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An optimized attack tree model for security test case planning and generation by Omotunde, Habeeb, Ibrahim, Rosziati, Ahmed, Maryam

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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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An efficient model for indoor radio signal prediction and coverage estimation / Md. Sumon Sarker by Md. Sumon, Sarker

“…BFS is used to generate the search space tree and Branch-And- Bound terminology is to avoid the unnecessary generation of the sub-tree using proposed bounding functions. …”
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Multi-objective method for divisible load scheduling in multi-level tree network by Ghanbari, Shamsollah, Othman, Mohamed, Abu Bakar, Mohd Rizam, Leong, Wah June

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Comparing the knowledge quality in rough classifier and decision tree classifier by Mohamad Mohsin, Mohamad Farhan, Abd Wahab, Mohd Helmy

“…Theoretically, different classifiers will generate different sets of rules via knowledge even though they are implemented to the same classification problem.Hence, the aim of this paper is to investigate the quality of knowledge produced by Rc and DTc when similar problems are presented to them.In this case, four important performance metrics are used as comparison, the accuracy of classification, rules quantity, rules length and rules coverage.Five dataset from UCI Machine Learning are chosen and then mined using Rc toolkit namely ROSETTA while C4.5 algorithm in WEKA application is chosen as DTc rule generator. …”
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Solar radiation prediction using boosted decision tree regression model: A case study in Malaysia by Jumin E., Basaruddin F.B., Yusoff Y.B.M., Latif S.D., Ahmed A.N.

A novel peak shaving algorithm for islanded microgrid using battery energy storage system by Uddin, Moslem, Romlie, M.F., Abdullah, M.F., Tan, Chia Kwang, Shafiullah, G.M., Bakar, Ab Halim Abu

“…The proposed algorithm helps an islanded microgrid to operate its generation units efficiently. …”
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A novel peak shaving algorithm for islanded microgrid using battery energy storage system by Uddin, M., Romlie, M.F., Abdullah, M.F., Tan, C., Shafiullah, G.M., Bakar, A.H.A.

“…The proposed algorithm helps an islanded microgrid to operate its generation units efficiently. …”
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Evaluating different machine learning models for predicting municipal solid waste generation: a case study of Malaysia by Latif S.D., Hazrin N.A.B., Younes M.K., Ahmed A.N., Elshafie A.

Real-Time Flood Inundation Map Generation Using Decision Tree Machine Learning Method: Case Study of Kelantan River Basins by Sidek L.M., Basri H., Marufuzzaman M., Deros A.M., Osman S., Hassan F.A.

A coalition model for efficient indexing in wireless sensor network with random mobility / Hazem Jihad Ali Badarneh by Hazem Jihad , Ali Badarneh

“…The proposed model consists of Dynamic-Coalition framework, Static-Coalition algorithm, and Coalition-Based Index-Tree framework. …”
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Frequent Lexicographic Algorithm for Mining Association Rules by Mustapha, Norwati

“…The experimental results showed that the proposed algorithm outperformed both existing algorithms especially for the case of long patterns. …”
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An Integrated Principal Component Analysis And Weighted Apriori-T Algorithm For Imbalanced Data Root Cause Analysis by Ong, Phaik Ling

“…On the other hand, Apriori-T with indexing enumeration tree is used for low cost FPM. A semiconductor manufacturing case study with Work In Progress data and true alarm data is used to proof the proposed algorithm. …”
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A Comparative Analysis of Peak Load Shaving Strategies for Isolated Microgrid Using Actual Data by Rana, M.M., Rahman, A., Uddin, M., Sarkar, M.R., Shezan, S.A., Ishraque, M.F., Rafin, S.M.S.H., Atef, M.

“…Actual variable load data and PV generation data are considered to conduct the simulation case studies which are col-lected from a real IMG system. …”
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Differentially expressed wound-response-related proteins from a major agarwood-producing tree, Aquilaria malaccensis Lam. identified via 2-D electrophoresis by Lee, Shiou Yih, Samsuddin, Ahmad Syazwan, Lamasudin, Dhilia Udie, Mohamed, Rozi

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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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An Intelligent System Approach to the Dynamic Hybrid Robot Control by Md. Yeasin, Md. Mahmud Hasan

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A comparative study between rough and decision tree classifiers by Mohamad Mohsin, Mohamad Farhan

“…Theoretically, a good set of knowledge should provide good accuracy when dealing with new cases.Besides accuracy, a good rule set must also has a minimum number of rules and each rule should be short as possible.It is often that a rule set contains smaller quantity of rules but they usually have more conditions.An ideal model should be able to produces fewer, shorter rule and classify new data with good accuracy.Consequently, the quality and compact knowledge will contribute manager with a good decision model.Because of that, the search for appropriate data mining approach which can provide quality knowledge is important.Rough classifier (RC) and decision tree classifier (DTC) are categorized as RBC.The purpose of this study is to investigate the capability of RC and DTC in generating quality knowledge which leads to the good accuracy.To achieve that, both classifiers are compared based on four measurements that are accuracy of the classification, the number of rule, the length of rule, and the coverage of rule.Five dataset from UCI Machine Learning namely United States Congressional Voting Records, Credit Approval, Wisconsin Diagnostic Breast Cancer, Pima Indians Diabetes Database, and Vehicle Silhouettes are chosen as data experiment.All datasets were mined using RC toolkit namely ROSETTA while C4.5 algorithm in WEKA application was chosen as DTC rule generator.The experimental results indicated that both classifiers produced good classification result and had generated quality rule in different types of model – higher accuracy, fewer rule, shorter rule, and higher coverage.In term of accuracy, RC obtained higher accuracy in average while DTC significantly generated lower number of rule than RC.In term of rule length, RC produced compact and shorter rule than DTC and the length is not significantly different.Meanwhile, RC has better coverage than DTC.Final conclusion can be decided as follows “If the user interested at a variety of rule pattern with a good accuracy and the number of rule is not important, RC is the best solution whereas if the user looks for fewer nr, DTC might be the best choice”…”
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Electricity distribution network for low and medium voltages based on evolutionary approach optimization by Hasan, Ihsan Jabbar

“…The result shows that the proposed algorithm is more cost effective and has lower power losses compare to the IEEE standard case. …”
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Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

“…There exist numerous algorithms to address the need of text categorization including Naive Bayes, k-nearest-neighbor classifier, and decision trees. …”
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