem, Valerian

“…This project is about monitoring the voltage stability of a system bus. Voltage stability problem has been one of the major concerns for electric utilities as a result of system heavy loading and needs to be solved. …”
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A comparison of machine learning models for suspended sediment load classification by AlDahoul N., Ahmed A.N., Allawi M.F., Sherif M., Sefelnasr A., Chau K.-W., El-Shafie A.

“…To this end, reliable and applicable models are required to compute and classify the SSL in rivers. The application of machine learning models has become common to solve complex problems such as SSL modeling. …”

Application of Extreme Learning Machine in Predicting Short- Term Wind Speed by Chen C.P., Tiong S.K., Koh S.P., Nasser A.A., Abbas D., Chooi F.Y.

Mixed pixel classification on hyperspectral image using imbalanced learning and hyperparameter tuning methods by Purwadi, Abu, Nur Azman, Mohd, Othman, Kusuma, Bagus Adhi

“…Hyperspectral has a huge phenomenon that makes computations heavy compared to other types of images because this image is 3D. The problem faced in hyperspectral image classification is the high computational load, especially if the spatial resolution of the image also has mixed pixel problems. …”
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Green machine learning approach for QoS improvement in cellular communications by Saeed, Mamoon M., Saeed, Rashid A., Azim, Mohammad Abdul, Ali, Elmustafa Sayed, Mokhtar, Rania A., Khalifa, Othman Omran

“…Artificial intelligent algorithms such as machine learning (ML) enable to detection of the dynamics in cellular networks by analyzing the complex cellular network processes and evaluating the spectrum and links qualities. …”
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Mixed integer goal programming model for flexible job shop scheduling problem (FJSSP) with load balancing / Shirley Sinatra Gran by Gran, Shirley Sinatra

“…The MIGP model formulated is to solve FJSSP with three objective functions, which are to minimize the makespan, the total machining time and the mean absolute deviation of the total machining time to achieve machine’s load balancing. …”
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Bayesian model averaging of load demand forecasts from neural network models by Hassan, S., Khosravi, A., Jaafar, J.

“…Neural network ensembles are designed to provide solutions to particular problems. Many researchers and academicians have adopted this NN ensemble technique, especially in machine learning, and has been applied in various fields of engineering, medicine and information technology. …”
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Bayesian model averaging of load demand forecasts from neural network models by Hassan, S., Khosravi, A., Jaafar, J.

“…Neural network ensembles are designed to provide solutions to particular problems. Many researchers and academicians have adopted this NN ensemble technique, especially in machine learning, and has been applied in various fields of engineering, medicine and information technology. …”
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Bayesian model averaging of load demand forecasts from neural network models by Hassan, S., Khosravi, A., Jaafar, J.

“…Neural network ensembles are designed to provide solutions to particular problems. Many researchers and academicians have adopted this NN ensemble technique, especially in machine learning, and has been applied in various fields of engineering, medicine and information technology. …”
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A review of big data analytics on customer complaints in the electricity industry by Saipol H.F.S., Drus S.M., Othman M.

“…On the basis of a study of the different researches, different techniques of machine learning have been used because of its accuracy and in finding a pattern to solve the relevant electrical problem such as predicting power demand, managing power loads, and enhancing strategic planning. …”

Mental health prediction using machine learning: taxonomy,applications, and challenges by Jetli Chung, Jason Teo

“…The increase of mental health problems and the need for effective medical health care have led to an investigation of machine learning that can be applied in mental health problems. )is paper presents a recent systematic review of machine learning approaches in predicting mental health problems. …”
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Development of hybrid machine learning model for simulation of chemical reactors in water treatment applications: Absorption in amino acid by Yanjie Zhang, Lakshmi Thangavelu, Talib Zeedan Taban, Walid Kamal Abdelbasset, Wanich Suksatan, Mohd Sani Sarjadi, Md Lutfor Rahman, Shaheen M. Sarkar, May Alashwal, Mohammed Zwawi, Mohammed Algarni

“…A number of CO2 solubility data are collected from resources and used for training and validation of machine learning computations. Several inputs were considered for the developed machine learning models. …”
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Design and fabrication of minimalzie wall table with storage / Wan Muhammad Jazli Na'im Wan Rozain by Wan Rozain, Wan Muhammad Jazli Na'im

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Mixed-load machine utilization improvement and transfer batch size optimization using hybrid simulation approach by Asih, Hayati Mukti

“…Firstly, the problem of mixed-load tester was formulated through a mathematical model. …”
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Activity recognition using optimized reduced kernel extreme learning machine (OPT-RKELM) / Yang Dong Rui by Yang , Dong Rui

“…One of the major research problems is the computation resources required by machine learning algorithm used for classification for HAR. …”
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