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Fault classification in smart distribution network using support vector machine by Chuan O.W., Ab Aziz N.F., Yasin Z.M., Salim N.A., Wahab N.A.

“…In this paper, a machine-learning algorithm known as Support Vector Machine (SVM) for fault type classification in distribution system has been developed. …”

Review of Plug-Based Load Energy Management Systems (PLEMS) for energy and comfort management of buildings by Amin, F.B.M., Mahmood, A.K.

“…A number of previous research that directed to PLEMS along with building sector, objectives, control systems, algorithm and simulation tools are also presented in this paper. …”
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Development of electromyography-controlled 3D printed robot hand and supervised machine learning for signal classification by Abdul Wahit, Mohamad Aizat

“…The current study of the hand posture classification requires a higher number of EMG sensor used to achieve an accurate classification performance that leads the system to be complicated. …”
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Development of collision avoidance warning system for heavy vehicles featuring adaptive minimum safe distance / Airul Sharizli Abdullah by Airul Sharizli, Abdullah

“…The determination of a minimum safe distance is a very fundamental and pivotal step for CAWS system activation. Hence, the success of CAWS system relies very much on whether the activation algorithm or model used is able to indicate a minimum safe distance precisely and timely. …”
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Distribution network fault section estimation using analytical database approach by Mokhtar, Ahmad Safawi

“…The proposed method was evaluated and tested on a typical distribution network by using voltage waveforms produced by PSCAD/EMTDC. n power system simulator. …”
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Short term load forecasting using a hybrid neural network by Yap K.S., Abidin I.Z., Lim C.P., Shah M.S.

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Support vector machine for day ahead electricity price forecasting by Razak I.A.B.W.A., Abidin I.B.Z., Siah Y.K., Rahman T.K.B.A., Lada M.Y., Ramani A.N.B., Nasir M.N.M., Ahmad A.B.

“…Previous day data of Hourly Ontario Electricity Price (HOEP), generation's price and demand from Ontario power market are used as the inputs for training data. The simulation is held using LSSVMlab in Matlab with the training and testing data of 2004. …”

Intuitive content management system via manipulation and duplication with if-else rules classification by Chan, Chung Hoong

“…As a result, ICMS can transform dynamic websites into static websites with faster load speed using manipulation method mixed with data mining classification prediction and Boyer-Moore Horspool algorithm which can be classified, edited, adjustable and searched more precisely. …”
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Feature extraction of power disturbance signal using time frequency analysis by Sihab, Norsabrina

“…Those signals are transformed into time frequency plane using Bdistribution algorithm. Then the important feature vectors or components are extracted using Singular Value Decomposition (SVD) and Principle Component Analysis (PCA). …”
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Dynamic load balancing policy in grid computing with multi-agent system integration by Yahaya, Bakri, Latip, Rohaya, Othman, Mohamed, Abdullah, Azizol

“…The unique capabilities offered by multi-agent systems can be integrated or combined with the structure of dynamic load balancing to produce a better strategy to produce a better dynamic load balancing algorithm with multi-agent systems.…”
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Power system security assessment using artificial neural network: article / Mohd Fathi Zakaria by Zakaria, Mohd Fathi

“…Extensive testing and training of the proposed ANN based apprnach indicates its viability for power system steady state stability classification assessment.…”
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Development of Phasor Measurement Unit Based Fault Detection and Faulty Line Classification in Electrical Power System by Muhammad Qasim, Khan

“…This study first focuses on modifying the PMU model for standard test systems in a MATLAB Simulink environment. This model implements Non-Recursive Phasor Estimation (NRPE) algorithm. …”
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Dynamic load balancing policy with communication and computation elements in grid computing with multi-agent system integration by Yahaya, Bakri, Latip, Rohaya, Othman, Mohamed, Abdullah, Azizol

“…The unique capabilities offered by multi-agent systems can be integrated or combined with the structure of dynamic load balancing to produce a better strategy and better load balancing algorithm. …”
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Assessment of cognitive load using multimedia learning and resting states with deep learning perspective by Qayyum, A., Faye, I., Malik, A.S., Mazher, M.

“…The results shows that alpha brain wave produced consistent behavior using for all cognition tasks based on pre-trained CNN models for classification and cognitive load assessment. © 2018 IEEE…”
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An optimal under frequency load shedding scheme for islanded distribution network / Amalina Izzati Md Isa by Md Isa, Amalina Izzati

“…Two new algorithms i.e., Load Classification based Fuzzy Logic (LCFL) and Binary Evolutionary Programming (BEP) are introduced in the module. …”
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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.

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Load balancing and server consolidation in cloud computing environments: a meta-study by Fadhil, Mohammed Alaa, Othman, Mohamed

“…This meta-study, reviews the literature on load balancing and server consolidation and presents a ready reference taxonomy on the most efficient algorithms that achieve load balancing and server consolidation. …”
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An application of a novel technique for assessing the operating performance of existing cooling systems on a university campus by Abdalla, E.A.H., Nallagownden, P., Nor, N.B.M., Romlie, M.F., Hassan, S.M.

“…Two contributions in this work are: (1) the prediction of a model by using Adaptive Neuro-Fuzzy Inference System (ANFIS)-based Fuzzy Clustering Subtractive (FCS), and (2) the classification and optimization of the predicted models by using an Accelerated Particle Swarm Optimization (APSO) algorithm. …”
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Teleworking monitoring system using NILM and K-NN algorithms: a strategy for sustainable smart cities by Yang, Chuan Choong, Noh, Adriana, Ibrahim, Siti Noorjannah, Asnawi, Ani Liza, Mohamed Azmin, Nor Fadhillah

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Development of vehicle detection and counting system for traffic analysis using computer vision by Saw, Kenny Wei Wen

“…Initially, the image and video dataset of road traffic is gathered from various online sources and undergoes categorization before loaded into the system for model training. Then two model training process begins, one is for vehicle model detection to learn the feature of a vehicle and the image background, while another training is for binary weather classification for rainy and sunny conditions. …”
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