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mining algorithm » cosine algorithm (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
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101
Predictive Model of Psychoactive Drugs Consumption using Classification Machine Learning Algorithms
Published 2023“…Our study aimed to use data mining classification techniques, in order to classify the individual into two categories: user or non-user. …”
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102
RHEEMix in the data jungle: a cost-based optimizer for cross-platform systems.
Published 2020“…Our main contributions are: (i) a mechanism based on graph transformations to explore alternative execution strategies; (ii) a novel graph-based approach to determine efficient data movement plans among subtasks and platforms; and (iii) an efficient plan enumeration algorithm, based on a novel enumeration algebra. …”
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A new family of multi-step quasi-Newton algorithms for unconstrained optimization
Published 1999“…It concentrates on deriving a variable-metric family of minimum curvature algorithms for unconstrained optimization. The derivation is based on considering a rational model, with a certain tuning parameter, where the aim is to develop a general framework that encompasses all possible two-step minimum curvature algorithms generated by appropriate parameter choices. …”
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Deep Learning-Based Short-Term Load Forecasting Approach in Smart Grid With Clustering and Consumption Pattern Recognition
Published 2021“…A k-Medoid based algorithm is employed for clustering whereas the forecasting models are generated for different clusters of load profiles. …”
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108
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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Development of multivariable PID controller gains in presence of measurement noise
Published 2017“…The development of the proposed optimal algorithm is based on minimising a stochastic performance index in presence of erroneous initial conditions, white measurement noise, and white process noise. …”
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111
Environmental/economic power dispatch using multiobjective evolutionary algorithms: a comparative study
Published 2003“…A comparative study of newly developed Pareto-based multiobjective evolutionary algorithms (MOEA) applied to a nonlinear power system multiobjective optimization problem is presented in this paper. …”
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112
Topology design of switched enterprise networks using a fuzzy simulated evolution algorithm
Published 2020“…In this paper, we present an approach based on Simulated Evolution algorithm for the design of SEN topology. …”
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113
Topology design of switched enterprise networks using a fuzzy simulated evolution algorithm
Published 2020“…In this paper, we present an approach based on Simulated Evolution algorithm for the design of SEN topology. …”
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114
Stochastic management of hybrid AC/DC microgrids considering electric vehicles charging demands
Published 2020“…A novel evolving solution based on flower pollination algorithm is also proposed to solve the problem optimally. …”
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115
Developing an online hate classifier for multiple social media platforms
Published 2020“…While all the models significantly outperform the keyword-based baseline classifier, XGBoost using all features performs the best (F1 = 0.92). …”
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Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks
Published 2025“…This work identifies the most reliable machine learning (ML) strategies for forecasting corrosion inhibitor efficiency before synthesis, thereby shortening development cycles and reducing experimental cost. Drawing on more than fifteen harmonized datasets that span pyrimidines, ionic liquids, graphene oxides, and additional compound families, we benchmark traditional algorithms, such as artificial neural networks, support vector machines, k-nearest neighbors, random forests, against advanced graph-based and deep architectures including three-level directed message-passing neural networks, 2D3DMol-CIC, and graph convolutional networks. …”
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