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boosting algorithm » cosine algorithm (Expand Search)
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boosting algorithm » cosine algorithm (Expand Search)
case scheduling » task scheduling (Expand Search), ahead scheduling (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
element » elements (Expand Search)
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Boosting the visibility of services in microservice architecture
Published 2023“…Our research also analyzed the boosting algorithms, namely Gradient Boost, XGBoost, LightGBM, and CatBoost to improve the overall performance. …”
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Efficient Dynamic Cost Scheduling Algorithm for Data Batch Processing
Published 2016Get full text
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Power-constrained system-on-a-chip test scheduling using a genetic algorithm
Published 2006“…This paper presents an efficient approach for the test scheduling problem of core-based systems based on a genetic algorithm. …”
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Optimized Load-Scheduling Algorithm for CubeSat's Electric Power System Management Considering Communication Link
Published 2023“…The solution obtained shows that the proposed scheduling algorithm meets the communication system's requirements while conserving power and energy resources.…”
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Efficient Prioritization and Processor Selection Schemes for HEFT Algorithm: A Makespan Optimizer for Task Scheduling in Cloud Environment
Published 2022“…Among these methods, the Heterogeneous Earliest Finish Time (HEFT) algorithm is recognized to produce optimal outcomes in a shorter time period for scheduling tasks in a heterogeneous environment. …”
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A Data-Driven Decision-Making Framework for Fleet Management in the Government Sector of Dubai
Published 2024“…The proposed framework comprises key elements: Important Decisions derived from interviews with transportation leaders, Knowledge Management enhanced by AI algorithms, Data Mining/Analysis utilizing historical data, the Fleet Management System employing Oracle ERP, and a Data-Driven Decision Support Framework that leans towards the extended framework approach. …”
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Bird’s Eye View feature selection for high-dimensional data
Published 2023“…This approach is inspired by the natural world, where a bird searches for important features in a sparse dataset, similar to how a bird search for sustenance in a sprawling jungle. BEV incorporates elements of Evolutionary Algorithms with a Genetic Algorithm to maintain a population of top-performing agents, Dynamic Markov Chain to steer the movement of agents in the search space, and Reinforcement Learning to reward and penalize agents based on their progress. …”
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A Fast and Robust Gas Recognition Algorithm Based on Hybrid Convolutional and Recurrent Neural Network
Published 2019“…The reported accuracy dramatically outperforms the previous algorithms, including gradient tree boosting (GTB), random forest (RF), support vector machine (SVM), k-nearest neighbor (KNN), and linear discriminant analysis (LDA). …”
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Optimal Management of Mobile Energy Generation and Storage Systems
Published 2018Get full text
doctoralThesis -
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Predicting Dropouts among a Homogeneous Population using a Data Mining Approach
Published 2019“…Our research relies solely on pre-college and college performance data available in the institutional database. Our research reveals that the Gradient Boosted Trees is a robust algorithm that predicts dropouts with an accuracy of 79.31% and AUC of 88.4% using only pre-enrollment data. …”
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Estimating Construction Project Duration Using a Machine Learning Algorithm
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Scalable Nonparametric Supervised Learning for Streaming and Massive Data: Applications in Healthcare Monitoring and Credit Risk
Published 2025“…Additionally, an online classifier is developed for streaming data, combining online PCA with a kernel-based recursive classifier using a stochastic approximation algorithm. …”
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Incremental Genetic Algorithm
Published 2006“…Classical Genetic Algorithms (CGA) are known to find good sub-optimal solutions for complex and intractable optimization problems. …”
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An efficient method for the open-shop scheduling problem using simulated annealing
Published 2016“…This paper presents a simulated annealing algorithm in order to solve the nonpreemptive open-shop scheduling problem with the objective of minimizing the makespan. …”
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A GRASP Approach for Solving Large-Scale Electric Bus Scheduling Problems
Published 2021“…The GRASP algorithm is used for case studies on several public transport systems having various properties and sizes. …”
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Oversampling techniques for imbalanced data in regression
Published 2024“…For such high-dimension data our approach outperforms the Synthetic Minority Oversampling Technique for Regression (SMOTER) algorithm for the IMDB-WIKI and AgeDB image datasets. …”
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Incremental & classical genetic algorithm. (c2001)
Published 2001Get full text
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masterThesis