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  1. 1
    Improved voting technique for ensemble of MLP system applied on various classification data / Saodah Omar, Iza Sazanita Isa and Junita Mohd Saleh.

    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

    Published 2010
    “…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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  2. 2
    Secure E-Voting With Blind Signature

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

    Published 2003
    “…We have developed an electronic voting system, E-Voting for a general election. …”
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  3. 3
    Classification of Mental Health Level of Students Using SMOTE and Soft Voting Ensemble Classifier and the DASS-21 Profile

    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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  4. 4
    A voting-based hybrid machine learning approach for fraudulent financial data classification / Kuldeep Kaur Ragbir Singh

    A voting-based hybrid machine learning approach for fraudulent financial data classification / Kuldeep Kaur Ragbir Singh by Kuldeep Kaur , Ragbir Singh

    Published 2019
    “…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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  5. 5
    An improved multiple classifier combination scheme for pattern classification

    An improved multiple classifier combination scheme for pattern classification by Abdullah,

    Published 2015
    “…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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  6. 6
    Ant system and weighted voting method for multiple classifier systems

    Ant system and weighted voting method for multiple classifier systems by Husin, Abdullah, Ku-Mahamud, Ku Ruhana

    Published 2018
    “…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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  7. 7
    Making programmer effective for software development teams: An extended study

    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.

    Published 2017
    “…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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  8. 8
    Nearest neighbour group-based classification

    Nearest neighbour group-based classification by Samsudin, Noor A., Bradley, Andrew P.

    Published 2010
    “…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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  9. 9
    TOPSIS-based Regression Algorithms Evaluation

    TOPSIS-based Regression Algorithms Evaluation by Abu-Shareha, Ahmad Adel

    Published 2022
    “…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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  10. 10
    Development of a PMV-based thermal comfort modelling

    Development of a PMV-based thermal comfort modelling by Shazmin Aniza, Abdul Shukor, Karl Kohlhof, Zul Azhar, Zahid Jamal

    Published 2009
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  11. 11
    Investigation And Development Of Forensic Mean-Based Adaptive Background Correction Algorithm (Mabca) For Visual Enhancement Of Bloodstains, Seminal Stains And Fingerprints

    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

    Published 2017
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  12. 12
    Smart thermal comfort system: a development of the fundamental control algorithm

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

    Published 2004
    “…This paper reports on the development of the fundamental algorithm for a smart thermal comfort system. …”
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  13. 13
    Smart thermal comfort system: a development of the fundamental control algorithm

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

    Published 2004
    “…This paper reports on the development of the fundamental algorithm for a smart thermal comfort system. …”
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  14. 14
    Dynamic linear programming model for quarterly budget allocation and execution / Rossidah Wan Abdul Aziz

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

    Published 2019
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  15. 15
    Hotel recommendation system using machine learning

    Hotel recommendation system using machine learning by Wong, Wai On

    Published 2025
    “…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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  16. 16
    The new efficient and accurate attribute-oriented clustering algorithms for categorical data

    The new efficient and accurate attribute-oriented clustering algorithms for categorical data by Qin, Hongwu

    Published 2012
    “…IG-ANMI algorithm improves G-ANMI by developing a new attribute-oriented initialization method in which part of initial chromosomes is generated by using the attributes partitions. …”
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  17. 17
    Influence maximisation towards target users and minimal diffusion of information based on information needs

    Influence maximisation towards target users and minimal diffusion of information based on information needs by Temitope, Olanrewaju Abdus-Samad

    Published 2020
    “…This study proposes the Information Diffusion towards Target Users (IDTU) algorithm to enhance influencer selection while minimizing the DC. …”
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  18. 18
    Design and development of fanger model and fuzzy logic based controller for air conditioners

    Design and development of fanger model and fuzzy logic based controller for air conditioners by Kee, Keh-Kim, Angelo Emanuel Robin, Pao, William K.S

    Published 2019
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  19. 19
    A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani

    A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani by Mahmoud Reza, Saybani

    Published 2016
    “…The increasing size of data being stored have created the need for computer-based methods for automatic data analysis. Many researchers, who have developed methods and algorithms within the field of artificial intelligence, machine learning and data mining, have addressed extracting useful information from the data. …”
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  20. 20
    Developing an ensembled machine learning prediction model for marine fish and aquaculture production

    Developing an ensembled machine learning prediction model for marine fish and aquaculture production by Rahman L.F., Marufuzzaman M., Alam L., Bari M.A., Sumaila U.R., Sidek L.M.

    Published 2023
    “…Finally, an ensemble approach named voting regression combines those three ML models. …”
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