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  1. 1
    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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  2. 2
    Image clustering comparison of two color segmentation techniques

    Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

    Published 2010
    “…Finally, the algorithm found, which would solve the image segmentation problem.…”
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  3. 3
    Data mining techniques for transformer failure prediction model: A systematic literature review

    Data mining techniques for transformer failure prediction model: A systematic literature review by Ravi N.N., Mohd Drus S., Krishnan P.S.

    Published 2023
    Conference Paper
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  4. 4
    Automatic Number Plate Recognition on android platform: With some Java code excerpts

    Automatic Number Plate Recognition on android platform: With some Java code excerpts by ., Abdul Mutholib, Gunawan, Teddy Surya, Kartiwi, Mira

    Published 2016
    “…On the other hand, the traditional algorithm using template matching only obtained 83.65% recognition rate with 0.97 second processing time. …”
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  5. 5
    Development of seven segment display recognition using TensorFlow on Raspberry Pi

    Development of seven segment display recognition using TensorFlow on Raspberry Pi by Gunawan, Teddy Surya, Mohammad Reduwan, Haque, Yaacob, Mashkuri, Mohamed Azmin, Nor Fadhillah, Ismail, Nanang, Ismail, Md Yusof, Kartiwi, Mira, A. Rahman, Azhar

    Published 2022
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  6. 6
    Facilitating resource allocation decision through Bibliomining: the case of UTM's library / Md Razib Karno

    Facilitating resource allocation decision through Bibliomining: the case of UTM's library / Md Razib Karno by Karno, Md Razib

    Published 2015
    “…(c) To study how constructed patterns and trends generate informed decisions on resource allocation for circulation function by using cluster analysis, frequency statistics, averages and aggregates and market basket analysis algorithm. This thesis highlights the finding of a research using data mining technique (CRISP-DM) to explore the potentials of the bibliographic data of an academic library. …”
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  7. 7
    Dynamic investment model for the restructed power market in the presence of wind source

    Dynamic investment model for the restructed power market in the presence of wind source by Esfahani, Mohammad Tolou Askari Sedehi

    Published 2014
    “…In the third step, the long term optimal investment strategies of the hybrid wind-thermal investor are determined based on the dynamic programming algorithm by considering the long term states of demand growth and fuel price uncertainties. …”
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  8. 8
    K Nearest Neighbor Joins And Mapreduce Process Enforcement For The Cluster Of Data Sets In Bigdata

    K Nearest Neighbor Joins And Mapreduce Process Enforcement For The Cluster Of Data Sets In Bigdata by Md Shah, Wahidah, Othman, Mohd Fairuz Iskandar, Hussian Hassan, Ali Abdul, Talib, Mohammed Saad, Mohammed, Ali Abdul Jabbar

    Published 2018
    “…K Nearest Neighbor Joins (KNN join) are regarded as highly primitive and expensive operations in the data mining.The efficient use of KNN join has proven good results in finding the objects from two data sets prevailed in the huge databases.This has been achieved with the combination of K-Nearest Neighbor query and join operation to find the distinct objects from different data sets.MapReduce is a newly introduced program with the combination of Map Procedure method and Reduce Method widely used in BigData.MapReduce is enriched with parallel distributed algorithm to find the results on a cluster of data sets in BigData.In this paper,the combination of KNN join and MapReduce methods are utilized on the cluster of data sets in BigData for knowledge discovery.Exploring the pinpoint data from huge data sets stored in Big Data demands the distributed large scale data processing.The present research paper is focusing on generic steps for KNN joins exploration operations on MapReduce.The operations of KNN Join are targeted to perform the data partitioning and data pre-processing and necessary calculations.By utilizing the combination of KNN joins with MapReduce methods on BigData data sets will demonstrate a solution for complex computational analysis. …”
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  9. 9
    The effectiveness of an agile software methodology: empirical evidence on humanistic aspects / Mazni Omar

    The effectiveness of an agile software methodology: empirical evidence on humanistic aspects / Mazni Omar by Omar, Mazni

    Published 2012
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