Search Results - (( panel estimation methods algorithm ) OR ( data distribution some algorithm ))

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

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

“…A controlled Cuk DC-DC converter was implemented and connected to a SunTech STP085B PV panel to verify the accuracy of the proposed method. …”
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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

“…Besides, the genetic algorithm has showed that it is an effective and efficient way to perform estimation of optimal tilt angle and orientation angle for solar sites with genetic algorithm as it is able to produce correct and accurate result in a short amount of time.…”
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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.

“…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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Dynamic replication algorithm in data grid: Survey by K. Madi, Mohammed, Hassan, Suhaidi

“…Data replication is a common method used to improve the performance of data access in distributed systems. …”
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A robust parameter estimation approach based on stochastic fractal search optimization algorithm applied to solar PV parameters by Rezk H., Babu T.S., Al-Dhaifallah M., Ziedan H.A.

Some families of count distributions for modelling zero-inflation and dispersion / Low Yeh Ching by Low, Yeh Ching

“…A popular distribution for the modelling of discrete count data is the Poisson distribution. …”
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COMPARATIVE PERFORMANCE OF SOME HYBRID HEURISTICS SCHEDULING ALGORITHMS BASED ON SLTR AND DEADLINE FOR COMPUTATIONAL GRID by AHMED ABBA, HARUNA

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Machine learning in botda fibre sensor for distributed temperature measurement by Nur Dalilla binti Nordin

“…To make the sensor more reliable, temperature data must be collected over the length of the cable, or distributed data rather than point data. …”

Analysis and evaluation of various aspects of solar radiation in the Palestinian territories by Ismail M.S., Moghavvemi M., Mahlia T.M.I.

“…Calculations of the optimized tilt and surface azimuth angles on monthly, seasonal and yearly basis were conducted, with the genetic algorithm being used for this purpose. Different PV tracking methods were also evaluated, taking into account the annual energy production. …”

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

“…Among these methods, Genetic Algorithm and Particle Swarm Optimization are known as two most effective methods for HRESs. …”
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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.

“…Calculations of the optimized tilt and surface azimuth angles on monthly, seasonal and yearly basis were conducted, with the genetic algorithm being used for this purpose. Different PV tracking methods were also evaluated, taking into account the annual energy production. …”
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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

“…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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Design and Implementation of Data-at-Rest Encryption for Hadoop by Wan Nor Shuhadah, Wan Nik, Mohamad Afendee, Mohamed, Zarina, Mohamad, Siti Hanisah, Kamaruzaman

“…It is shown that the implementation of AES encryption algorithm is capable to secure data stored in HDFS to some extent.…”
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Design and Implementation of Data-at-Rest Encryption for Hadoop by Wan Nor Shuhadah, Wan Nik, Mohamad Afendee, Mohamed, Zarina, Mohamad, Siti Hanisah, Kamaruzaman

“…It is shown that the implementation of AES encryption algorithm is capable to secure data stored in HDFS to some extent.…”
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The Performance of Chlorophyll-a Distribution Estimation by Using Ratio Algorithm on Landsat-8 in Sungai Merbok Estuary / Jesse Vince Rabing ... [et al.] by Rabing, Jesse Vince, Abd.Aziz, Khairul Naim, Kamaruddin, Sharir Aizat, Roslani, Muhammad Akmal, Tajam, Jamil, Ahmad, Aziani, Nazri, Rosnani, Zainol, Zamzila Erdawati, Ramli, Rohayu, Shaari, Mohd Idrus

“…This study explores the applicability of ratio algorithms for estimation of the chl- a concentration at Sungai Merbok by assessing chl-a distribution pattern built by the algorithms and evaluating each algorithm for their errors compared to in-situ data. …”
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A simulation study of a parametric mixture model of three different distributions to analyze heterogeneous survival data by Mohammed, Yusuf Abbakar, Yatim, Bidin, Ismail, Suzilah

“…In this paper a simulation study of a parametric mixture model of three different distributions is considered to model heterogeneous survival data.Some properties of the proposed parametric mixture of Exponential, Gamma and Weibull are investigated.The Expectation Maximization Algorithm (EM) is implemented to estimate the maximum likelihood estimators of three different postulated parametric mixture model parameters.The simulations are performed by simulating data sampled from a population of three component parametric mixture of three different distributions, and the simulations are repeated 10, 30, 50, 100 and 500 times to investigate the consistency and stability of the EM scheme.The EM Algorithm scheme developed is able to estimate the parameters of the mixture which are very close to the parameters of the postulated model.The repetitions of the simulation give parameters closer and closer to the postulated models, as the number of repetitions increases, with relatively small standard errors.…”
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Solving the vehicle routing problem with stochastic demands via hybrid genetic algorithm-tabu search by Ismail, Zuhaimy, Irhamah, Irhamah

“…The relative performance of the proposed HGATS is compared to each GA and TS alone, on a set of randomly generated problems following some discrete probability distributions. The problem data are inspired by real case of VRPSD in waste collection. …”
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Survey on job scheduling mechanisms in grid environment by S. M., Argungu, Che Mohamed Arif, Ahmad Suki, Omar, Mohd Hasbullah

“…Grid systems provide geographically distributed resources for both computational intensive and data-intensive applications.These applications generate large data sets.However, the high latency imposed by the underlying technologies; upon which the grid system is built (such as the Internet and WWW), induced impediment in the effective access to such huge and widely distributed data.To minimize this impediment, jobs need to be scheduled across grid environments to achieve efficient data access.Scheduling multiple data requests submitted by grid users onto the grid environment is NP-hard.Thus, there is no best scheduling algorithm that cuts across all grids computing environments.Job scheduling is one of the key research area in grid computing.In the recent past many researchers have proposed different mechanisms to help scheduling of user jobs in grid systems.Some characteristic features of the grid components; such as machines types and nature of jobs at hand means that a choice needs to be made for an appropriate scheduling algorithm to march a given grid environment.The aim of scheduling is to achieve maximum possible system throughput and to match the application needs with the available computing resources.This paper is motivated by the need to explore the various job scheduling techniques alongside their area of implementation.The paper will systematically analyze the strengths and weaknesses of some selected approaches in the area of grid jobs scheduling.This helps researchers better understand the concept of scheduling, and can contribute in developing more efficient and practical scheduling algorithms.This will also benefit interested researchers to carry out further work in this dynamic research area.…”
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A spawn mobile agent itinerary planning approach for energy-efficient data gathering in wireless sensor networks by Q. Qadori, Huthiafa, Ahmad Zulkarnain, Zuriati, Mohd Hanapi, Zurina, Subramaniam, Shamala

“…Moreover, each distributed MA has to carry the processing code (data aggregation code) to collect the sensory data and return back to the sink with the accumulated data. …”
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