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  1. 1
    Development of mobile location based notification for crime cases tracking as an alternative alert for public safety / Noraini Ismail

    Development of mobile location based notification for crime cases tracking as an alternative alert for public safety / Noraini Ismail by Ismail, Noraini

    Published 2014
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  2. 2
    Group formation using genetic algorithm

    Group formation using genetic algorithm by Che Ani, Zhamri, Husin, Mohd Zabidin, Yasin, Azman

    Published 2009
    “…However, due to lack of programming skills especially in Java programming language and the inability to have meetings frequently among the group members,most of the students’ software project cannot be delivered successfully.To solve this problem, systematic group formation is one of the initial factors that should be considered to ensure that every group consists of quality individuals who are good in Java programming and also to ensure that every group member in a group are staying closer to each other.In this research, we propose a method for group formation using Genetic Algorithms, where the members for each group will be generated based on the students’ programming skill and location of residential colleges.…”
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  3. 3
    Multi-floor indoor location estimation system based on wireless local area network

    Multi-floor indoor location estimation system based on wireless local area network by Chua, Tien Han

    Published 2007
    “…The most probable match is selected and returned as estimated location based on Bayesian filtering algorithm. Estimated location is reported as physical location and symbolic location. …”
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  4. 4
    Traveler’s recommendation mobile based system around Terengganu / Muhammad Aiman Syakir Shamsudin

    Traveler’s recommendation mobile based system around Terengganu / Muhammad Aiman Syakir Shamsudin by Shamsudin, Muhammad Aiman Syakir

    Published 2021
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  5. 5
    Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms

    Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

    Published 2005
    “…In cluster generating process, the developed BBSI algorithm was used to select the best band combination for generating cluster by using Iterative self- Organizing Data Analysis (ISODATA) technique. …”
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  6. 6
    Neural Networks Ensemble: Evaluation of Aggregation Algorithms for Forecasting

    Neural Networks Ensemble: Evaluation of Aggregation Algorithms for Forecasting by HASSAN, SAIMA

    Published 2013
    “…These algorithms include equal�weights combination of Best NN models, combination of trimmed forecasts, combination through Variance-Covariance method and Bayesian Model Averaging. …”
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  7. 7
    Group method of data handling with artificial bee colony in combining forecasts

    Group method of data handling with artificial bee colony in combining forecasts by Yahya, Nurhaziyatul Adawiyah, Samsudin, Ruhaidah, Darmawan, Irfan, Kasim, Shahreen

    Published 2018
    “…This study is done by combining individual forecasts of Group Method of Data Handling models using the weighted-based combine approach. …”
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  8. 8
    An efficient secure ECG compression based on 2D-SPIHT and SIT algorithm

    An efficient secure ECG compression based on 2D-SPIHT and SIT algorithm by Jati, Grafika, Rachmasari, Ardina Rizqy, Jatmiko, Wisnu, Mursanto, Petrus, Sediono, Wahju

    Published 2017
    “…This research proposes an efficient combination of a compression and an encryption algorithms. …”
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    Proceeding Paper
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  9. 9
    Ideal combination feature selection model for classification problem based on bio-inspired approach

    Ideal combination feature selection model for classification problem based on bio-inspired approach by Basir, Mohammad Aizat, Hussin, Mohamed Saifullah, Yusof, Yuhanis

    Published 2020
    “…The important step is to idealize the combined feature selection models by finding the best combination of search method and feature selection algorithms. …”
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    Book Section
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  10. 10
    A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat

    A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat by Sakamat, Norzehan

    Published 2021
    “…The combined method is called Hybrid K-MeansCGA. Modifications of K-Means structures were done by inserting genetic algorithm operators and tuning the population. …”
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  11. 11
    Technical job distribution at BSD SHARP service center using combination of naïve Bayes and K-Nearest neighbour

    Technical job distribution at BSD SHARP service center using combination of naïve Bayes and K-Nearest neighbour by Pebrianti, Dwi, Ariawan, Angga, Bayuaji, Luhur, Mahdiana, Deni, ,, Rusdah

    Published 2022
    “…Meanwhile, k-NN algorithm is used to classify the experimental data. …”
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  12. 12
    Robust combining methods in committee neural networks

    Robust combining methods in committee neural networks by Kenari, Seyed Ali Jafari, Mashohor, Syamsiah

    Published 2011
    “…Therefore, we have used a Genetic Algorithm (GA) method to combine the individuals with the Huber and Bisquare as the fitness functions. …”
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  13. 13
    A fast and simple method of spectral enhancement

    A fast and simple method of spectral enhancement by Sajid, Muhammad, Ghosh, Deva

    Published 2014
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  14. 14
    Shape-based recognition using combined Jaccard and Mahalanobis measurement / Noor Aznimah Abdul Aziz

    Shape-based recognition using combined Jaccard and Mahalanobis measurement / Noor Aznimah Abdul Aziz by Abdul Aziz, Noor Aznimah

    Published 2013
    “…This proposed combined algorithms and techniques can achieve high performance in shape similarity measurement recognition and also the masking technique in Mahalanobis distance measurement can reduce the amount of data analysis.…”
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  15. 15
    Breast cancer disease classification using fuzzy-ID3 algorithm with FUZZYDBD method: automatic fuzzy database definition

    Breast cancer disease classification using fuzzy-ID3 algorithm with FUZZYDBD method: automatic fuzzy database definition by Nur Farahaina, Idris, Mohd Arfian, Ismail

    Published 2021
    “…FUZZYDBD method, an automatic fuzzy database definition method, would be used to design the fuzzy database for fuzzification of data in the FID3 algorithm. …”
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  16. 16
    Application of the bees algorithm to the selection features for manufacturing data

    Application of the bees algorithm to the selection features for manufacturing data by Pham, D.T, Mahmuddin, Massudi, Otri, S., Al-Jabbouli, H.

    Published 2007
    “…The proposed method has been tested on data collected in semiconductor manufacturing. …”
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  17. 17
    Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform

    Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform by Alias, Norma, Satam, Noriza, Abd. Ghaffar, Zarith Safiza, Darwis, Roziha, Hamzah, Norhafiza, Islam, Md. Rajibul

    Published 2009
    “…The development of this architecture is based on several programming language as it involves algorithm implementation on C, parallelization using Parallel Virtual Machine (PVM) and Java for web services development. …”
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  18. 18
    Ensemble Dual Recursive Learning Algorithms for Identifying Custom Tanks Flow with Leakage

    Ensemble Dual Recursive Learning Algorithms for Identifying Custom Tanks Flow with Leakage by Akib, Afifi, Saad , Nordin, Asirvadam , Vijanth Sagayan

    Published 2010
    “…The objective of this paper is to introduce a combination of advantages of different algorithm scheme into one learning algorithm. …”
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  19. 19
    Ensemble dual recursive learning algorithms for identifying flow with leakage

    Ensemble dual recursive learning algorithms for identifying flow with leakage by Akib, Afifi, Saad , Nordin, Asirvadam , Vijanth Sagayan

    Published 2010
    “…The objective of this paper is to introduce a combination of advantages of different algorithm scheme into one learning algorithm. …”
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  20. 20
    Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach

    Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach by Nurnajmin Qasrina Ann, ., Pebrianti, Dwi, Mohamad Fadhil, Abas, Bayuaji, Luhur

    Published 2022
    “…Accuracy by using 80:20 ratio of training and test data gives result 98% of accurate training data, and 73% of test data are predicted with the proposed algorithm while 91 and 40% of the DNN models are predicted in training and test data.…”
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