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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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An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM) by Shamim, Akhtar

“…This study recommends a selection trade-off as the function of prediction efficiency and efficacy of the algorithm. Particularly, the proposed optimized Bagged Trees are the most effective algorithm for energy demand prediction applications, and the proposed optimized Medium Trees are the most efficient algorithm for real-time systems. …”
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Enhanced convergence of Bat Algorithm based on dimensional and inertia weight factor by Ramli, Mohamad Raziff, Abal Abas, Zuraida, Desa, Mohammad Ishak, Zainal Abidin, Zaheera, Al Azzam, Malik Bader Hasan

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Decision tree-based approach for online management of PEM fuel cells for residential application by Mohd Rusllim, Mohamed

“…In this research, a Decision Tree (DT) algorithm is employed to obtain the optimal, or quasioptimal, settings of the fuel cell online and in a general framework. …”
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Decision tree-based approach for online management of pem fuel cells for residential application by Mohamed, Mohd Rusllim

“…In this research, a Decision Tree (DT) algorithm was employed to obtain the optimal, or quasi-optimal, settings of the fuel cell online and in a general framework. …”
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Cyberbullying detection: a machine learning approach by Yeong, Su Yen

“…The machine learning algorithm, Support Vector Machine was chosen after comparing it with other algorithms such as Multinomial Naïve Bayes, Decision Tree Classifier, and Random Forest Classifier. …”
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Driver behaviour classification: a research using OBD-II data and machine learning by Muhamad Fadzil, Nur Farisya Aqilah, Mohd Fadzir, Hilda, Mansor, Hafizah, Rahardja, Untung

“…The relationship between all features and engine speed is analysed to select the optimal features, which include engine speed, vehicle speed, throttle position, and calculated engine load. Then, the proposed model makes use of the K-Means algorithm to create driving behaviour labels whether belong to safe or aggressive - validated by the safety score criteria. …”
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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

“…A PLS regression is used on NIR spectra to implement the prediction of ergosterol concentration which shows good corelation of R = 0.861 between the ergosterol concentration and oil palm NIR spectra. Four different ML algorithms are tested for prediction of G. boninense infection: K-Nearest Neighbour (kNN), Naïve Bayes (NB), Support Vector Machine (SVM) and Decision Tree (DT) are tested which depicted DT algorithm achieves a satisfactory overall performance with high accuracy up to 93.1% and F1-score of 92.6% compared to other algorithms. …”
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Parametric modelling of a TRMS using dynamic spread factor particle swarm optimisation by Toha, Siti Fauziah, Abd Latiff, I., Mohamad, M., Tokhi, M Osman

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Local search manoeuvres recruitment in the bees algorithm by Muhamad, Zaidi, Mahmuddin, Massudi, Nasrudin, Mohammad Faidzul, Sahran, Shahnorbanun

“…Swarm intelligence of honey bees had motivated many bioinspired based optimisation techniques. The Bees Algorithm (BA) was created specifically by mimicking the foraging behavior of foraging bees in searching for food sources.During the searching, the original BA ignores the possibilities of the recruits being lost during the flying.The BA algorithm can become closer to the nature foraging behavior of bees by taking account of this phenomenon.This paper proposes an enhanced BA which adds a neighbourhood search parameter which we called as the Local Search Manoeuvres (LSM) recruitment factor.The parameter controls the possibilities of a bee extends its neighbourhood searching area in certain direction.The aim of LSM recruitment is to decrease the number of searching iteration in solving optimization problems that have high dimensions.The experiment results on several benchmark functions show that the BA with LSM performs better compared to the one with basic recruitment.…”
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Unit commitment in power system using multi-agent evolutionary programming incorporating priority listing optimisation technique / Muhammad Nazree Che Othman by Che Othman, Muhammad Nazree

“…The search process then being refined using heuristic EP-based algorithm with multi-agent approach to produce the final solution. …”
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Handover Parameter for Self-optimisation in 6g Mobile Networks: A Survey by Ukasyah Mahamod, Ibraheem Shayea, Hafizal Mohamad, Marinah Othman, Fauzun Abdullah Asuhaimi

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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Modeling purchase intention towards edible bird's nest products among Malaysians by Mohamad Shukri, Nurul Nabilah Huda, Mohd Nawi, Nolila, Abdullah, Amin Mahir, Man, Norsida

“…The three popular classification algorithms from predictive models which are decision tree, logistic regression, and artificial neural network will be used to analyze the dataset and determined the best model building. …”
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Instance matching framework for heterogeneous semantic web content over linked data environment by Mansir, Abubakar

“…These discovered attributes serve as input to a modified training set generation component, where training sets are generated based on the potential attributes’ clusters. Property alignment check the irregular data associated to the generated sets to optimise the matching performance. …”
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Gravitational energy harvesting system based on multistage braking technique for multilevel elevated car parking building by Al Kubaisi, Yasir Mahmood

“…Applying a methodology based on three basic aspects; Firstly, designing a (GEH) structure of a scaled-down prototype for the actual system describing the mechanism of the energy harvesting, which is inspired by the elevator structures. …”
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Abnormal event detection in video surveillance / Lim Mei Kuan by Lim, Mei Kuan

“…Therefore, by considering tracking as an optimisation problem, the proposed SwATrack algorithm searches for the optimal distribution of motion model without making prior assumptions, or prior learning of the motion model. …”
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