Search Results - (( java implementation case algorithm ) OR ( parameter adaptation clustering algorithm ))

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  1. 1

    Topological Clustering via Adaptive Resonance Theory With Information Theoretic Learning by Masuyama, Naoki, Loo, Chu Kiong, Ishibuchi, Hisao, Kubota, Naoyuki, Nojima, Yusuke, Liu, Yiping

    Published 2019
    “…Other types of the ART-based topological clustering algorithms have been developed, however, these algorithms have various drawbacks such as a large number of parameters, sensitivity to noisy data. …”
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    Article
  2. 2

    Aco-based feature selection algorithm for classification by Al-mazini, Hassan Fouad Abbas

    Published 2022
    “…However, the MGCACO algorithm has three main drawbacks in producing a features subset because of its clustering method, parameter sensitivity, and the final subset determination. …”
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    Thesis
  3. 3

    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

    Published 2008
    “…The prototype system, known as Java Plagiarism Detection System (JPDS) implements the Greedy-String-Tiling algorithm to detect similarities among tokens in a Java source code files. …”
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    Thesis
  4. 4

    Hybrid Henry gas solubility optimization algorithm with dynamic cluster-to-algorithm mapping by Kamal Z., Zamli, Kader, Md. Abdul, Azad, Saiful, Ahmed, Bestoun S.

    Published 2021
    “…Exploiting the dynamic cluster-to-algorithm mapping via penalized and reward model with adaptive switching factor, HHGSO offers a novel approach for meta-heuristic hybridization consisting of Jaya Algorithm, Sooty Tern Optimization Algorithm, Butterfly Optimization Algorithm, and Owl Search Algorithm, respectively. …”
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  5. 5

    Cluster head selection algorithm using fuzzy logic in multi-tier Wireless Sensor Network for energy efficiency / Wan Isni Sofiah Wan Din by Wan Din, Wan Isni Sofiah

    Published 2016
    “…However, there is still a lack of effective techniques to determine and select the cluster head. Currently, the selection of cluster head is based on residual energy and several parameters. …”
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    Thesis
  6. 6

    Energy Balancing Through Cluster Head Selection Using K-Theorem in Homogeneous Wireless Sensor Networks by Muhammad , Imran, Asfandyar, khan, Azween, Abdullah

    “…This CN take up the responsibility of transmitting data to the base station over longer distances from cluster heads. We have proposed a cluster head selection algorithm based on K - theorem and other parameters i.e. residual energy, distance to coordinator node, reliability and degree of mobility. …”
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    Conference or Workshop Item
  7. 7

    Energy Balancing Through Cluster Head Selection Using K-Theorem in Homogeneous Wireless Sensor Networks by Muhammad , Imran, Asfandyar, khan, Azween, Abdullah

    Published 2008
    “…This CN take up the responsibility of transmitting data to the base station over longer distances from cluster heads. We have proposed a cluster head selection algorithm based on K - theorem and other parameters i.e. residual energy, distance to coordinator node, reliability and degree of mobility. …”
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    Conference or Workshop Item
  8. 8
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    Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed by Borujeni, Sattar Chavoshi

    Published 2012
    “…In conventional hard clustering approach, the number of clusters was determined by hierarchical clustering and two-step cluster analysis; then the sites were allocated to the appropriate cluster by k-means clustering method. …”
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    Thesis
  10. 10

    Novel direct and self-regulating approaches to determine optimum growing multi-experts network structure by Loo, C.K., Rajeswari, M., Rao, M.V.C.

    Published 2004
    “…However, GMN is not ergonomic due to too many network control parameters. Therefore, a self-regulating GMN (SGMN) algorithm is proposed. …”
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    Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things by Hadi, Ahmed Adnan

    Published 2022
    “…Hence, the algorithm must overcome the problem of dynamic updates in the internal parameters or counter the concept drift. …”
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    Thesis
  13. 13

    Hyper-heuristic framework for sequential semi-supervised classification based on core clustering by Adnan, Ahmed, Muhammed, Abdullah, Abd Ghani, Abdul Azim, Abdullah, Azizol, Huyop @ Ayop, Fahrul Hakim

    Published 2020
    “…Hence, the algorithm must overcome the problem of dynamic update in the internal parameters or countering the concept drift. …”
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  14. 14

    A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

    Published 2023
    “…The research starts with developing the hybrid deep learning model consisting of DNN and a K-Means Clustering Algorithm. Then, the developed algorithm is implemented to estimate the parameters of the Lorenz system. …”
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  15. 15

    A framework of modified adaptive neuro-fuzzy inference engine by Hossen, Md. Jakir

    Published 2012
    “…The developed TSK type fuzzy inference engine is called modified adaptive fuzzy inference engine (MAFIE) and its parameters were then adjusted by the hybrid learning algorithm using adaptive neural network architecture towards improved performance which is called MANFIE. …”
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    Thesis
  16. 16

    Adaptive neuro-fuzzy model with fuzzy clustering for nonlinear prediction and control by Al-Himyari, Bayadir Abbas, Yasin, Azman, Gitano, Horizon

    Published 2014
    “…One area of particular importance is the design of networks capable of modeling and predicting the behavior of systems that involve complex, multi-variable processes.To illustrate the applicability of the neuro-fuzzy networks, a case study involving air-fuel ratio is presented here.Air- fuel ratio represents complex, nonlinear and stochastic behavior.To monitor the engine conditions, an adaptive neuro-fuzzy inference system (ANFIS) is used to capture the nonlinear connections between the air- fuel ratio and control parameters such manifold air pressure, throttle position, manifold air temperature, engine temperature, engine speed, and injection opening time.This paper describes a fuzzy clustering method to initialize the ANFIS.…”
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  17. 17

    Pairwise testing tools based on hill climbing algorithm (PTCA) by Lim, Seng Kee

    Published 2014
    “…The actual implementation of the algorithm which is in Java programming language, the program is implemented on Net Bean 7.0.1. …”
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    Undergraduates Project Papers
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    Java based expert system for selection of natural fibre composite materials by Ahmed Ali, Basheer A., Salit, Mohd Sapuan, Zainudin, Edi Syams, Othman, Mohamed

    Published 2013
    “…In this paper, we develop a technology for the materials selection system using Java based expert system. The weighted-range method (WRM) was implemented to identify the range value and to scrutinise the candidate materials. …”
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