Search Results - (( weight distribution free algorithm ) OR ( parameter estimation mining algorithm ))

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  1. 1
    Tree-based contrast subspace mining method

    Tree-based contrast subspace mining method by Florence Sia Fui Sze

    Published 2020
    “…Hence, this thesis presents the optimization of parameters values for the tree-based method by genetic algorithm. …”
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  2. 2
    Expectation maximization clustering algorithm for user modeling in web usage mining system

    Expectation maximization clustering algorithm for user modeling in web usage mining system by Mustapha, Norwati, Jalali, Manijeh, Jalali, Mehrdad

    Published 2009
    “…In this study we advance a model for mining of user’s navigation pattern. The model is based on expectation-maximization (EM) algorithm and it is used for finding maximum likelihood estimates of parameters in probabilistic models, where the model depends on unobserved latent variables. …”
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  3. 3
    A firefly algorithm based hybrid method for structural topology optimization

    A firefly algorithm based hybrid method for structural topology optimization by Gebremedhen, H.S., Woldemichael, D.E., Hashim, F.M.

    Published 2020
    “…The lower and upper limit of design variables (0 and 1) were used to find initial material distribution to initialize the firefly algorithm based section of the hybrid algorithm. …”
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  4. 4
    Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets

    Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets by Saeed, Sana

    Published 2019
    “…For its fast convergence and for its efficient search procedure, the self-adaptation is proposed in the parameters of the proposed hybrid algorithm. The effectiveness of this algorithm is verified by applying it on the unconstrained and constrained test functions through a simulation study. …”
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  5. 5
    Peak pressure analysis of foot plantar distribution based on image processing algorithm

    Peak pressure analysis of foot plantar distribution based on image processing algorithm by Sabry, Ali Hussein

    Published 2018
    “…The other main goal of this work is to create an algorithm which has the ability to formulate accurately and reliably the distribution of pressure over the foot plantar. …”
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  6. 6
    Optimized range-free localization scheme using autonomous groups particles swarm optimization for anisotropic wireless sensor networks

    Optimized range-free localization scheme using autonomous groups particles swarm optimization for anisotropic wireless sensor networks by Han, Fengrong, Izzeldin, Ibrahim Mohamed Abdelaziz, Kamarul Hawari, Ghazali, Zhao, Yue, Li, Ning

    Published 2023
    “…Distance Vector-Hop (DV-Hop) algorithm as the most typical range-free localization scheme is more suitable for large-scaled WSNs. …”
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  7. 7
    Development an accurate and stable range-free localization scheme for anisotropic wireless sensor networks

    Development an accurate and stable range-free localization scheme for anisotropic wireless sensor networks by Han, Fengrong

    Published 2022
    “…Accordingly, this study aspires to bridge the research gap by exploring a new DV-Hop algorithm to build a fast, costefficient, strong range-free localization scheme. …”
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  8. 8
    Performance analysis of machine learning algorithms for missing value imputation

    Performance analysis of machine learning algorithms for missing value imputation by Ismail, Amelia Ritahani, Zainal Abidin, Nadzurah, Emran, Nurul Akmar

    Published 2018
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  9. 9
    Prediction of Temerloh River water level for prediction of flood using Artificial Neural Network (ANN) method

    Prediction of Temerloh River water level for prediction of flood using Artificial Neural Network (ANN) method by Muhamad Afiq, Mustafa

    Published 2015
    “…The purpose of this project is to research more about the flood occurrence in Temerloh, Pahang. The data mining approaches using artificial neural network (ANN) techniques will be use to conduct this research for flood estimation. …”
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  10. 10
    New synchronization protocol for distributed system with TCP extension

    New synchronization protocol for distributed system with TCP extension by Bayat, Peyman

    Published 2013
    “…In the worst condition, it optimized 3.99% higher than the most fault-tolerant previous works. The resulting algorithm does not involve variability in the hardware type nor is it based on specific distributed application software or databases. …”
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  11. 11
    Class binarization with self-adaptive algorithm to improve human activity recognition

    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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  12. 12
    Machine-learning-based adaptive distance protection relay to eliminate zone-3 protection under-reach problem on statcom-compensated transmission lines

    Machine-learning-based adaptive distance protection relay to eliminate zone-3 protection under-reach problem on statcom-compensated transmission lines by Aker, Elhadi Emhemed Alhaaj Ammar

    Published 2020
    “…This current study proposes an intelligent data mining approach for the Machine Learning- Adaptive Distance Relay (ML-ADR) fault classification model using novel extracted 1-cycle transient voltage and current signals hidden knowledge from both healthy and faulty lines parameters. …”
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  13. 13
    Performance analysis of machine learning algorithms for missing value imputation

    Performance analysis of machine learning algorithms for missing value imputation by Zainal Abidin, Nadzurah, Ismail, Amelia Ritahani, Emran, Nurul Akmar

    Published 2018
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  14. 14
    Robust Kernel Density Function Estimation

    Robust Kernel Density Function Estimation by Dadkhah, Kourosh

    Published 2010
    “…The second method attempts to define an approach that is useable not only for unimodal distribution but also for multimodal distribution. This approach incorporates robust weights, whereby, high weights and low weights are assigned to normal (clean) and outlying observations, respectively. …”
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  15. 15
    Mining The Basic Reproduction Number (R0) Forecast For The Covid Outbreak

    Mining The Basic Reproduction Number (R0) Forecast For The Covid Outbreak by Rajogoval, Illayakantthan

    Published 2022
    “…Waikato Environment for Knowledge Analysis (WEKA) version 3.8 was adopted for data mining analysis at two levels of classification stages. …”
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    Monograph
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  16. 16
    Identification of debris flow initiation zones using topographic model and airborne laser scanning data

    Identification of debris flow initiation zones using topographic model and airborne laser scanning data by Lay, Usman Salihu, Pradhan, Biswajeet

    Published 2017
    “…MARSpline multivariate data mining predictive approach was implemented using morphometric indices and topographical derived parameter as independent variables. …”
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    Conference or Workshop Item
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  17. 17
    EEG-and MRI-based epilepsy source localization using multivariate empirical mode decomposition and inverse solution method

    EEG-and MRI-based epilepsy source localization using multivariate empirical mode decomposition and inverse solution method by Khosropanah, Pegah

    Published 2018
    “…Standardized Low Resolution Tomography (sLORETA) andWeighted Minimum Norm (WMN) are linear distributed inverse solutions which lead up to zero localization error using noise-free EEG, state-of-the-art feature extractor and realistic head model. …”
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  18. 18
    Dynamic investment model for the restructed power market in the presence of wind source

    Dynamic investment model for the restructed power market in the presence of wind source by Esfahani, Mohammad Tolou Askari Sedehi

    Published 2014
    “…In the third step, the long term optimal investment strategies of the hybrid wind-thermal investor are determined based on the dynamic programming algorithm by considering the long term states of demand growth and fuel price uncertainties. …”
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