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  1. 1
    Automatic Multi-Objective Clustering Algorithm Using Hybrid Particle Swarm Optimization With Simulated Annealing.

    Automatic Multi-Objective Clustering Algorithm Using Hybrid Particle Swarm Optimization With Simulated Annealing. by Abubaker, Ahmad Asad

    Published 2016
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  2. 2
    Fuzzy clustering method and evaluation based on multi criteria decision making technique

    Fuzzy clustering method and evaluation based on multi criteria decision making technique by Sameer, Fadhaa Othman

    Published 2018
    “…The proposed algorithm is used as a pre-processing method for data followed by Gustafson-Kessel (GK) algorithm to classify credit scoring data. …”
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  3. 3
    Energy-efficient data transmission with clustering and compressive sensing in wireless sensor networks / Mukil Alagirisamy

    Energy-efficient data transmission with clustering and compressive sensing in wireless sensor networks / Mukil Alagirisamy by Mukil , Alagirisamy

    Published 2020
    “…In the extended ECH-DUAL algorithm in addition to dual sink a new cluster head selection method is proposed for unequal clustering. …”
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  4. 4
    A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption

    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 first research objective is to develop a new deep learning algorithm by a hybrid of DNN and K-Means Clustering algorithms for estimating the Lorenz chaotic system. …”
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  5. 5
    Optimisation model for scheduling MapReduce jobs in big data processing / Ibrahim Abaker Targio Hashem

    Optimisation model for scheduling MapReduce jobs in big data processing / Ibrahim Abaker Targio Hashem by Ibrahim Abaker , Targio Hashem

    Published 2017
    “…In addition, NSGA-II algorithm was able to find the optimal solutions. We then proposed a multi-objective scheduling algorithm framework that considers resource allocation and task scheduling in a heterogonous cloud environment. …”
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  6. 6
    A green clustering protocol for mobile sensor network using particle swarm optimization

    A green clustering protocol for mobile sensor network using particle swarm optimization by Latiff, N.M.A., NikAbdMalik, N., Latiff, A.H.A.

    Published 2016
    “…One of the methods that can improve the utilization of sensor nodes batteries is the clustering method. In this paper, we propose a green clustering protocol for mobile sensor networks using particle swarm optimization (PSO) algorithm. …”
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  7. 7
    A green clustering protocol for mobile sensor network using particle swarm optimization

    A green clustering protocol for mobile sensor network using particle swarm optimization by Latiff, N.M.A., NikAbdMalik, N., Latiff, A.H.A.

    Published 2016
    “…One of the methods that can improve the utilization of sensor nodes batteries is the clustering method. In this paper, we propose a green clustering protocol for mobile sensor networks using particle swarm optimization (PSO) algorithm. …”
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  8. 8
    Energy-Aware Routing Hole Detection Algorithm in the Hierarchical Wireless Sensor Network

    Energy-Aware Routing Hole Detection Algorithm in the Hierarchical Wireless Sensor Network by Najm Us, Sama, Kartinah, Zen, Atiq Ur, Rahman, Aziz Ud, Din

    Published 2019
    “…Detection of holes saves the additional energy consumption around the hole and minimize the hole size. In this paper a novel energy efficient routing hole detection (EEHD) algorithm is presented, on the detection of routing hole, the periodic re-clustering is performed to avoid the long detour path. …”
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  9. 9
    Region-based Energy-aware Clustering (REC) for Efficient Packet Forwarding in WSN

    Region-based Energy-aware Clustering (REC) for Efficient Packet Forwarding in WSN by Nazir, Babar, Hasbullah, Halabi

    Published 2010
    “…With REC, algorithms for energy efficient cluster formation, cluster head selection, and intercluster communication is proposed. …”
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  10. 10
    Case study : an effect of noise in character recognition system using neural network

    Case study : an effect of noise in character recognition system using neural network by Mohamad, Esmawaty

    Published 2003
    “…The aim of this project is to develop a network that is able to recognize various inputs through a series of simulation using Neural Network simulator called MATLAB. …”
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  11. 11
    Regionalization by fuzzy expert system based approach optimized by genetic algorithm.

