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method algorithm » mould algorithm (Expand Search)
forest algorithm » firefly algorithm (Expand Search)
data scheduling » task scheduling (Expand Search), ahead scheduling (Expand Search)
method algorithm » mould algorithm (Expand Search)
forest algorithm » firefly algorithm (Expand Search)
data scheduling » task scheduling (Expand Search), ahead scheduling (Expand Search)
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Efficient Dynamic Cost Scheduling Algorithm for Data Batch Processing
Published 2016“…A Master of Science thesis in Engineering Systems Management by Alia Al Sadawi entitled, "Efficient Dynamic Cost Scheduling Algorithm for Data Batch Process," submitted in May 2016. …”
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Efficient Dynamic Cost Scheduling Algorithm for Financial Data Supply Chain
Published 2021“…An iterative dynamic scheduling algorithm (DCSDBP) was developed to address the data batching process. …”
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Stochastic Search Algorithms for Exam Scheduling
Published 2007“…Then, we empirically compare the three proposed algorithms and FESP using realistic data. Our experimental results show that SA and GA produce good exam schedules that are better than those of FESP heuristic procedure. …”
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Three-phase approach for curriculum-based course timetabling problem. (c2012)
Published 2012Subjects: “…Scheduling -- Data processing…”
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Proactive Fault Tolerance and Minimizing Task Execution Failure in A Cloud Data Center
Published 2024Subjects: Get full text
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Three-phase simulated annealing algorithms for exam scheduling
Published 2003“…We empirically compare 3PSA with a 4-phase clustering-based heuristic algorithm using realistic data. Our experimental results show that 3PSA produces good exam schedules, which are better than those of the clustering heuristic procedure.…”
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Simulated annealing and genetic algorithms for exam scheduling. (c1997)
Published 1997Get full text
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A Scatter search algorithm for exam scheduling. (c2006)
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Delay Optimization in LoRaWAN by Employing Adaptive Scheduling Algorithm With Unsupervised Learning
Published 2023Subjects: -
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A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method
Published 2022“…Due to a limited training dataset, an ML-based IDS generates a higher false detection ratio and encounters data imbalance issues. To deal with the data-imbalance issue, this research develops an efficient hybrid network-based IDS model (HNIDS), which is utilized using the enhanced genetic algorithm and particle swarm optimization(EGA-PSO) and improved random forest (IRF) methods. …”
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Optimizing Energy Consumption of Cloud Computing IaaS
Published 2017Subjects: Get full text
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Predict Student Success and Performance factors by analyzing educational data using data mining techniques
Published 2022“…The research study is performed as experimental analysis and develop models from nine machine learning algorithms including KNN, Naïve Bayes, SVM, Logistic regression, Decision Tree, Random forest, Adaboost, Bagging Classifier, and voting Classifier. …”
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A Novel Partitioned Random Forest Method-Based Facial Emotion Recognition
Published 2025“…A range of machine learning (ML) methods can be used to recognize facial expressions based on data from small to large datasets. Random Forest (RF) is simpler and more efficient than other ML algorithms. …”
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Random Forest Bagging and X‐Means Clustered Antipattern Detection from SQL Query Log for Accessing Secure Mobile Data
Published 2021“…<p dir="ltr">In the current ongoing crisis, people mostly rely on mobile phones for all the activities, but query analysis and mobile data security are major issues. Several research works have been made on efficient detection of antipatterns for minimizing the complexity of query analysis. …”
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On-site workshop investment problem: A novel mathematical approach and solution procedure
Published 2023Subjects: -
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A Novel Big Data Classification Technique for Healthcare Application Using Support Vector Machine, Random Forest and J48
Published 2022“…This was done by studying the performance of three well-known classification algorithms Random Forest Classifier (RFC), Support Vector Machine (SVM), and Decision Tree-J48 (J48), to predict the probability of heart attack. …”
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Power System Transient Stability Assessment Based on Machine Learning Algorithms and Grid Topology
Published 2023“…In this study, the emergency control algorithms based on ensemble machine learning algorithms (XGBoost and Random Forest) were developed for a low-inertia power system. …”
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Extended Behavioral Modeling of FET and Lattice-Mismatched HEMT Devices
Published 2016Subjects: Get full text
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