Search Results - (( parallel distribution mining algorithm ) OR ( panel estimation using algorithm ))

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    Spacecraft sun-pointing using coplanar solar panels data and magnetic field measurements by Mohammad Abdelrahman, Mohammad Ibraheem

    Published 2013
    “…The proposed algorithm has been applied to EgyptSat-1. The satellite is switched from earth-pointing to sun-pointing mode using the estimated sun-vector. …”
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    Proceeding Paper
  3. 3

    Robust estimation methods for fixed effect panel data model having block-concentrated outliers by Abu Bakar @ Harun, Nor Mazlina

    Published 2019
    “…The Ordinary Least Squares (OLS) is the commonly used method to estimate the parameters of fixed effect panel data model. …”
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    Thesis
  4. 4

    Attitude and deformation coupled estimation of flexible satellite using low-cost sensors by Ghani, Marzieh, Assadian, Nima, Varatharajoo, Renuganth

    Published 2022
    “…The numerical results also demonstrate that including the flexibility model in the developed estimation equations enables the algorithm to successfully estimate the deformation at any solar panel location without the need for any conventional sensor that directly measures the strain and/or deformation.…”
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    Article
  5. 5

    Implementation of a modified incremental conductance MPPT algorithm with direct control based on a fuzzy duty cycle change estimator using dSPACE by Radjai, T., Rahmani, L., Mekhilef, Saad, Gaubert, J.P.

    Published 2014
    “…A fuzzy logic estimator (FLE) is used to estimate the new duty cycle used to track the PV array maximum power point. …”
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    Article
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    Performance analyses of various photovoltaic power plant based on local spectral irradiances in Malaysia using genetic algorithm by Lim, Song Wei

    Published 2023
    “…This project aims to measure the performances of various photovoltaic power plants in Malaysia based on local spectral irradiances using genetic algorithm. A Python computational model that uses genetic algorithms will be developed to estimate the optimal tilt angle and orientation angle as well as the solar power received for the solar sites. …”
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    Final Year Project / Dissertation / Thesis
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    Random sampling method of large-scale graph data classification by Rashed Mustafa, Mohammad Sultan Mahmud, Mahir Shadid

    Published 2024
    “…Mining a large number of graphs becomes a challenging task because state-of-the-art methods are not scalable due to the memory limit. …”
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    Article
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    Modeling and analysis of the impact of information and communication technology on household consumption expenditure in different regions by Fan, Chaozhi, Law, Siong Hook, Ibrahim, Saifuzzaman, Naseem, N. A. M.

    Published 2022
    “…Based on the panel data of cities and towns in China, by using the generalized estimation method of a dynamic panel, through the construction of regional household consumption expenditure evaluation models, optimize the impact evaluation algorithm of household consumption expenditure in different regions, standardize critic indicators, and build the impact modeling of household consumption expenditure in combination with relevant algorithms such as the Engel coefficient. …”
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    Article
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    Analysis and evaluation of various aspects of solar radiation in the Palestinian territories by Ismail M.S., Moghavvemi M., Mahlia T.M.I.

    Published 2023
    “…These coefficients were calculated using both MATLAB's fitting tool and genetic algorithm. …”
    Article
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    K Nearest Neighbor Joins And Mapreduce Process Enforcement For The Cluster Of Data Sets In Bigdata by Md Shah, Wahidah, Othman, Mohd Fairuz Iskandar, Hussian Hassan, Ali Abdul, Talib, Mohammed Saad, Mohammed, Ali Abdul Jabbar

    Published 2018
    “…K Nearest Neighbor Joins (KNN join) are regarded as highly primitive and expensive operations in the data mining.The efficient use of KNN join has proven good results in finding the objects from two data sets prevailed in the huge databases.This has been achieved with the combination of K-Nearest Neighbor query and join operation to find the distinct objects from different data sets.MapReduce is a newly introduced program with the combination of Map Procedure method and Reduce Method widely used in BigData.MapReduce is enriched with parallel distributed algorithm to find the results on a cluster of data sets in BigData.In this paper,the combination of KNN join and MapReduce methods are utilized on the cluster of data sets in BigData for knowledge discovery.Exploring the pinpoint data from huge data sets stored in Big Data demands the distributed large scale data processing.The present research paper is focusing on generic steps for KNN joins exploration operations on MapReduce.The operations of KNN Join are targeted to perform the data partitioning and data pre-processing and necessary calculations.By utilizing the combination of KNN joins with MapReduce methods on BigData data sets will demonstrate a solution for complex computational analysis. …”
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    Article
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    Analysis and evaluation of various aspects of solar radiation in the Palestinian territories by Ismail, M.S., Moghavvemi, Mahmoud, Mahlia, T.M.I.

    Published 2013
    “…These coefficients were calculated using both MATLAB's fitting tool and genetic algorithm. …”
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    Article
  13. 13

    Multi-objective optimization of stand-alone hybrid renewable energy system by genetic algorithm by Nejad, Mohsen Fadaee

    Published 2013
    “…HOGA, as a new effective tool for multi-objective optimization by evolutionary algorithm is used in this research. HOGA (Hybrid Optimization by Genetic Algorithms) is developed by Dr.Lopez from Zaragoza university in Spain. …”
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    Thesis
  14. 14

    Panel regression method to analyse the stock market returns due to Covid-19 / Nur Mardziah Aziz Jaafar and Noraini Noordin by Aziz Jaafar, Nur Mardziah, Noordin, Noraini

    Published 2021
    “…This study aimed to determine the aftereffects of COVID-19 pandemic outbreaks on stock markets by measuring the correlation between market returns and daily growth of total new and death cases of COVID-19. Panel regression methods, namely pooled ordinary least square and fixed-effect methods were used in this study where the dependent variable is stock market returns and independent variables were i) daily growth new death cases COVID-19 ii) natural algorithm market capitalisation iii) Brent Crude Oil Price from January 2, 2020, until March 31, 2020. …”
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    Article
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