Search Results - (( java implementation max algorithm ) OR ( programming based regression 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. …”
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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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A regression test case selection and prioritization for object-oriented programs using dependency graph and genetic algorithm
Published 2014“…This paper presents an evolutionary regression test case prioritization for object-oriented software based on dependence graph model analysis of the affected program using Genetic Algorithm. …”
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Software regression test case prioritization for object-oriented programs using genetic algorithm with reduced-fitness severity
Published 2015“…This paper propose an optimized regression test case selection and prioritization for object-oriented software based on dependence graph model analysis of the source code and optimized the selected test case using Genetic Algorithm. …”
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The effect of replacement strategies of genetic algorithm in regression test case prioritization of selected test cases
Published 2015“…Design-based regression testing approaches have been proposed to address changes at higher levels of abstraction, these approaches may not detect changes in the method body and several of the code based addresses procedural programs. …”
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Regression test case selection & prioritization using dependence graph and genetic algorithm
Published 2014“…Unfortunately, it is costly and time consuming to allow for the re-execution of all test cases during regression testing. The challenge in regression testing is the selection of best test cases from the existing test suite.This paper presents an evolutionary regression test case prioritization for object-oriented software based on extended system dependence graph model of the affected program using genetic algorithm. …”
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Modified zero inflated poisson regression analysis and its application to public health data
Published 2019“…This paper focuses on the programming of zero inflated Poisson regression (ZIPR) with combination of fuzzy regression method through SAS algorithm. …”
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Comparison between fuzzy bootstrap weighted multiple linear regression and multiple linear regression: a case study for oral cancer modelling
Published 2018“…Objectives: In this study, multiple linear regression model was calculated by using SAS programming language based on computational statistics which considered combination of robust regression, bootstrap, weighted data, Bayesian, and fuzzy regression method. …”
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Proceeding Paper -
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AI recommendation penetration testing tool for SQL injection: linear regression
Published 2025“…In conclusion, the objective of this project is success because the linear regression algorithm was able to be insert in the penetration testing framework.…”
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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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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…This merit is provided by balancing the exploitation of solution structure and exploration of its appropriate weighting factors through use of a robust and efficient optimization algorithm in learning process of GEP approach. To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
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A framework of test case prioritisation in regression testing using particle swarm-artificial bee colony algorithm
Published 2024“…The developed framework, grounded in fault-based testing theory, comprises three key components: inputs, prioritization factors, and a prioritization algorithm. …”
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The development of an automated pattern recognition based on neural network / Irni Hamiza Hamzah, Mohammad Nizam Ibrahim and Linda Mohd Kasim
Published 2006“…The selected neural network architecture is the Multilayer Perceptron (MLP) network, which is trained with three different types of learning algorithms, namely the Levenberg Marquardt (LM), Bayesian Regression (BR) and Gradient Descent (GDX). …”
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Three-term conjugate gradient method under Armijo line search for unemployment rate in Malaysia / Muhammad Fiqhi Zulkifli
Published 2023“…TTDY is the most effective method based on numerical results but only TTRMIL+ can be applied in regression analysis.…”
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