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High impedance fault detection and identification based on pattern recognition of phase displacement computation by Ali, Mohd Syukri, Bakar, Ab Halim Abu, Tan, Chia Kwang, Arof, Hamzah, Mokhlis, Hazlie

“…Subsequently, an automatic HIF classification algorithm based on predefined indices is proposed to perform event identification and HIF detection. …”
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Detection and classification of conflict flows in SDN using machine learning algorithms by Mutaz Hamed Hussien Khairi, Sharifah Hafizah Syed Ariffin, Nurul Mu'azzah Abdul Latiff, Kamaludin Mohamad Yusof, Mohamed Khalafalla Hassan, Fahad Taha Al-Dhief, Mosab Hamda, Suleman Khan, Muzaffar Hamzah

“…Moreover, applying machine learning algorithms in the identification and classification of conflicting flows has limitations. …”
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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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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.

“…Machine learning application have been widely used in various sector as part of reducing work load and creating an automated decision making tool. …”

Damage Identification and Assessment in Rc Structures Using Vibration Data: A Review by Fayyadh, M.M., Razak, H.A.

“…Studies on the use of modal testing for detection of damage severity and location algorithms and procedures are also presented. …”
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An automated multimodal white matter hyperintensities identification in MRI brain images using image processing / Iza Sazanita Isa by Isa, Iza Sazanita

“…In addition, this research also proposes to classify the WMH severity based on the features of segmented WMH. In the WMH classification stage, the research considered two types of WMH features of volume and intensities to classify the severity. …”
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An automated multimodal white matter hyperintensities identification in MRI brain images using image processing / Iza Sazanita Isa by Isa, Iza Sazanita

“…In addition, this research also proposes to classify the WMH severity based on the features of segmented WMH. In the WMH classification stage, the research considered two types of WMH features of volume and intensities to classify the severity. …”
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Voltage stability margin identification using evolution programming learning algorithm / Zamzuhairi Darus by Darus, Zamzuhairi

“…Voltage stability problems have been one of the major concerns for electric utilities as a result of a system heavy loading. This project proposed on an investigation on the voltage stability margin identification using evolution programming learning algorithm. …”
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Evolutionary Programming (EP) based technique for secure point identification with load shedding technique in power transmission / Abdul Rahman Minhat by Minhat, Abdul Rahman

“…Consequently, another algorithm for maximum loadability identification using EP optimization technique was also developed. …”
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Development of multi-objective load shedding optimization via back tracking search algorithm with novel reactive power tracing index by Verayiah R., Mohamed A., Shareef H., Abidin I.H.Z.

An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani by Ab Ghani, Nur Laila

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Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

“…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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An adaptive ant colony optimization algorithm for rule-based classification by Al-Behadili, Hayder Naser Khraibet

“…Ant-Miner is a variant of ant colony optimisation and a prominent intelligent algorithm widely use in rules-based classification. …”
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Classification of tropical rainforest using different classification algorithm based on remote sensing imagery: A study of Gunung Basor by Intan Noradybah Md Rodi

“…Thehighest accuracy for classification map of Gunung Basor is by using maximum likelihood algorithm with an accuracy of 82.90%. …”
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Real-time Traffic Classification Algorithm Based on Hybrid of Signature Statistical and Port to Identify Internet Applications by Hamza Awad, Hamza Ibrahim, Sulaiman, Mohd Nor, Izzeldin, I. Mohd, Mohamed Saad, Mahoub, Haitham, A. Jamil

“…In addition, as demonstrated in the real time online experiments done, SSPC algorithm uses a short time to classify traffic and thus it is suitable to be used for online classification.…”
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Daisy species classification based on image using Convolutional Neural Network algorithm / Haris Hidayatullah Khaimuza by Khaimuza, Haris Hidayatullah

“…Second objective is to develop the prototype of daisy species classification based on image using CNN algorithm. The last objective is to evaluate the accuracy of CNN model in the daisy species classification based on image. …”
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Enhanced ontology-based text classification algorithm for structurally organized documents by Oleiwi, Suha Sahib

“…The third algorithm is the Ontology Based Text Classification (OBTC) and is designed to reduce the dimensionality of training sets. …”
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Feature extraction and selection algorithm based on self adaptive ant colony system for sky image classification by Petwan, Montha

“…The performance of FESSIC was evaluated against ten benchmark image classification algorithms and six classifiers on four ground-based sky image datasets. …”
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Ant colony optimization algorithm for rule based classification: Issues and potential by Al-Behadili, Hayder Naser Khraibet, Ku-Mahamud, Ku Ruhana, Sagban, Rafid

“…Furthermore, this review can be used as a source of reference to other researchers in developing new ACO algorithms for rule classification.…”
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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

“…The comparison showed that, the accuracy of the unsupervised classification map with value of 88.4% that was generated by using the cluster labelling algorithm was slightly more than the maximum-likelihood supervised classification map with value of 87.5%. …”
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