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Electricity load profile determination by using fuzzy C-means and probability neural network / Norhasnelly Anuar by Anuar, Norhasnelly

“…A lot of efforts have been made to investigate methodologies to form optimal efficiency in determining typical load profiles (TLPs), derived from various clustering and classification techniques. …”
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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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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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Power system security assessment using artificial neural network: article / Mohd Fathi Zakaria by Zakaria, Mohd Fathi

“…This paper presented an application of Artificial Neural Network (ANN) in steady state stability classifications. A multi layer feed forward ANN with Back Propagation Network algorithm is proposed in determining the steady state stability classifications. …”
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Spectral Estimation And Supervised Classification Technique For Real Time Electromyography Pattern Recognition by Burhan, Nuradebah

“…Electromyography (EMG) signal is a biomedical signal which measures physical activity of human muscle.It has been acknowledged to be widely used in rehabilitation or recovery application system assisting physiotherapist to monitor a patient’s physical strength,function,motion and overall well-being by addressing the underlying physical issues.In application system associated with rehabilitation,a signal processing and classification techniques are implemented to classify EMG signal obtained.For real time application in the rehabilitation, the classification is crucial issue.The success of the signal classification depends on the selection of the features that represent a raw EMG signal in the signal processing.Therefore,a robust and resilient denoising method and spectral estimation technique have been acknowledged as necessary to distinguish and detect the EMG pattern.The present study was undertaken to determine the characteristic of EMG features using denoising method and spectral estimation technique for assessing the EMG pattern based on a supervised classification algorithm.In the study,the combination of time-frequency domain (TFD) and time domain (TD) were identified as the preferred denoising method and spectral estimation techniques.In the first part of study, the recorded EMG signal filtered the contaminated noise by using wavelet transform (WT) approach which implemented discrete wavelet transform (DWT) method of the wavelet-denoising signal. …”
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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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Ganoderma boninense classification based on near-infrared spectral data using machine learning techniques by Mas Ira Syafila, Mohd Hilmi Tan, Mohd Faizal, Jamlos, Ahmad Fairuz, Omar, Kamarulzaman, Kamarudin, Mohd Aminudin, Jamlos

“…The result represents a significant step in the development of a nondestructive and in-situ detection system which validated by both chemometric and machine learning (ML) classification techniques…”
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Decision tree-based approach for online management of PEM fuel cells for residential application by Mohd Rusllim, Mohamed

“…The main idea is to employ a classification technique, trained on a sufficient subset of data, to produce an estimate of the optimal setting without repeating the optimization process. …”
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Electricity Anomaly Point Detection using Unsupervised Technique Based on Electricity Load Prediction Derived from Long Short-Term Memory by Salleh N.S.M., Saripuddin M., Suliman A., Jorgensen B.N.

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

“…Lastly another deep sort algorithm is utilized to keep track of the detected vehicles and count them accordingly. …”
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Decision tree-based approach for online management of pem fuel cells for residential application by Mohamed, Mohd Rusllim

“…The main idea was to employ a classification technique, trained on a sufficient subset of data, to produce an estimate of the optimal setting without repeating the optimization process. …”
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Detection And Classification Of Impact-Induced Delamination In Fiberglass Pre-Impregnated Laminated Composites From Ultrasonic A-Scan Signal Using Artificial Intelligence by Mahmod, Muhammad Faisal

“…This technique is not suitable as the damage caused by the impact normally occurred by accident at random location. …”
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Distinguishing Micro-Scale Voltage Disturbances Using Wavelet Decomposition Techniques by Wan, Chen Yoong

“…All the modelling and classification processes are performed in MATLAB where wavelet-1D toolbox and MATLAB algorithm are developed and employed. …”
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An overview to chip-based power transistor and prognostics techniques / Muhamad Hazwan Abdul Halim … [et al.] by Abdul Halim, Muhamad Hazwan, Buniyamin, Norlida, N., Naoe, A., Imazawa, Rosman, M. Syafiq

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An Implementation Framework Overview of Non-Intrusive Load Monitoring by Omar Al-Khadher, Azharudin Mukhtaruddin, Fakroul Ridzuan Hashim, Hussin Mamat, Muhammad Mokhzaini Azizan

Delamination in fiberglass pre-impregnated laminated composites from ultrasonic a-scan signal using artificial intelligence by Mahmod, Muhammad Faisal

“…This technique is not suitable as the damage caused by the impact normally occurred by accident at random location. …”
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Distribution network fault section estimation using analytical database approach by Mokhtar, Ahmad Safawi

“…Database search and comparison algorithms were developed to identify the faulty section fix the network. …”
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Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan by Meisam , Gordan

“…In the modeling phase, amongst all DM algorithms, the applicability of machine learning, artificial intelligence and statistical data mining techniques were examined using Support Vector Machine (SVM), Artificial Neural Network (ANN) and Classification and Regression Tree (CART) to detect the hidden patterns in vibration data. …”
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Microgrid control methods toward achieving sustainable energy management by Roslan M.F., Hannan M.A., Ker P.J., Uddin M.N.

An automated multimodal white matter hyperintensities identification in MRI brain images using image processing / Iza Sazanita Isa by Isa, Iza Sazanita

“…The first stage is preprocessing procedure that combines the thresholding and filtering algorithm for pre processing the MRI images while the second stage contains two phases of main processing techniques of enhancement and segmentation. …”
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