Search Results - (( based solution clustering algorithm ) OR ( evolution optimization method algorithm ))

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  1. 1
    Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms

    Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms by Alswaitti, Mohammed Y. T.

    Published 2018
    “…Nature-inspired optimization-based clustering techniques are powerful, robust and more sophisticated than the conventional clustering methods due to their stochastic and heuristic characteristics. …”
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  2. 2
    Clustering ensemble learning method based on incremental genetic algorithms

    Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

    Published 2012
    “…Firstly, an architecture for the clustering ensemble based on incremental genetic-based algorithms is proposed consisting of two phases: (i) to produce cluster partitions as initial populations, (ii) to combine cluster partitions and to generate final clustering solution by incremental genetic based clustering ensemble learning algorithm. …”
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  3. 3
    A novel clustering based genetic algorithm for route optimization

    A novel clustering based genetic algorithm for route optimization by Aibinu, Abiodun Musa, Salau, Habeeb Bello, Najeeb, Athaur Rahman, Nwohu, Mark Ndubuka, Akachukwu, Chichebe

    Published 2016
    “…It was also observed that the introduction of clustering based selection algorithm guaranteed the selection of cluster with the optimal solution in every generation. …”
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  4. 4
    A new variant of black hole algorithm based on multi population and levy flight for clustering problem

    A new variant of black hole algorithm based on multi population and levy flight for clustering problem by Haneen Abdul Wahab, Abdul Raheem

    Published 2020
    “…Black Hole (BH) optimization algorithm has been underlined as a solution for data clustering problems. …”
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  5. 5
    Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain

    Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain by Mohamad Zihin , Mohd Zain

    Published 2018
    “…The proposed method is tested on 10 multi-objective benchmark problems of CEC 2009 and compared with four metaheuristics: Multi-Objective Grey Wolf Optimizer (MOGWO), Multi-Objective Evolutionary Algorithm Based on Decomposition (MOEA/D), Multi-Objective Differential Evolution (MODE) and MOPSO. …”
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  6. 6
    Multi-objective clustering algorithm using particle swarm optimization with crowding distance (MCPSO-CD)

    Multi-objective clustering algorithm using particle swarm optimization with crowding distance (MCPSO-CD) by Rashed, Alwatben Batoul, Hamdan, Hazlina, Mohd Sharef, Nurfadhlina, Sulaiman, Md Nasir, Yaakob, Razali, Abubakar, Mansir

    Published 2020
    “…In an attempt to address this problem, the clustering-based method that utilizes crowding distance (CD) technique to balance the optimality of the objectives in Pareto optimal solution search is proposed. …”
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  7. 7
    Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse)

    Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse) by Jia, Xing Yeoh, Chuii, Khim Chong, Mohd Saberi, Mohamad, Yee, Wen Choon, Lian, En Chai, Safaai, Deris, Zuwairie, Ibrahim

    Published 2015
    “…The hybrid of Differential Evolution algorithm with Kalman Filtering and Bacterial Foraging algorithm is a novel global optimisation method implemented to obtain the best kinetic parameter value. …”
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  8. 8
    A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising

    A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising by Al-Dabbagh, Mohanad Dawood, Al-Dabbagh, Rawaa Dawoud, Raja Abdullah, Raja Syamsul Azmir, Hashim, Fazirulhisyam

    Published 2015
    “…The main intention of this study was to investigate the development of a new optimization technique based on the differential evolution (DE) algorithm, for the purpose of linear frequency modulation radar signal de-noising. …”
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  9. 9
    Differential evolution optimization algorithm based on generation systems reliability assessment integrated with wind energy

    Differential evolution optimization algorithm based on generation systems reliability assessment integrated with wind energy by Kadhem, Athraa Ali, Abdul Wahab, Noor Izzri, Abdalla, Ahmed N.

    Published 2019
    “…This stuffy proposed a novel optimization method labeled the "Differential Evolution Optimization Algorithm" (DEOA) to assess the reliability of power generation systems (PGS). …”
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  10. 10
    Spectrum aware clustering algorithm based on fuzzy logic for sensor based monitoring application / Noorhayati Mohamed Noor …[et al.]

    Spectrum aware clustering algorithm based on fuzzy logic for sensor based monitoring application / Noorhayati Mohamed Noor …[et al.] by Mohamed Noor, Noorhayati, Md Din, Norashidah, Kasiran, Zolidah, Khalid, Nor Azimah, Abdullah, Shapina

    Published 2020
    “…The cluster formation is based on the relative channel availability between the cluster member (CM) and CH to ensure stable cluster connectivity from link failure. …”
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  11. 11
    Knowledge-based genetic algorithm for multidimensional data clustering

    Knowledge-based genetic algorithm for multidimensional data clustering by Purnomo, Muhammad Ridwan Andi, Saleh, Chairul, Lagaida, R.L., Hassan, Azmi

    Published 2013
    “…In this paper, a new approach of genetic algorithm called knowledge-based Genetic Algorithm (KBGA-Clustering) is proposed for multidimensional data clustering. …”
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  12. 12
    Multiobjective optimization of bioethanol production via hydrolysis using hopfield- enhanced differential evolution

    Multiobjective optimization of bioethanol production via hydrolysis using hopfield- enhanced differential evolution by Ganesan, T., Elamvazuthi, I., Shaari, K.Z.K., Vasant, P.

