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Improved voting technique for ensemble of MLP system applied on various classification data / Saodah Omar, Iza Sazanita Isa and Junita Mohd Saleh. by Omar, Saodah, Isa, Iza Sazanita, Mohd Saleh, Junita

“…The work employs MATLAB Neural Network Toolbox and Borland C++ programming language as the tools to develop the proposed system. The MLP networks are trained using two types of learning algorithm, which are the Levenberg Marquardt and the Resilient Back Propagation algorithms. …”
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Ant colony optimization algorithm for load balancing in grid computing by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

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Secure E-Voting With Blind Signature by Ibrahim, Subariah, Kamat, Maznah, Salleh, Mazleena, Abdul Aziz, Shah Rizan

“…We have developed an electronic voting system, E-Voting for a general election. …”
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Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

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Resource management in grid computing using ant colony optimization by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

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Dynamic force-directed graph with weighted nodes for scholar network visualization by Mohd. Aris, Khalid Al-Walid, Ramasamy, Chitra, Mohd Aris, Teh Noranis, Zolkepli, Maslina

“…The approach is realized by creating a web-based interface using D3 JavaScript algorithm that allows the visualization to focus on how data are connected to each other more accurately than the conventional lines of data seen in traditional data representation. …”
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Classification of Mental Health Level of Students Using SMOTE and Soft Voting Ensemble Classifier and the DASS-21 Profile by Muhammad Imron, Rosadi, Khoirun, Nisa, Nanik, Kholifah

“…It leverages the Synthetic Minority Over-sampling Technique (SMOTE) to address the class imbalance in the dataset and employs a Voting Ensemble with soft voting to combine several base algorithms (Logistic Regression, Random Forest, Gradient Boosting, and XGBoost/SVM) for accurate prediction of mental health levels (normal, mild, moderate, severe, very severe). …”
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A voting-based hybrid machine learning approach for fraudulent financial data classification / Kuldeep Kaur Ragbir Singh by Kuldeep Kaur , Ragbir Singh

“…The voting-based hybrid approach consisting of various machine learning models with the ability to tackle issues related to missing and imbalanced data is then developed. …”
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An improved multiple classifier combination scheme for pattern classification by Abdullah,

“…The ant system (AS) algorithm is used to partition feature set in developing feature subsets which represent the number of classifiers. …”
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Ant system and weighted voting method for multiple classifier systems by Husin, Abdullah, Ku-Mahamud, Ku Ruhana

“…A diverse classifier ensemble is constructed by training them with different feature set partitions. The ant system-based algorithm is used to form the optimal feature set partitions. …”
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Making programmer effective for software development teams: An extended study by Gilal, A.R., Jaafar, J., Abro, A., Umrani, W.A., Basri, S., Omar, M.

“…Results emanated from training experiments were validated with Standard Voting (SV), Voting with Object tracking, and Naïve Bayes classification techniques based on prediction accuracy. …”
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Nearest neighbour group-based classification by Samsudin, Noor A., Bradley, Andrew P.

“…In this paper, we extend three variants of the nearest neighbour algorithm to develop a number of non-parametric group-based classification techniques. …”
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TOPSIS-based Regression Algorithms Evaluation by Abu-Shareha, Ahmad Adel

“…Following that, using three datasets, namely Combined Cycle Power Plant, Real Estate, and Concrete, Voting using multiple classifiers (k-means-based classifiers) was the top-ranked in the Combined Cycle Power Plant and Real Estate datasets. …”
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Development of a PMV-based thermal comfort modelling by Shazmin Aniza, Abdul Shukor, Karl Kohlhof, Zul Azhar, Zahid Jamal

Investigation And Development Of Forensic Mean-Based Adaptive Background Correction Algorithm (Mabca) For Visual Enhancement Of Bloodstains, Seminal Stains And Fingerprints by Lee, Wee Chuen

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Smart thermal comfort system: a development of the fundamental control algorithm by Abdul Shukor, Shazmin Aniza

“…This paper reports on the development of the fundamental algorithm for a smart thermal comfort system. …”
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Smart thermal comfort system: a development of the fundamental control algorithm by Abdul Shukor, Shazmin Aniza

“…This paper reports on the development of the fundamental algorithm for a smart thermal comfort system. …”
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Constrained clustering approach to aid in remodularisation of object-oriented software systems / Chong Chun Yong by Chong, Chun Yong

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Dynamic linear programming model for quarterly budget allocation and execution / Rossidah Wan Abdul Aziz by Wan Abdul Aziz, Rossidah

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Hotel recommendation system using machine learning by Wong, Wai On

“…There are three objectives in the study, which is to perform data preprocessing on the Google Reviews dataset for hotels in Perak using an instant data scraper, to develop three suitable machine learning models on the cleaned dataset and evaluate their performance, and to propose a recommendation system based on the developed machine learning models. …”
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