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modeling algorithm » scheduling algorithm (Expand Search)
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element » elements (Expand Search)
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An Ultrafast Maximum Power Point Setting Scheme for Photovoltaic Arrays Using Model Parameter Identification
Published 2015“…Subsequently a simple but effective global MPPT algorithm is proposed to track the MPP in the overallP-Icurve obtained from the identified PV array model, ensuring that the converter works at the MPP. …”
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Metaheuristic Algorithm for State-Based Software Testing
Published 2018“…This article presents a metaheuristic algorithm for testing software, especially web applications, which can be modeled as a state transition diagram. …”
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Delay Optimization in LoRaWAN by Employing Adaptive Scheduling Algorithm With Unsupervised Learning
Published 2023“…This paper aims to optimize the delay in LoRaWAN by using an Adaptive Scheduling Algorithm (ASA) with an unsupervised probabilistic approach called Gaussian Mixture Model (GMM). …”
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Spectrum Sensing Algorithms for Cooperative Cognitive Radio Networks
Published 2010Get full text
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Scatter search for homology modeling
Published 2016“…Homology modeling is an effective technique in protein structure prediction (PSP). …”
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Efficient Dynamic Cost Scheduling Algorithm for Data Batch Processing
Published 2016Get full text
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Correlation Clustering with Overlaps
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Efficient Dynamic Cost Scheduling Algorithm for Financial Data Supply Chain
Published 2021“…The developed algorithm proved effective by testing it on an illustrative network. …”
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Efficient heuristic algorithms for influence propagation in social networks. (c2018)
Published 2018“…Our experiments on a variety of social (sub) networks show that our algorithms can almost always manage to extract a small set of influencers through which we can effectively propagate a message throughout the whole network.…”
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Using Machine Learning Algorithms to Forecast Solar Energy Power Output
Published 2025“…Due to the variability of solar energy, the forecasting window is an important aspect of solar energy forecasting that must be integrated into any machine learning model. This study evaluates the suitability of selected machine learning (ML) models comprising Linear Regression, Decision Tree, Random Forest and XGBoost, which have been proven to be effective at forecasting. …”
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Forecasting the nearly unforecastable: why aren’t airline bookings adhering to the prediction algorithm?
Published 2021“…Research results indicate that algorithmic approaches in competitive industries must account for shifting customer preferences, changes to the travel environment, and confounding business effects rather than relying solely on historical data.…”
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NOVEL STACKING CLASSIFICATION AND PREDICTION ALGORITHM BASED AMBIENT ASSISTED LIVING FOR ELDERLY
Published 2022“…The experimental outcomes demonstrate the proposed MCFS, NCA, and NSCP algorithms work more effectively than previous feature selection, clustering and classification algorithms, respectively, in terms of accuracy, sensitivity, specificity, precision, recall, f-measure and execution time. …”
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Multi-Objective Co-optimization of Power and Gas under Uncertainties with P2H embedded
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UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data
Published 2024“…To improve the effectiveness and efficiency of the UniBFS algorithm, Redundant Features Elimination algorithm (RFE) is presented in this paper. …”
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Stochastic management of hybrid AC/DC microgrids considering electric vehicles charging demands
Published 2020“…In order to model the uncertainty effects, a data-driven framework based on point estimate method and support vector machine is developed. …”
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The automation of the development of classification models and improvement of model quality using feature engineering techniques
Published 2023“…<p>Recently pipelines of machine learning-based classification models have become important to codify, orchestrate, and automate the workflow to produce an effective machine learning model. …”