Search Results - (( data optimization mining algorithm ) OR ( parameter optimization based algorithm ))

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  1. 1

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

    Published 2020
    “…Hence, this thesis presents the optimization of parameters values for the tree-based method by genetic algorithm. …”
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    Thesis
  2. 2

    An online density-based clustering algorithm for data stream based on local optimal radius and cluster pruning by Islam, Md Kamrul

    Published 2019
    “…BOCEDS clusters the data stream in a single stage. The algorithm summarizes the data from data stream in micro-clusters. …”
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    Thesis
  3. 3
  4. 4

    Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets by Saeed, Sana

    Published 2019
    “…Classification of imbalanced datasets remained a significant issue in data mining and machine learning (ML) fields. This research work proposed a new idea based on the optimization for handling the imbalanced datasets. …”
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    Thesis
  5. 5

    Adaptive parameter control strategy for ant-miner classification algorithm by Al-Behadili, Hayder Naser Khraibet, Sagban, Rafid, Ku-Mahamud, Ku Ruhana

    Published 2020
    “…This criterion is responsible for adding only the important terms to each rule, thus discarding noisy data. The ACS algorithm is designed to optimize the IR parameter during the learning process of the Ant-Miner algorithm. …”
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    Article
  6. 6

    A buffer-based online clustering for evolving data stream by Islam, Md. Kamrul, Ahmed, Md. Manjur, Kamal Z., Zamli

    Published 2019
    “…In this study, we present a fully online density-based clustering algorithm called buffer-based online clustering for evolving data stream (BOCEDS). …”
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    Article
  7. 7

    A hybrid model using genetic algorithm and neural network for predicting dengue outbreak by Husin, Nor Azura, Mustapha, Norwati, Sulaiman, Md. Nasir, Yaakob, Razali

    Published 2012
    “…Several model architectures are designed and the parameters are adjusted to achieve optimal prediction performance. …”
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    Conference or Workshop Item
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    Improvement on rooftop classification of worldview-3 imagery using object-based image analysis by Norman, Masayu

    Published 2019
    “…Then, the classifier (support vector machine (SVM) and data mining (DM) algorithm, decision tree (DT) were applied on each fusion image and their accuracy were evaluated. …”
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    Thesis
  10. 10

    Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…Also, self-adaptive scaling factor and crossover probability control parameters are introduced to diminish time of finding an optimal parameter to produce the best population. …”
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    Thesis
  11. 11

    Identification of debris flow initiation zones using topographic model and airborne laser scanning data by Lay, Usman Salihu, Pradhan, Biswajeet

    Published 2017
    “…Conditioning parameters were numerically optimized to identify the arbitrarily maximum model basis function for eleven variables, using MARSplines analysis (algorithm). …”
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    Conference or Workshop Item
  12. 12

    Evaluation of data mining models for predicting concrete strength by Wong, Chuan Ming

    Published 2024
    “…Data mining techniques are becoming more popular in recent years due to their abilities to predict any types of data with high accuracy. …”
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    Final Year Project / Dissertation / Thesis
  13. 13

    Machine-learning-based adaptive distance protection relay to eliminate zone-3 protection under-reach problem on statcom-compensated transmission lines by Aker, Elhadi Emhemed Alhaaj Ammar

    Published 2020
    “…Several conventional adaptive distance relay (ADR) and computational based intelligent modifications presented to solve the impending compromise by using faulted line voltage and current parameters for the various protection relay controller modification, optimizing synchronized measurement to block or limit the fault current penetration into the grid. …”
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    Thesis
  14. 14

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

    Published 2014
    “…The uncertainties of the output power of wind turbine generators are modelled based upon the scenario-based method and data mining techniques. …”
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    Thesis
  15. 15

    Feature selection with integrated Gaussian seahorse optimization data mining for cross-border business cooperation between the Malaysian medical industry and tourism industry by Ma, Yuaner, Jabar, Juhaini, Abdul Aziz, Nor Azah

    Published 2023
    “…This study proposes an integrated approach that combines feature selection with Gaussian Seahorse Optimization Data Mining (GSH-DM) to identify the most relevant features and optimize the data mining process. …”
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    Article
  16. 16

    Web usage mining for UUM learning care using association rules by Ramli, Azizul Azhar

    Published 2004
    “…With the powerful of data mining technique, Web usage mining approach has been combined with the basic Association Rules, Apriori Algorithm to optimize the content of the university E�Learning portal. …”
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    Thesis
  17. 17

    Web Usage Mining for UUM Learning Care Using Association Rules by Azizul Azhar, Ramli

    Published 2004
    “…Main resources, server log files become a set of raw data where it's must go through with all the Web usage mining technique, Web usage mining approach has been combined with the basic Association Rules, Apriori Algorithm to optimize the content of the university E-Learning portal. …”
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    Thesis
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    Data mining using genetic algorithm in finance data / A. Noor Latiffah and A. B. Nordin by Latiffah, A. Noor, Nordin, A. B.

    Published 2006
    “…Data mining can discover patterns or rules from a vast volume of data. …”
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    Conference or Workshop Item
  20. 20

    Optimizing Tree-Based Contrast Subspace Mining Using Genetic Algorithm by Sia, Florence Fui Sze, Rayner Alfred

    Published 2022
    “…Recently, tree-based contrast subspace mining method has been introduced to find contrast subspace in numerical data set effectively. …”
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    Article