    Published 2014
    “…In this chapter, the weighted sum scalarization approach is used in conjunction with three meta-heuristic algorithms: Differential Evolution (DE), Hopfield-Enhanced Differential Evolution (HEDE), and Gravitational Search Algorithm (GSA). …”
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  13. 13
    HEAT EXCHANGER NETWORK SYNTHESIS AND OPTIMIZATION BY PINCH ANALYSIS AND DIFFERENTIAL EVOLUTION METHOD

    HEAT EXCHANGER NETWORK SYNTHESIS AND OPTIMIZATION BY PINCH ANALYSIS AND DIFFERENTIAL EVOLUTION METHOD by NGO , THI PHUONG THUY

    Published 2016
    “…This metadology way uses an algorithm which combines Pinch Design Method and Differential Evolution Method. …”
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  14. 14
    Performance analysis of clustering based genetic algorithm

    Performance analysis of clustering based genetic algorithm by Najeeb, Athaur Rahman, Aibinu, Abiodun Musa, Nwohu, M. N., Salami, Momoh Jimoh Eyiomika, Salau, H Bello

    Published 2016
    “…In this work, performance analysis of Clustering based Genetic Algorithm (CGA) proposed in the literature has been undertaken. …”
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  15. 15
    Knowledge-based genetic algorithm for multidimensional data clustering

    Knowledge-based genetic algorithm for multidimensional data clustering by Purnomo, Muhammad Ridwan Andi, Saleh, Chairul, Lagaida, Reny Lituhayu, Hassan, Azmi

    Published 2014
    “…In this paper, a new approach of genetic algorithm called knowledge-based Genetic Algorithm (KBGA-Clustering) is proposed for multidimensional data clustering. …”
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  16. 16
    Optimal location and size of distributed generation to reduce power losses and improve voltage profiles using differential evolution optimization method

    Optimal location and size of distributed generation to reduce power losses and improve voltage profiles using differential evolution optimization method by Hammadi, Ahmed Sahib

    Published 2016
    “…The results obtained by using the DE method were compared with those obtained by genetic algorithm (GA) method. …”
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  17. 17
    Parameter extraction of photovoltaic module using hybrid evolutionary algorithm

    Parameter extraction of photovoltaic module using hybrid evolutionary algorithm by Muhsen D.H., Ghazali A.B., Khatib T.

    Published 2023
    “…Algorithms; Diodes; Extraction; Iterative methods; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Different evolutions; Differential Evolution; Diode modeling; Electromagnetism-like algorithm; Extracting parameter; Hybrid evolutionary algorithm; Photovoltaic model; Photovoltaic modules; Evolutionary algorithms…”
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  18. 18
    Multi-objective optimization of two-stage thermo-electric cooler using differential evolution: MO optimization of TEC using DE

    Multi-objective optimization of two-stage thermo-electric cooler using differential evolution: MO optimization of TEC using DE by Khanh, D.V.K., Vasant, P.M., Elamvazuthi, I., Dieu, V.N.

    Published 2015
    “…In this chapter, the technical issues of two-stage TEC were discussed. After that, a new method of optimizing the dimension of TECs using differential evolution to maximize the cooling rate and coefficient of performance was proposed. …”
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  19. 19
    Balancing exploration and exploitation in ACS algorithms for data clustering

    Balancing exploration and exploitation in ACS algorithms for data clustering by Jabbar, Ayad Mohammed, Sagban, Rafid, Ku-Mahamud, Ku Ruhana

    Published 2019
    “…This makes the algorithm deviate from the clustering solution and performs a biased exploration. …”
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  20. 20
    An energy-efficient spectrum-aware reinforcement learning-based clustering algorithm for cognitive radio sensor networks

    An energy-efficient spectrum-aware reinforcement learning-based clustering algorithm for cognitive radio sensor networks by Mustapha, Ibrahim, Mohd Ali, Borhanuddin, A. Rasid, Mohd Fadlee, Sali, Aduwati, Mohamad, Hafizal

    Published 2015
    “…In this paper, we propose a reinforcement learning-based spectrum-aware clustering algorithm that allows a member node to learn the energy and cooperative sensing costs for neighboring clusters to achieve an optimal solution. …”
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