Search Results - (( java implementation max algorithm ) OR ( parameters data normalization algorithm ))
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OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT
Published 2023“…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. The objectives of this work are: i) to provide a comprehensive review of the cloud and scheduling process; ii) to classify the scheduling strategies and scientific workflows; iii) to implement our proposed algorithm with various scheduling algorithms (i.e., Min-Min, Round-Robin, Max-Min, and Modified Max-Min) for performance comparison, within different cloudlet sizes (i.e., small, medium, large, and heavy) in three scientific workflows (i.e., Montage, Epigenomics, and SIPHT); and iv) to investigate the performance of the implemented algorithms by using CloudSim. …”
Review -
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Batch mode heuristic approaches for efficient task scheduling in grid computing system
Published 2016“…Many algorithms have been implemented to solve the grid scheduling problem. …”
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An alternative approach to normal parameter reduction algorithms for decision making using a soft set theory / Sani Danjuma
Published 2017“…Many normal parameter reduction algorithms exist to handle parameter reduction and maintain consistency of decision choices. …”
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Confidence intervals (CI) for concentration parameter in von Mises distribution and analysis of missing values for circular data / Siti Fatimah binti Hassan
Published 2015“…For example, the distribution analogues to the normal distribution in linear data is known as circular normal distribution. …”
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Smart diagnosis of long bone tumor / Mazni Parimin
Published 2005“…The data samples involve in this project are data that had been normalize and become the inputs of the prototype. …”
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Student Project -
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PSO and Linear LS for parameter estimation of NARMAX/NARMA/NARX models for non-linear data / Siti Muniroh Abdullah
Published 2017“…Results suggest that the PSO algorithm is viable alternative to other established algorithms for LLS parameter estimation. …”
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7
Dynamic robust bootstrap method based on LTS estimators
Published 2009“…In order to make reliable inferences about the parameters of a model, require that the parameter estimates are normally distributed. …”
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The normalized random map of gradient for generating multifocus image fusion
Published 2020“…The proposed algorithm successes to supersede difficulties of mathematical equations and algorithms. …”
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Smart energy meter with adaptive communication data transfer algorithm for electrical energy monitoring
Published 2021“…Thus, in this thesis, a new Smart Energy Meter (SEM) with adaptive data transfer algorithm is designed to accommodate the problem. …”
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10
Simulation algorithm of bayesian approach for choice-conjoint model
Published 2011“…Generally in Choice-Conjoint method the Multinomial Logit Model (MNL) is normally used to analyze choice conjoint data, but the MNL has some serious limitations. …”
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Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares
Published 2009“…One of the important assumptions of the linear model is that the error terms are normally distributed. Unfortunately, many researchers are not aware that the performance of the OLS can be very poor when the data set that one often makes a normal assumption, has a heavy-tailed distribution which may arise as a result of the presence of outliers. …”
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Statistical approach on grading: mixture modeling
Published 2006“…In the conditional Bayesian model, we assume the data to follow the Normal Mixture distribution where the grades are distinctively separated by the parameters: means and proportions of the Normal Mixture distribution. …”
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Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak
Published 2019“…Thus, this study proposes the development of algorithms to detect and classify jamming attacks using a set of parameters on the physical layer and MAC in MANET. …”
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Pairwise test suite generator tool based on harmony search algorithm (HS-PTSGT)
Published 2014“…From the comparison with other existing pairwise testing tools in term of size, it is shown that the strategy used in HS PTSGT can effectively generate optimum test suite with minimized test data and performed better on certain parameter size.…”
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Undergraduates Project Papers -
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SG-PBFS : Shortest Gap-Priority Based Fair Scheduling technique for job scheduling in cloud environment
Published 2024“…To conduct this experiment, we employed the CloudSim simulator, which is implemented using the Java programming language.…”
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Adaptive policing and shaping algorithms on inbound traffic using generalized Pareto distribution / Nor Azura Ayop
Published 2016“…Log likelihood estimation technique is used to fit the best 2-parameter CDF compared to Weibull, Normal and Rician distribution model. …”
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Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah
Published 2015“…Two important Weibull parameters which are shape and scale are measured. Based on the identified statistical parameters, a new Time Based Policing and Shaping algorithm is developed and simulated. …”
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Estimating Crack Effects on Electrical Characteristics of PV Modules Based on Monitoring Data and I-V Curves
Published 2024“…This study presents an approach to investigate microcrack effects on the output characteristics of photovoltaic (PV) modules based on a theoretical model that is derived from the equivalent single-diode model through monitoring data and current-voltage (I-V) curves. Meanwhile, an innovative parameter optimization algorithm based on particle swarm optimization is developed to extract the parameters. …”
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Development of artificial neural network models for predicting lipid profile using smartMF electrical parameters / Ahmad Zulkhairi Zulkefli
Published 2021“…The data were divided into two categories for each lipid profile parameters, normal and abnormal. …”
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Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets
Published 2019“…For this purpose, the normal distributions are applied to each class. The parameters of this distribution are optimized by applying the proposed MOHA. …”
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