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Empirical comparison of regression test selection algorithms
Published 2001“…In the maintenance phase, the regression test selection problem refers to selecting test cases from the initial suite of test cases used in the development phase. …”
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Arabic Text Classification Using Modified Artificial Bee Colony Algorithm for Sentiment Analysis: The Case of Jordanian Dialect
Published 2022“…The second phase, modified the Artificial Bee Colony (ABC) Algorithm, with Upper Confidence Bound (UCB) Algorithm, to promote the exploitation ability for the minimum dimension, to get the minimum number of the optimal feature, then using forward feature selection strategy by four classifiers of machine learning algorithms: (K-Nearest Neighbors (KNN), Support vector machines (SVM), Naïve-Bayes (NB), and Polynomial Neural Networks (PNN). …”
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A non-convex economic load dispatch problem using chameleon swarm algorithm with roulette wheel and Levy flight methods
Published 2023“…An Enhanced Chameleon Swarm Algorithm (ECSA) by integrating roulette wheel selection and Lévy flight methods is presented to solve non-convex Economic Load Dispatch (ELD) problems. …”
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Intelligent Bilateral Client Selection in Federated Learning Using Game Theory
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Efficient Prioritization and Processor Selection Schemes for HEFT Algorithm: A Makespan Optimizer for Task Scheduling in Cloud Environment
Published 2022“…Therefore, here we propose modified versions of the HEFT algorithm that can obtain improved results. In the rank generation phase, we implement different methodologies for calculating ranks, while in the processor selection phase, we modify the way of selecting idle slots for scheduling the tasks. …”
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A flexible genetic algorithm-fuzzy regression approach for forecasting: The case of bitumen consumption
Published 2019“…This study aims to introduce a flexible genetic algorithm-fuzzy regression approach for forecasting the future bitumen consumption. …”
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Calibration of building model based on indoor temperature for overheating assessment using genetic algorithm: Methodology, evaluation criteria, and case study
Published 2022“…It was found that the calibrated model achieved these metrics with RMSE of 0.3 ◦C, and MAD of 0.8 ◦C, and 85% of data points with an error less than 0.5 ◦C for a school building case.…”
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Regression test selection for trusted database applications
Published 2006“…Our proposed algorithms automate an important portion of the regression testing process, and they operate more efficiently than most other regression test selection algorithms. …”
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Con-Detect: Detecting adversarially perturbed natural language inputs to deep classifiers through holistic analysis
Published 2023“…Deep Learning (DL) algorithms have shown wonders in many Natural Language Processing (NLP) tasks such as language-to-language translation, spam filtering, fake-news detection, and comprehension understanding. …”
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Con-Detect: Detecting Adversarially Perturbed Natural Language Inputs to Deep Classifiers Through Holistic Analysis
Published 2023“…<p>Deep Learning (DL) algorithms have shown wonders in many Natural Language Processing (NLP) tasks such as language-to-language translation, spam filtering, fake-news detection, and comprehension understanding. …”
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A Multistage Passive Islanding Detection Method for Synchronous-Based Distributed Generation
Published 2021“…One of the key requirements for the proposed algorithm was that easy cases should be flagged as soon as possible; this property was confirmed by the observation that most events ( ≈ 79%) were detected within 10–20 ms, while at the same time retaining a very high detection rate overall cases ( >99 %).…”
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Four-dimensional representation and collision detection for movingobjects
Published 1998“…The problem is then posed as a nonlinear programming problem. The algorithm can handle the case of a rigid body moving on a general path in 2 or 3 with simultaneous translation and rotation. …”
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Anomaly Detection Based Framework for Profile Monitoring
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A hybrid genetic algorithm for task allocation in multicomputers
Published 2018“…A hybrid genetic algorithm for the task allocation problem (HGATA) in multicomputers is presented. …”
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Detection of statistically significant network changes in complex biological networks
Published 2017“…When applied to detect the main differences between the networks of IDH-mutant and IDH-wild-type glioma tumors, it correctly selects sub-networks centered on important key regulators of these two different subtypes. …”