Search Results - (( data selection based algorithm ) OR ( data optimization based algorithm ))

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  1. 1

    Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection by Tubishat, Mohammad, Idris, Norisma, Shuib, Liyana, Abushariah, Mohammad A.M., Mirjalili, Seyedali

    Published 2020
    “…Thus, to solve these problems, feature selection can be used to select optimal subset of features and reduce the data dimensionality. …”
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    Article
  2. 2

    Enhancing Classification Algorithms with Metaheuristic Technique by Cokro, Nurwinto, Tri Basuki, Kurniawan, Misinem, ., Tata, Sutabri, Yesi Novaria, Kunang

    Published 2024
    “…However, the classification algorithm cannotclassify data optimally due to the challenges in dealing with variousdata sets. …”
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  3. 3

    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

    Published 2022
    “…Therefore, in this paper, we proposed Dynamic tasks scheduling algorithm based on attribute reduction with an enhanced hybrid Genetic Algorithm and Particle Swarm Optimization for optimal device selection. …”
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    Feature selection based on particle swarm optimization algorithm for sentiment analysis classification by Nurcahyawati, Vivine, Mustaffa, Zuriani

    Published 2021
    “…Furthermore, the proposed algorithm solves the complex background problems about noise data and feature selection that affect the classification performance on sentiment analysis. …”
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    Conference or Workshop Item
  6. 6

    Taylor-Bird Swarm Optimization-Based Deep Belief Network For Medical Data Classification by Mohammed, Alhassan Afnan

    Published 2022
    “…The major contribution of this research is to introduce a Taylor-Bird Swarm optimization-based Deep Belief Network (Taylor-BSA-based DBN) for medical data classification. …”
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    Thesis
  7. 7

    Ant colony optimization for rule induction with simulated annealing for terms selection by Saian, Rizauddin, Ku-Mahamud, Ku Ruhana

    Published 2012
    “…This paper proposes a sequential covering based algorithm that uses an ant colony optimization algorithm to directly extract classification rules from the data set.The proposed algorithm uses a Simulated Annealing algorithm to optimize terms selection, while growing a rule.The proposed algorithm minimizes the problem of a low quality discovered rule by an ant in a colony, where the rule discovered by an ant is not the best quality rule, by optimizing the terms selection in rule construction. …”
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    Conference or Workshop Item
  8. 8

    Enhancement of bearing defect diagnosis via genetic algorithm optimized feature selection by Chia, Yee Shin

    Published 2015
    “…In addition, GA has the limitation on generalization which causes the problem of overfitting to the training data. Therefore a correlation-based filtering algorithm is embedded into GA feature selection to solve the over-fitting problem and increase the adaptability of the diagnostic scheme to unpredictable input data. …”
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    Thesis
  9. 9

    Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi by Atefi, Kayvan

    Published 2019
    “…This strategy includes a number of components that are a novel approach to clustering generation. In fact a data clustering method is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on our proposed algorithm; which is Enhanced Binary Particle swarm Optimization (EBPSO), (ii) To mine data using various data chunks (windows) and overcome a failure of single clustering. …”
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    Thesis
  10. 10

    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
    “…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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    Thesis
  11. 11

    Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

    Published 2018
    “…To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
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    Thesis
  12. 12

    Improved intrusion detection algorithm based on TLBO and GA algorithms by Aljanabi, Mohammad, Mohd Arfian, Ismail

    Published 2021
    “…The proposed method combined the New Teaching-Learning-Based Optimization Algorithm (NTLBO), Support Vector Machine (SVM), Extreme Learning Machine (ELM), and Logistic Regression (LR) (feature selection and weighting) NTLBO algorithm with supervised machine learning techniques for Feature Subset Selection (FSS). …”
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    Article
  13. 13

    A Conceptual Framework of Bacterial Foraging Optimization Algorithm for Data Classification by Hossin, M., Mohd Suria, F.

    Published 2016
    “…Most previous works on Bacterial Foraging Optimization Algorithm (BFOA) for data classification were integrated BFOA as a feature selection algorithm and parameters optimizer for other classifiers. …”
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    Proceeding
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    Optimization of attribute selection model using bio-inspired algorithms by Basir, Mohammad Aizat, Yusof, Yuhanis, Hussin, Mohamed Saifullah

    Published 2019
    “…The aim of this paper is to investigate the use of bio-inspired search algorithms in producing optimal attribute set. This is achieved in two stages; 1) create attribute selection models by combining search method and feature selection algorithms, and 2) determine an optimized attribute set by employing bio-inspired algorithms.Classification performance of the produced attribute set is analyzed based on accuracy and number of selected attributes. …”
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    Article
  17. 17

    Mutable composite firefly algorithm for gene selection in microarray based cancer classification by Fajila, Mohamed Nisper Fathima

    Published 2022
    “…Hence, this study proposed to modify the Firefly Algorithm (FA) along with the Correlation-based Feature Selection (CFS) filter for the gene selection task. …”
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    Thesis
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    Ideal combination feature selection model for classification problem based on bio-inspired approach by Basir, Mohammad Aizat, Hussin, Mohamed Saifullah, Yusof, Yuhanis

    Published 2020
    “…Feature selection or attribute reduction is a crucial process to achieve optimal data reduction for classification task. …”
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    Book Section
  19. 19

    VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern by Angeline Teoh, Szu Fern

    Published 2012
    “…GA is a widely used optimization algorithm based on the concept of survival of the fittest. …”
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    Thesis
  20. 20

    Development of genetic algorithm-based fuzzy rules design for metal cutting data selection by Wong, S.V, Hamouda, A.M.S

    Published 2002
    “…The development of a Fuzzy Genetic Optimization algorithm is presented and discussed. An object-oriented library to handle fuzzy rules optimization with genetic optimization has been developed. …”
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    Article