Search Results - (( developing function mining algorithm ) OR ( its implementation case algorithm ))

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  1. 1
    Tree-based contrast subspace mining method

    Tree-based contrast subspace mining method by Florence Sia Fui Sze

    Published 2020
    “…Then, the tree-based method, the genetic algorithm based parameter values identification of tree-based method, and followed by the genetic algorithm based tree-based method, for numerical data sets are developed and evaluated. …”
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  2. 2
    The application of neural network data mining algorithm into mixed pixel classification in geographic information system environment

    The application of neural network data mining algorithm into mixed pixel classification in geographic information system environment by Nanna Suryana, Herman

    Published 2007
    “…This , paper discusses the development of data mining and pattern recognition algorithm to handle the complexity of hyperspectral remote sensing images in Geographical Information Systems environment. …”
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  3. 3
    Development and applications of metaheuristic algorithms in engineering design and structural optimization / Ali Sadollah

    Development and applications of metaheuristic algorithms in engineering design and structural optimization / Ali Sadollah by Ali, Sadollah

    Published 2013
    “…In addition, two novel optimization methods are developed and presented which are named the mine blast algorithm (MBA) and the water cycle algorithm (WCA). …”
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  4. 4
    Y-type Random 2-satisfiability In Discrete Hopfield Neural Network

    Y-type Random 2-satisfiability In Discrete Hopfield Neural Network by Guo, Yueling

    Published 2024
    “…The developed logic mining will be used to analyze the Alzheimer's Disease Neuroimaging Initiative dataset.…”
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  5. 5
    Data Mining Analysis Of Chronic Kidney Disease (CKD) Level

    Data Mining Analysis Of Chronic Kidney Disease (CKD) Level by Mohd Harizi, Muhammad Hafizam Afiq

    Published 2022
    “…Adding the uncertain class the best accuracy obtained was 98.5% using the SMO algorithm. A predictive classification model that determines the accuracy for three classification classes was developed accordingly using the SMO algorithm.…”
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  6. 6
    IMPLEMENTATION OF GRAPH BASED PATH PLANNING ALGORITHMS FOR INDOOR NAVIGATION

    IMPLEMENTATION OF GRAPH BASED PATH PLANNING ALGORITHMS FOR INDOOR NAVIGATION by SYED KHAIZURA, SYED HUSEIN KAMIL

    Published 2018
    “…Thus, the A* algorithm is implemented in a small mobile robot, this is to see its effectiveness in real world application. …”
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    Final Year Project
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  7. 7
    Context aware app recommendation using email semantic analysis

    Context aware app recommendation using email semantic analysis by Tang, Zi Cong

    Published 2019
    “…The recommendation system is planned to develop by using data mining and machine learning. …”
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  8. 8
    A new text-based w-distance metric to find the perfect match between words

    A new text-based w-distance metric to find the perfect match between words by Ali, M., Jung, L.T., Hosam, O., Wagan, A.A., Shah, R.A., Khayyat, M.

    Published 2020
    “…The k-NN algorithm is an instance-based learning algorithm which is widely used in the data mining applications. …”
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  9. 9
    Image clustering comparison of two color segmentation techniques

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

    Published 2010
    “…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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  10. 10
    Stock price monitoring system

    Stock price monitoring system by Ng, Chun Ming

    Published 2024
    “…Consequently, Root Mean Squared Error (RMSE) and Mean Absolute Percentage Error (MAPE) are used to evaluate the performance of the prediction algorithms. The methodology used in this project is Cross-Industry Standard Process for Data Mining (CRISP-DM), which is a common standard for data mining projects. …”
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  11. 11
    A study of fluctuations in genetic algorithm optimized network in data centre

    A study of fluctuations in genetic algorithm optimized network in data centre by Nurika, O., Hassan, M.F., Zakaria, N., Jung, L.T.

    Published 2017
    “…The reliability of genetic algorithm may vary based on implementation case, hence it is necessary to investigate its performance pattern for each implementation case. …”
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  12. 12
    Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy

    Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

    Published 2019
    “…An efficient iterative algorithm is developed to optimize the objective function of the proposed algorithm since it is non-smooth and difficult to solve. …”
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  13. 13
    A study of fluctuations and confidence of implementation in genetic algorithm optimized network in data centre

    A study of fluctuations and confidence of implementation in genetic algorithm optimized network in data centre by Nurika, O., Hassan, M.F., Zakaria, N., Jung, L.T.

    Published 2018
    “…The reliability of genetic algorithm may vary based on implementation case, hence it is necessary to investigate its performance pattern for each implementation case. …”
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  14. 14
    A study of fluctuations and confidence of implementation in genetic algorithm optimized network in data centre

    A study of fluctuations and confidence of implementation in genetic algorithm optimized network in data centre by Nurika, O., Hassan, M.F., Zakaria, N., Jung, L.T.

    Published 2018
    “…The reliability of genetic algorithm may vary based on implementation case, hence it is necessary to investigate its performance pattern for each implementation case. …”
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  15. 15
    Prediction Of Leaf Mechanical Properties Based On Geometry Features With Data Mining

    Prediction Of Leaf Mechanical Properties Based On Geometry Features With Data Mining by H’ng, Choo Wooi

    Published 2019
    “…The linear models and rules developed from the M5P algorithm were adopted for the FT indicator prediction modelling of 14 attributes. …”
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  16. 16
    Implementation and Evaluation of Large Rsa Encryption and Decryption Keys For Internet Security

    Implementation and Evaluation of Large Rsa Encryption and Decryption Keys For Internet Security by H. Belgassem, Seddeq

    Published 2004
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  17. 17
    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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  18. 18
    Construction of prioritized t-way test suite using Bi-objective Dragonfly Algorithm

    Construction of prioritized t-way test suite using Bi-objective Dragonfly Algorithm by Ahmed, Mashuk, Nasser, Abdullah B., Kamal Z., Zamli

    Published 2022
    “…We have designed and implemented a Bi-objective Dragonfly Algorithm (BDA) for prioritized t-way test suite generation, and the two objectives are test case weight and test case priority. …”
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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
    “…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
    Logistic regression methods for classification of imbalanced data sets

    Logistic regression methods for classification of imbalanced data sets by Santi Puteri Rahayu, -

    Published 2012
    “…This thesis aims to develop the simple and effective imbalanced classification algorithms by previously improving the algorithms performance of general classifiers i.e. …”
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