    Regionalization by fuzzy expert system based approach optimized by genetic algorithm. by Chavoshi, Sattar, Sulaiman, Wan Nor Azmin, Saghafian, Bahram, Sulaiman, Md. Nasir, Abd Manaf, Latifah

    Published 2013
    “…Genetic algorithm (GA) was employed to adjust parameters of FES and optimize the system. …”
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  12. 12
    Green anaconda optimization based energy aware clustering protocol for 6G wireless communication systems

    Green anaconda optimization based energy aware clustering protocol for 6G wireless communication systems by Motwakel, Abdelwahed, Hassan Abdalla Hashim, Aisha, Mengash, Hanan Abdullah, Alruwais, Nuha, Yafoz, Ayman, Alsini, Raed, Edris, Alaa

    Published 2023
    “…Therefore, this study presents a new Green Anaconda Optimization Based Energy Aware Clustering Protocol (GAOB-EACP) approach for WSN. …”
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  13. 13
    QoS BASED ENERGY EFFICIENT ROUTING IN WIRELESS SENSOR NETWORK

    QoS BASED ENERGY EFFICIENT ROUTING IN WIRELESS SENSOR NETWORK by NAZIR, BABAR

    Published 2012
    “…Clustering within normal sensor nodes is done by optimizing the network/coverage lifetime through a cluster-head-selection algorithm and a sleep/wake scheduling algorithm. …”
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  14. 14
    Neuro fuzzy classification and detection technique for bioinformatics problems

    Neuro fuzzy classification and detection technique for bioinformatics problems by Othman, Mohd. Fauzi, Moh, Thomas Shan Yau

    Published 2007
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  15. 15
    Lightweight ontology architecture for QoS aware service discovery and semantic CoAP data management in heterogeneous IoT environment

    Lightweight ontology architecture for QoS aware service discovery and semantic CoAP data management in heterogeneous IoT environment by Sukhavasi, Suman, Perumal, Thinagaran, Mustapha, Norwati, Yaakob, Razali

    Published 2026
    “…To address these issues, this paper proposes a lightweight ontology-based architecture that enhances service discovery and QoS-aware semantic data management. The architecture employs Modified-Ordered Points to Identify the Clustering Structure (M-OPTICS) to cluster and eliminate redundant IoT data. …”
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  16. 16
    Self-Organized Wireless Sensor Network (SOWSN) for dense jungle applications

    Self-Organized Wireless Sensor Network (SOWSN) for dense jungle applications by Hakim, Galang Persada Nurani, Habaebi, Mohamed Hadi, Islam, Md Rafiqul, Alghaihab, Abdullah, Yusoff, Siti Hajar, Adesta, Erry Yulian Triblas

    Published 2023
    “…The introduced features were extensively evaluated and analyzed using simulation and empirical measurements. Using clustering, near-ground propagation, and adaptive transmission power control features, a robust wireless data transmission system was built while simultaneously providing power conservation in SOWSN operation. …”
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  17. 17
    Wavelet based fault tolerant control of induction motor / Khalaf Salloum Gaeid

    Wavelet based fault tolerant control of induction motor / Khalaf Salloum Gaeid by Gaeid, Khalaf Salloum

    Published 2012
    “…There are two steps in the fault tolerant control process; in the first step the fault is identified with the feature extraction module, a fault decision module and a feature cluster module. …”
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  18. 18
    On density-based data streams clustering algorithms: A survey

    On density-based data streams clustering algorithms: A survey by Teh, Y.W.

    Published 2017
    “…Recently, a lot of density-based clustering algorithms are extended for data streams. …”
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  19. 19
    A study of density-grid based clustering algorithms on data streams

    A study of density-grid based clustering algorithms on data streams by Amini, A., Saybani, M.R., Sahaf Yazdi, S.R.A.

    Published 2011
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  20. 20
    An adaptive density-based method for clustering evolving data streams / Amineh Amini

    An adaptive density-based method for clustering evolving data streams / Amineh Amini by Amini, Amineh

    Published 2014
    “…Due to these characteristics the traditional densitybased clustering is not applicable. Recently, a number of density-based algorithms have been developed for clustering data streams. …”
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