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An evolutionary based features construction methods for data summarization approach by Rayner Alfred, Suraya Alias, Chin, Kim On

“…Here, feature construction methods are applied in order to improve the descriptive accuracy of the DARA algorithm.This research proposes novel feature construction methods, called Variable Length Feature Construction without Substitution (VLFCWOS) and Variable Length Feature Construction with Substitution(VLFCWS), in order to construct a set of relevant features in learning relational data. …”
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Theory-guided machine learning for predicting and minimising surface settlement caused by the excavation of twin tunnels / Chia Yu Huat by Chia , Yu Huat

“…This dataset, alongside key parameters like cover-to-depth ratio, pillar width, soil stiffness, cohesion, friction angle, and overburden-to-face pressure ratio, integrates into a machine learning framework using a theory-guided approach. …”
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Enhancement Of Static Code Analysis Malware Detection Framework For Android Category-Based Application by Aminordin, Azmi

“…Static analysis is where the static features are examined. Too many features used, features extraction time consuming and the reliability of accuracy result by various machine learning algorithm are the main issues spotted in static analysis approach. …”
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Learning analytic framework for students’ academic performance and critical learning pathways by Lyn, Jessica Tan Yen, Goh, Yong Kheng, Lai, An Chow, Ngeow, Yoke Meng

“…The resulting reduced dataset is then subjected to various clustering algorithms, including partition-based clustering (K-means), hierarchical clustering, and density-based clustering (DBSCAN). …”
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An artificial neural network approach in service life prediction of building components in Malaysia based on local environment and building service load by Tapsir, Siti Hamisah, Mohd. Yatim, Jamaludin, Usman, Fathoni

“…The back-propagation learning algorithm is used as learning model. The environment load factors, workmanship, design, usage and level of maintenance are used as input variables in training process of the neural network model. …”
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Correlation model in the adoption of E-payment services: A machine learning approach by Tan, Xi En

“…The main goal of the project is to automate this process, by using machine learning to identify the important features. …”
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Predicting Diseases Using Multi-BackPropagation by Wan Hussain, Wan Ishak

“…Multi-network approach does not require any changes in neural network learning algorithm. …”
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A Stepper Motor Design Optimization Using by Wong, Chin Wei

“…There is a need to fill this void in the area of small-motor design, and develop a program using Genetic Algorithms (GAs) as an approach to achieve optimization. …”
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User interface and interactivity design guidelines of algorithm visualization on mobile platform by Supli, Ahmad Affandi

“…Moreover, the evaluation of the effectiveness of the AVOMP prototype from 35 participants through laboratory experiments based on the bloom taxonomy test shows that there is a significant difference between students learning sorting algorithms using the manual approach (Pre-Test) and the AVOMP app (Post-Test). …”
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A vision-based deep learning approach for non-contact vibration measurement using (2+1)D CNN and optical flow by Harold Harrison, Mazlina Mamat, Farah Wong, Hoe Tung Yew, Racheal Lim, Wan Mimi Diyana Wan Zaki

“…This paper introduces a proof-of-concept vision-based deep learning approach for vibration measurement, proposing a factorized (2+1)D Convolutional Neural Network (CNN) model to predict four vibration metrics: acceleration, velocity, displacement, and frequency, with a focus on rigid body motion. …”
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Development of an artificial neural network algorithm for predicting the cutting force in end milling of Inconel 718 alloy by Hossain, Ishtiaq, Amin, A. K. M. Nurul, Patwari, Muhammed Anayet Ullah

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A Hybrid Machine Learning and Optimisation-Based Model for Predicting the Success of Business-To-Consumer Software Development Projects in Indonesia by Setiawan, Rudi

“…Building on these findings, a predictive framework is constructed by integrating machine learning algorithms with advanced optimization and data handling strategies. …”
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Performance evaluation of hospital site suitability using multilayer perceptron MLP and analytical hierarchy process AHP models in Malacca, Malaysia by Almansi, Khaled Yousef, Mohamed Shariff, Abdul Rashid, Kalantar, Bahareh, Abdullah, Ahmad Fikri, Syed Ismail, Sharifah Norkhadijah, Ueda, Naonori

“…Identification of the most significant conditioning parameters that impact the choice of an appropriate hospital site was accomplished using correlation-based feature selection (CFS) with a search algorithm (greedy stepwise). …”
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Ant system-based feature set partitioning algorithm for classifier ensemble construction by Abdullah, , Ku-Mahamud, Ku Ruhana

“…In this study, Ant system-based feature set partitioning algorithm for classifier ensemble construction is proposed.The Ant System Algorithm is used to form an optimal feature set partition of the original training set which represents the number of classifiers.Experiments were carried out to construct several homogeneous classifier ensembles using nearest mean classifier, naive Bayes classifier, k-nearest neighbor and linear discriminant analysis as base classifier and majority voting technique as combiner. …”
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A data mining approach to construct graduates employability model in Malaysia by Sapaat, Myzatul Akmam, Mustapha, Aida, Ahmad, Johanna, Chamili, Khadijah, Muhamad, Rahamirzam

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Bayesian network of influence of sociodemographic variables on dengue related knowledge, attitude, and practices in selected areas in Selangor, Malaysia by Ajibola, Lamidi-Sarumoh Alaba

“…The data collected was used to learn the structure of BN via some known algorithms using R programming language. …”
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Design and statistical analysis of initial solution construction approach in curriculum based course timetabling problem by Wahid, Juliana, Mohd Hussin, Naimah

“…This paper investigates the construction phase approach in which the sequential order of the courses/lectures applied several combination of graph heuristics to generate a population of initial solutions in curriculum-based course timetabling (CBCTT).The construction of population of initial solution is a prerequisite in a population-based metaheuristic implementation. …”
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A Data Mining Approach to Construct Graduates Employability Model in Malaysia by Myzatul Akmam Sapaat, Aida Mustapha, Johanna Ahmad, Khadijah Chamili, Rahamirzam Muhamad

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Ant system-based feature set partitioning algorithm for K-NN and LDA ensembles construction by Abdullah, , Ku-Mahamud, Ku Ruhana

“…Combination of several classifiers has been very useful in improving the prediction accuracy and in most situations multiple classifiers perform better than single classifier.However not all combining approaches are successful at producing multiple classifiers with good classification accuracy because there is no standard resolution in constructing diverse and accurate classifier ensemble.This paper proposes ant system-based feature set partitioning algorithm in constructing k-nearest neighbor (k-NN) and linear discriminant analysis (LDA) ensembles. …”
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Harmony annealing algorithm for curriculum-based course timetabling problem by Wahid, Juliana, Mohd Hussin, Naimah

“…An attempt to solve these problems was made via an approach broken down into two parts; first, constructive algorithm with saturation degree approach was used to ensure a feasible solution, where the hard constraints are satisfied.Secondly, Harmony annealing algorithm was used to further improve the results obtained.The algorithm produced results that were not comparatively better than those previously known as best solution.With proper modification in terms of the approach in this algorithm would make the algorithm perform better on curriculum-based course timetabling.…”
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