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  1. 1
    Predicting future sales using genetic algorithm: data mining sales / Siti Hajar Yaacob

    Predicting future sales using genetic algorithm: data mining sales / Siti Hajar Yaacob by Yaacob, Siti Hajar

    Published 2014
    “…Tool decision tree calculate the stock based on the number of product order. This research using Simple Genetic Algorithm which is involved crossover and fitness. …”
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  2. 2
    A Rough-Apriori Technique in Mining Linguistic Association Rules

    A Rough-Apriori Technique in Mining Linguistic Association Rules by Choo, Yun Huoy, Abu Bakar, Azuraliza, Hamdan, Abdul Razak

    Published 2008
    “…It uses the rough membership function to capture the linguistic interval before implementing the Apriori algorithm to mine interesting association rules. …”
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  3. 3
    A partition based feature selection approach for mixed data clustering / Ashish Dutt

    A partition based feature selection approach for mixed data clustering / Ashish Dutt by Ashish , Dutt

    Published 2020
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  4. 4
    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
    “…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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  5. 5
    Intelligent transmission line fault diagnosis using the Apriori associated rule algorithm under cloud computing environment

    Intelligent transmission line fault diagnosis using the Apriori associated rule algorithm under cloud computing environment by Al-Jumaili A.H.A., Muniyandi R.C., Hasan M.K., Singh M.J., Paw J.K.S.

    Published 2024
    “…In this paper, the optimised Apriori association rule algorithm is used as technical support to realise the function of interlocking fault diagnosis in the intelligent fault diagnosis system module. …”
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  6. 6
    Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model

    Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model by Sulaiman, Md. Nasir, Mohamed, Raihani, Mustapha, Norwati, Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…Expectation maximization (EM) is one of the representatives clustering algorithms which have broadly applied in solving classification problems by improving the density of data using the probability density function. …”
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  7. 7
    RMIL/AG: A new class of nonlinear conjugate gradient for training back propagation algorithm

    RMIL/AG: A new class of nonlinear conjugate gradient for training back propagation algorithm by Basri, S.M.M., Nawi, N.M., Mamat, M., Hamid, N.A.

    Published 2018
    “…This paper introduced a new class of efficient second order conjugate gradient (CG) for training BP called Rivaie, Mustafa, Ismail and Leong (RMIL)/AG. The RMIL uses the value of adaptive gain parameter in the activation function to modify the gradient based search direction. …”
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  8. 8
    Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.

    Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

    Published 2005
    “…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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  9. 9
    Framework for stream clustering of trajectories based on temporal micro clustering technique

    Framework for stream clustering of trajectories based on temporal micro clustering technique by Abdulrazzaq, Musaab Riyadh

    Published 2018
    “…In the preprocessing stage, the On-Line Noise Filtering Algorithm for Trajectory Segmentation Based on Minimum Description Length concept (ONF_TRS) is proposed to achieve trajectory segmentation and remove noise points in real time with low computational cost. …”
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  10. 10
    The Parallel Fuzzy C-Median Clustering Algorithm Using Spark for the Big Data

    The Parallel Fuzzy C-Median Clustering Algorithm Using Spark for the Big Data by Mallik, Moksud Alam, Zulkurnain, Nurul Fariza, Siddiqui, Sumrana, Sarkar, Rashel

    Published 2024
    “…Therefore, we develop a Parallel Fuzzy C-Median Clustering Algorithm Using Spark for Big Data that can handle large datasets while maintaining high accuracy and scalability. …”
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  11. 11
    Seed disperser ant algorithm for optimization / Chang Wen Liang

    Seed disperser ant algorithm for optimization / Chang Wen Liang by Chang , Wen Liang

    Published 2018
    “…The classical benchmark problems and composite benchmark functions from Congress on Evolutionary Computation (CEC) 2005 special session is used for validate SDAA. …”
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  12. 12
    Arabic text classification using hybrid feature selection method using chi-square binary artificial bee colony algorithm

    Arabic text classification using hybrid feature selection method using chi-square binary artificial bee colony algorithm by Hijazi, Musab, Zeki, Akram M., Ismail, Amelia Ritahani

    Published 2021
    “…After that, the wrapper method, Artificial Bee Colony algorithm, is used as the second level where Naive Base is used as a fitness function. …”
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  13. 13
    Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool

    Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool by Nurshafiqa Saffah, Mohd Sharif

    Published 2018
    “…Classification and prediction are the functions provided by the data mining techniques that suit in EEG signal processing. …”
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  14. 14
    Discretization of integrated moment invariants for writer identification

    Discretization of integrated moment invariants for writer identification by Draman @ Muda, Azah Kamilah, Shamsuddin, Siti Maryam, Darus, Maslina

    Published 2008
    “…Conservative regular moments have been proven to exhibit some shortcomings in the original formulations of moment functions in terms of scaling factor. Hence, an incorporated scaling factor of geometric functions into United Moment Invariant function is proposed for mining the feature of unconstrained words. …”
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  15. 15
    Comparative analysis for topic classification in juz Al-Baqarah

    Comparative analysis for topic classification in juz Al-Baqarah by Rahman, Mohamad Izzuddin, Samsudin, Noor Azah, Mustapha, Aida, Abdullahi Oyekunle, Adeleke

    Published 2018
    “…This research project is aiming to create computing environment that enable us use to text mining the Quran. …”
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  16. 16
    The discovery of Top-K DNA frequent patterns with approximate method / Nittaya Kerdprasop and Kittisak Kerdprasop

    The discovery of Top-K DNA frequent patterns with approximate method / Nittaya Kerdprasop and Kittisak Kerdprasop by Kerdprasop, Nittaya, Kerdprasop, Kittisak

    Published 2014
    “…These representatives are subsequently used in the main process of frequent pattern mining. …”
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  17. 17
    Density based subspace clustering: a case study on perception of the required skill

    Density based subspace clustering: a case study on perception of the required skill by Rahmat Widia, Sembiring

    Published 2014
    “…In the early stage, the present research estimates density dimensions and the results are used as input data to determine the initial cluster based on density connection, using DBSCAN algorithm. …”
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  18. 18
    Density subspace clustering: a case study on perception of the required skill

    Density subspace clustering: a case study on perception of the required skill by Sembiring, Rahmat Widia

    Published 2014
    “…In the early stage, the present research estimates density dimensions and the results are used as input data to determine the initial cluster based on density connection, using DBSCAN algorithm. …”
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  19. 19
    Deviation detection in text using conceptual graph interchange format and error tolerance dissimilarity function

    Deviation detection in text using conceptual graph interchange format and error tolerance dissimilarity function by Kamaruddin, Siti Sakira, Hamdan, Abdul Razak, Abu Bakar, Azuraliza, Mat Nor, Fauzias

    Published 2012
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  20. 20
    Named entity recognition using a new fuzzy support vector machine.

    Named entity recognition using a new fuzzy support vector machine. by Mansouri, Alireza, Affendy, Lilly Suriani, Mamat, Ali

    Published 2008
    “…Nowadays more researchers use three type of approaches namely, Rule-base NER, Machine Learning-base NER and Hybrid NER to identify names. …”
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