Search Results - (( based generation mining algorithm ) OR ( based optimization method algorithm ))

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  1. 1

    Social media mining: a genetic based multiobjective clustering approach to topic modelling by Rayner Alfred, Loo Yew Jie, Joe Henry Obit, Yuto Lim, Haviluddin Haviluddin, Azreen Azman

    Published 2021
    “…However, less works have been conducted in applying multiobjective based algorithm for topic extraction. Most of these algorithms are not optimized, even if they are, they are only optimized by using a single objective method and may underperform when solving real-world problems which are typically multi-objectives in nature. …”
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  2. 2

    Social media mining: a genetic based multiobjective clustering approach to topic modelling by Alfred, Rayner, Loo, Yew Jie, Obit, Joe Henry, Lim, Yuto, Haviluddin, Haviluddin, Azman, Azreen

    Published 2021
    “…However, less works have been conducted in applying multiobjective based algorithm for topic extraction. Most of these algorithms are not optimized, even if they are, they are only optimized by using a single objective method and may underperform when solving real-world problems which are typically multi-objectives in nature. …”
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  3. 3

    Optimal QoS aware multiple paths web service composition using heuristic algorithms and data mining techniques by Qtaish, Osama Kayed Taher

    Published 2014
    “…The aim is to solve the above-mentioned problems via an optimization mechanism based upon the combination between runtime path prediction method and heuristic algorithms. …”
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  4. 4

    Ideal combination feature selection model for classification problem based on bio-inspired approach by Basir, Mohammad Aizat, Hussin, Mohamed Saifullah, Yusof, Yuhanis

    Published 2020
    “…The aim of this paper is to exploit the capability of bio-inspired search algorithms, together with wrapper and filtered methods in generating optimal set of features. …”
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  5. 5

    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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  6. 6

    Discovering optimal clusters using firefly algorithm by Mohammed, Athraa Jasim, Yusof, Yuhanis, Husni, Husniza

    Published 2016
    “…Existing conventional clustering techniques require a pre-determined number of clusters, unluckily; missing information about real world problem makes it a hard challenge.A new orientation in data clustering is to automatically cluster a given set of items by identifying the appropriate number of clusters and the optimal centre for each cluster.In this paper, we present the WFA_selection algorithm that originates from weight-based firefly algorithm.The newly proposed WFA_selection merges selected clusters in order to produce a better quality of clusters.Experiments utilising the WFA and WFA_selection algorithms were conducted on the 20Newsgroups and Reuters-21578 benchmark dataset and the output were compared against bisect K-means and general stochastic clustering method (GSCM).Results demonstrate that the WFA_selection generates a more robust and compact clusters as compared to the WFA, bisect K-means and GSCM.…”
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  7. 7

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

    Published 2019
    “…Data stream clustering plays an important role in data stream mining for knowledge extraction. Numerous researchers have recently studied density-based clustering algorithms due to their capability to generate arbitrarily shaped clusters. …”
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  8. 8

    An enhanced version of black hole algorithm via levy flight for optimization and data lustering problems by Haneen, Abd Wahab, Noraziah, Ahmad, Alsewari, Abdulrahman A., Sinan, Q. Salih

    Published 2019
    “…Black Hole (BH) optimization algorithm has been underlined as a solution for data clustering problems, in which it is a population-based metaheuristic that emulates the phenomenon of the black holes in the universe. …”
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  9. 9
  10. 10

    An enhanced version of black hole algorithm via levy flight for optimization and data clustering problems by Abdulwahab, Haneen A., Noraziah, Ahmad, Al-Sewari, Abdul Rahman Ahmed Mohammed, Salih, Sinan Q.

    Published 2019
    “…Black Hole (BH) optimization algorithm has been underlined as a solution for data clustering problems, in which it is a population-based metaheuristic that emulates the phenomenon of the black holes in the universe. …”
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  11. 11

    Hybrid metaheuristics for QOS-aware service composition / Hadi Naghavipour by Hadi , Naghavipour

    Published 2022
    “…An absolute majority of base algorithms for this problem were nature-inspired and population-based metaheuristics extended to complementary methods in hybrid solutions. …”
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  12. 12

    Improved Malware detection model with Apriori Association rule and particle swarm optimization by Adebayo, Olawale Surajudeen, Abdul Aziz, Normaziah

    Published 2019
    “…In order to improve the detection rate of malicious application on the Android platform, a novel knowledge-based database discovery model that improves apriori association rule mining of a priori algorithm with Particle Swarm Optimization (PSO) is proposed. …”
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  13. 13

    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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  14. 14

    Spatial Data Mining Model For Landfill Sites Suitability Mapping Based On Neural Networks And Multivariate Analysis by Abujayyab, Sohaib K. M.

    Published 2017
    “…Hybrid neural network was utilized as an evaluation method to select the optimal selection method and optimal training algorithm. …”
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  15. 15

    An enhanced sequential exception technique for semantic-based text anomaly detection by Taiye, Mohammed Ahmed

    Published 2019
    “…The detection of semantic-based text anomaly is an interesting research area which has gained considerable attention from the data mining community. …”
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  16. 16

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

    Published 2018
    “…The clustering algorithm consists of two components: the temporal micro-clusters generation and the temporal micro clusters merging. …”
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  17. 17

    Classification with degree of importance of attributes for stock market data mining by Khokhar, Rashid Hafeez, Md. Sap, Mohd. Noor

    Published 2004
    “…The experimental results show that predictive FDT algorithm can generate a relatively optimal tree without much computation effort (comprehensibility), and WFPRs have a better predictive accuracy of stock market time series data. …”
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  18. 18

    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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  19. 19

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

    Published 2018
    “…To enhance the selection of most highly ranking features, irrelevant features are ‘pruned’ based on determined boundary threshold. In order to estimate the quality of ‘pruned’ features, self-adaptive DE algorithm is proposed. …”
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  20. 20

    A frequent pattern mining algorithm based on FP-growth without generating tree by Tohidi, Hossein, Ibrahim, Hamidah

    Published 2010
    “…Our algorithm works based on prime factorization, and is called Frequent Pattern-Prime Factorization (FPPF).…”
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