Search Results - (( parameter optimization system algorithm ) OR ( using function clustering algorithm ))

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  1. 1

    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 fitness function used is the correlation function in the SKF algorithm to optimize the cipher image produced using the Lorenz system. …”
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    Thesis
  2. 2

    Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed by Borujeni, Sattar Chavoshi

    Published 2012
    “…Genetic algorithm (GA) was employed to adjust parameters of FES and optimize the system. …”
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    Thesis
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    Cauchy density-based algorithm for VANETs clustering in 3D road environments by Jubair, Mohammed Ahmed, Ahmad, Mohd Riduan, Abdul Aziz, Izzatdin, Al-Obaidi, Ahmed Salih, Al-Tickriti, Abdullah Talaat, Hassan, Mustafa Hamid, Mostafa, Salama A., Mahdin, Hairulnizam

    Published 2022
    “…Clustering algorithms for VANETs operate in a decentralized mode, which requires incorporating additional stages before deciding the clustering decisions and might create sub-optimality due to the local nature of the decentralized approach. …”
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    Article
  5. 5

    Development of compound clustering techniques using hybrid soft-computing algorithms by Salim, Naomie, Shamsuddin, Siti Mariyam, Salleh @ Sallehuddin, Roselina, Alwee, Razana

    Published 2006
    “…The hierarchical fuzzy clustering algorithm developed in this work assign the overlapping structures (structures having more than one activity) to more than one clusters if their fuzzy membership values are significantly high for those clusters. …”
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    Monograph
  6. 6

    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
    “…In addition, an objective function is designed to accomplish Quality of Service (QoS) in WSN using three input parameters, namely energy, distance, and delay. …”
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    Article
  7. 7

    Time series modeling of water level at Sulaiman Station, Klang River, Malaysia by Galavi, Hadi

    Published 2010
    “…An ARIMA(3,1,3) model was found to be the appropriate ARIMA model for the modelling of the selected case study. A Subtractive Clustering Method was used in the fuzzy inference system to determine the optimal number of Membership Functions (MF) and rules. …”
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    Thesis
  8. 8

    Landslide susceptibility mapping using decision-tree based chi-squared automatic interaction detection (CHAID) and logistic regression (LR) integration by Althuwaynee, Omar F., Pradhan, Biswajeet, Ahmad, Noordin

    Published 2014
    “…LR model was used to find the corresponding coefficients of best fitting function that assess the optimal terminal nodes. …”
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    Conference or Workshop Item
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    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 first feature is the introduction of Multi Criteria Decision Making (MCDM) algorithm with simple Additive Weight (SAW) function for clustering the SOWSN nodes. …”
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    Article
  11. 11

    Channel Modeling and Direction-of-Arrival Estimation in Mobile Multiple-Antenna Communication Systems by Ravari, Arastoo Rostami

    Published 2005
    “…The characterization of the spatial channel, in particular mean direction of arrival and spatial spread, is of prime interest for system optimization and performance prediction. Low-complexity spectral-based estimators are used for the estimation of direction and spatial spread of the distributed source by employing the proposed channel model for simulation. …”
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    Thesis
  12. 12

    Determining the preprocessing clustering algorithm in radial basis function neural network by S.L. Ang, H.C. Ong, H.C. Law

    Published 2008
    “…Three types of method used in this study to find the centres include random selections, K-means clustering algorithm and also K-median clustering algorithm. …”
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    Article
  13. 13

    Biological-based semi-supervised clustering algorithm to improve gene function prediction by Kasim, Shahreen, Deris, Safaai, M. Othman, Razib, Hashim, Rathiah

    Published 2011
    “…However, commonclustering algorithms do not provide a comprehensive approach that look into the three categories of annotations; biologicalprocess, molecular function, and cellular component, and were not tested with different functional annotation database formats.Furthermore, the traditional clustering algorithms use random initialization which causes inconsistent cluster generation and areunable to determine the number of clusters involved. …”
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    Article
  14. 14

    Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm by Dalatu, Paul Inuwa

    Published 2018
    “…The K-Means algorithm is the commonest and fast technique in partitional cluster algorithms, although with unnormalized datasets it can achieve local optimal. …”
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    Thesis
  15. 15

    A Study On The Application Of Gravitational Search Algorithm In Optimizing Stereo Matching Algorithm’s Parameters For Star Fruit Inspection System by Zainal Abidin, Amar Faiz, Mohd Ali, Nursabillilah, Mat Zain, Norlina, Abdul Majid, Masmaria, Rifin, Rozi, Kadiran, Kamaru Adzha, Mohd Mokji, Ahmad Musa, Tan, Kok, Amirulah, Rahman

    Published 2018
    “…This paper reports the result obtained by implementing Gravitational Search Algorithm for tuning Stereo Matching Algorithm’s parameters for the application star fruit inspection system. …”
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    Article
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    A soft hierarchical algorithm for the clustering of multiple bioactive chemical compounds by Salim, Naomie, Shah, J. Z.

    Published 2007
    “…In this work a fuzzy hierarchical algorithm is developed which provides a mechanism not only to benefit from the fuzzy clustering process but also to get advantage of the multiple membership function of the fuzzy clustering. …”
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    Book Section
  18. 18

    A review: accuracy optimization in clustering ensembles using genetic algorithms by Ghaemi, Reza, Sulaiman, Md. Nasir, Ibrahim, Hamidah, Mustapha, Norwati

    Published 2011
    “…This paper concludes that using genetic algorithms in clustering ensemble improves the clustering accuracy and addresses open questions subject to future research.…”
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    Article
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    An Optimized PID Parameters for LFC in Interconnected Power Systems Using MLSL Optimization Algorithm by Najeeb, Mushtaq, Shahooth, Mohammed, Mohaisen, Arrak, Ramdan, Razali, Hamdan, Daniyal

    Published 2016
    “…In order to enhance the dynamic performance, the optimal parameters of the PID scheme which optimized by the proposed MLSL algorithm are compared with that one’s obtained by GA algorithm. …”
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    Article