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A multi-depot vehicle routing problem with stochastic road capacity and reduced two-stage stochastic integer linear programming models for rollout algorithm by Anuar, Wadi Khalid, Lee, Lai Soon, Seow, Hsin Vonn, Pickl, Stefan

“…A matheuristic approach based on a reduced two-stage Stochastic Integer Linear Programming (SILP) model is presented. The proposed approach is suitable for obtaining a policy constructed dynamically on the go during the rollout algorithm. …”
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Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof by Yusof, Yusman

“…From the reviews, it is evident that autonomous system is set to handle finite number of encountered states using finite sequences of actions. In order to learn the optimized states-action policy the self-learning algorithm is developed using hybrid AI algorithm by combining unsupervised weightless neural network, which employs AUTOWiSARD and reinforcement learning algorithm, which employs Q-learning. …”
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Object-Oriented Programming semantics representation utilizing agents by Mohd Aris, Teh Noranis

“…The problem occurs during the transition from learning fundamental programming language concept to OOP concept. …”
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Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process by Ali Al-Assadi, Hayder M. A.

“…Artificial Neural Network (ANN) was selected from Machine Learning Algorithms to be the learning algorithm. …”
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Assessment of using EZ-Prog: an easy color schematic model for programming problem solving by Siti Nordianah Hai Hom, Hasnul Hadi Ibrahim, Abrizah Ibrahim, Mudiana Mokhsin, Corrienna Abdul Talib

“…The implications of this study indicate that EZ-Prog can be used in learning and teaching algorithms, especially programming problems. …”
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Optimal water supply reservoir operation by leveraging the meta-heuristic Harris Hawks algorithms and opposite based learning technique by Lai V., Huang Y.F., Koo C.H., Ahmed A.N., Sherif M., El-Shafie A.

“…To ease water scarcity, dynamic programming, stochastic dynamic programming, and heuristic algorithms have been applied to solve problem matters related to water resources. …”

Implementation of Health Monitoring System for Patients using Machine Learning Algorithms by Hariprasad, U.S., UshaSree, R.

“…We employed the Decision Tree Algorithm to train and assess a model that produced a perfection of 66.66%.…”
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Machine Learning in accounting: an introduction / Wan Mardyatul Miza Wan Tahir and Jaízah Abdul Jabar by Wan Tahir, Wan Mardyatul Miza, Abdul Jabar, Jaízah

“…Machine Learning is an application of Artificial Intelligence (AI) in which computers use algorithms to learn and recognise patterns. …”
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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

“…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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A review of classification techniques for electromyography signals by Mohd Saad, Norhashimah, Omar, Siti Nashayu, Abdullah, Abdul Rahim, Shair, Ezreen Farina, H.Rashid

“…Machine Learning (ML) is an area of Artificial Intelligent (AI) with a concept that a computer program can learn and familiarize to new data without human intervention. …”
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Collision prediction based genetic network programming-reinforcement learning for mobile robot navigation in unknown dynamic environments by Findi, Ahmed H. M., Marhaban, Mohammad Hamiruce, Raja Ahmad, Raja Mohd Kamil, Hassan, Mohd Khair

“…The problem of determining a smooth and collision-free path with maximum possible speed for a Mobile Robot (MR) which is chasing a moving target in a dynamic environment is addressed in this paper. Genetic Network Programming with Reinforcement Learning (GNP-RL) has several important features over other evolutionary algorithms such as it combines offline and online learning on the one hand, and it combines diversified and intensified search on the other hand, but it was used in solving the problem of MR navigation in static environment only. …”
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Machine Learning in Sports: Identifying Potential Archers by Rabiu Muazu, Musa, Zahari, Taha, Anwar, P. P. Abdul Majeed, Mohamad Razali, Abdullah

“…This book is valuable for coaches and managers in identifying potential archers during talent identification programs.​…”
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Pattern extraction for programming performance evaluation using directed apriori by Mohamad Mohsin, Mohamad Farhan, Zaiyadi, Mohd Fairuz, Md Norwawi, Norita, Abd Wahab, Mohd Helmy

“…Several researches indicated that there are many factors which can affect student programming performance.Thus, the objective of this paper is to investigate the significant factors that may influence students programming performance using information from previous student performance.Since data mining data analysis able to discover hidden knowledge in database, a programming dataset which comprises information about performance profile of Bachelor of Information Technology students of Faculty of IT, Universiti Utara Malaysia in the year 2004-2005 were explored using data mining technique.The dataset consists of 421 records with 70 mixture type of attributes were pre-processed and then mined using directed association rule (AR) mining algorithm namely apriori.The result indicated that the student who has a programming experience in advanced before starts learn programming in university and scored well in Mathematics and English subject during SPM were among the factor that contributes to a good programming grades.…”
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An investigation into influence factor of student programming grade using association rule mining by Mohamad Mohsin, Mohamad Farhan, Abd Wahab, Mohd Helmy, Zaiyadi, Mohd Fairuz, Hibadullah, Cik Fazilah

“…This finding can be a guideline to the faculty to plan a teaching and learning program for new registered student.…”
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Examining the potential of machine learning for predicting academic achievement: A systematic review by Nazir, M., Noraziah, Ahmad, Rahmah, M., Sharma, Aditi

“…Predicting student academic performance is a critical area of education research. Machine learning (ML) algorithms have gained significant popularity in recent years. …”
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Examining the potential of machine learning for predicting academic achievement: A systematic review by Nazir, M., Noraziah, Ahmad, Rahmah, M., Sharma, Aditi

“…Predicting student academic performance is a critical area of education research. Machine learning (ML) algorithms have gained significant popularity in recent years. …”
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An ensemble deep learning classifier stacked with fuzzy ARTMAP for malware detection by Shing, Chiang Tan, Mohammed Al-Andoli, Mohammed Nasser, Kok, Swee Lim, Pey, Yun Goh, Chee, Peng Lim

“…However, legacy anti-malware methods are confronted with millions of potential malicious programs. To combat these threats, intelligent anti-malware systems utilizing machine learning (ML) models are useful. …”
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Implementing case-based reasoning approach to framework documentation by Hajar M.J., Lee S.P.

Predicting Post-Internship Employability Using Ensemble Machine Learning Approach by Aiza Azlin, Kahlik, Abdulrazak Yahya, Saleh

“…Employing a machine learning approach on a dataset comprising student records from Universiti Malaysia Sarawak spanning from 2019 to 2021, we compared the performance of various algorithms, including ensemble methods. …”
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Simulation on Emotion Recognition for Autism Therapy by Adzmi, Muhammad Azrin

“…This paper mainly focusing on the simulation of emotion recognition software based on the Local Binary Pattern (LBP) algorithm to extract the features from the image. The program will be used by the therapist during therapy session with the autism child in order to create more exciting environment for them to learn about the classification of basic human emotions with the help of human-computer interaction. …”
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