Search Results - (( data distribution _ algorithm ) OR ( peer evaluation modified algorithm ))

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    A novel scheduling algorithm based on game theory and multicriteria decision making in LTE network by Hindia, M.N., Reza, A.W., Noordin, K.A.

    Published 2015
    “…On the first level, bankruptcy and shapely value algorithm fairly distribute the resources among smart grid applications. …”
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    Article
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    Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems by Shakeel Ahmed, Kamboh

    Published 2014
    “…To implement the parallel algorithms a distributed parallel computing laboratory using easily available low cost computers is setup. …”
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    Thesis
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    Predicting Customer Buying Decisions for Online Shopping with Unbalanced Data Set by Yap, Chau Tean

    Published 2022
    “…Weka, a data mining tool, provides the facility to classify the data set with different machine learning algorithms. …”
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    Final Year Project / Dissertation / Thesis
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    Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation by Ahmadipour, Masoud

    Published 2019
    “…Then, by means of the Slantlet Transform theory, the matrix data extraction for any decomposition level are computed and the best of them are selected as input data to feed to an effective classifier. …”
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    Thesis
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    Sustainable energy management: Artificial intelligence-based electricity consumption prediction in limited dataset environment for industry applications by Chuan, Zun Liang, Tan, Lit Ken, Wee, Angel Chi Chyin, Yim Hin, Tham, Shao, Jie Ong, Jia, Yi Low, Chong, Yeh Sai

    Published 2024
    “…Therefore, accurately predicting electricity consumption is crucial for economic management, security analysis, facility scheduling for generation and distribution, and maintenance planning. This study aimed to develop a modified stacked ensemble multivariable Artificial Intelligence (AI)-based predictive algorithm, specifically Stacked Simple Linear Regression and Multiple Linear Regression (SLR-MLR), and Stacked Simple Linear Regression and Multiple Non-Linear Regression (SLR-MNLR) utilizing the Cross Industry Standard Process for Data Mining (CRISP-DM) data science methodology. …”
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    Article
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    Dynamic robust bootstrap method based on LTS estimators by Midi, Habshah, Uraibi, Hassan Sami, Al-Talib, Bashar Abdul Aziz Majeed

    Published 2009
    “…We call this method Dynamic Robust Bootstrap-LTS based (DRBLTS) because here we have employed the LTS estimator in the modified bootstrap algorithm. The performance of the DRBLTS is evaluated by real data sets and simulation study. …”
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    Article
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    Dealing with Routing Hole Problem in Multi-hop Hierarchical Routing Protocol in Wireless Sensor Network by Sama, Najm Us

    Published 2019
    “…The challenging issue of routing protocols is to reduce the communication overhead for data transmission by determining an optimal path. …”
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    Thesis
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    Automatic generic process migration system in linux by Zarrabi, Amirreza

    Published 2012
    “…It introduces an intuitively appealing approach which facilitates dynamic load distribution, fault resilience, easy system administration, and data access locality. …”
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    Thesis
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    Parameter estimation of Kumaraswamy Burr type X models based on cure models with or without covariates by Yusuf, Madaki Umar

    Published 2017
    “…The two common types of cure fraction models, namely; mixture and the non-mixture models for the survival data based on the BKBX, KBX and BWB distributions were provided. …”
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    Thesis
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    Robust Kernel Density Function Estimation by Dadkhah, Kourosh

    Published 2010
    “…Finally this thesis also addresses the estimation of Mutual Information (MI) for mixture distribution which prone to create two distant groups in the data. …”
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    Thesis
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    Power prediction using the wind turbine power curve and data-driven approaches / Ehsan Taslimi Renani by Ehsan Taslimi , Renani

    Published 2018
    “…In this method, firstly, Weibull density function is utilized to model the wind speed and then several methods are applied to estimate the parameters of the wind speed distribution. To evaluate the performance of the Weibull parameters’ estimator methods, two sets of data are considered, one based on simulated data with different random variable size and the other based on actual data collected from a wind farm in Iran. …”
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    Thesis
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