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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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DG-Means – A Superior Greedy Algorithm for Clustering Distributed Data
Published 2022“…In this work, we present DG-means, which is a greedy algorithm that performs on distributed sets of data. …”
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NOVEL STACKING CLASSIFICATION AND PREDICTION ALGORITHM BASED AMBIENT ASSISTED LIVING FOR ELDERLY
Published 2022“…This study's dataset was sourced from the Kaggle machine learning repository, and it refers to data gathering from wearable IoT devices. …”
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A Data-Driven Decision-Making Framework for Fleet Management in the Government Sector of Dubai
Published 2024“…My research aims to develop a data-driven decision support framework for fleet management, focusing on leveraging advanced algorithms, including decision trees and random forests, to generate domain-specific AI models. …”
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An Effective Hybrid NARX-LSTM Model for Point and Interval PV Power Forecasting
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Using genetic algorithms to optimize software quality estimation models
Published 2004“…In the first approach, we assume the existence of several models, and we use a genetic algorithm to combine them, and adapt them to a given data set. …”
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Second-order conic programming for data envelopment analysis models
Published 2022“…This paper constructs a second-order conic optimization problem unifying several DEA models. Moreover, it presents an algorithm that solves the former problem, and provides a MATLAB function associated with it. …”
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The automation of the development of classification models and improvement of model quality using feature engineering techniques
Published 2023“…In this article, we propose a framework that combines feature engineering techniques such as data imputation, transformation, and class balancing to compare the performance of different prediction models and select the best final model based on predefined parameters. …”
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UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data
Published 2024“…<p>Feature selection (FS) is a crucial technique in machine learning and data mining, serving a variety of purposes such as simplifying model construction, facilitating knowledge discovery, improving computational efficiency, and reducing memory consumption. …”
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A Novel Hybrid Genetic-Whale Optimization Model for Ontology Learning from Arabic Text
Published 2019“…Second, a hybrid genetic-whale optimization algorithm was proposed to optimize ontology learning from Arabic text. …”
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A Genetic Algorithm for Improving Accuracy of Software Quality Predictive Models
Published 2010“…In this paper, we present a genetic algorithm that adapts such models to new data. We give empirical evidence illustrating that our approach out-beats the machine learning algorithm C4.5 and random guess.…”
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Correlation Clustering with Overlaps
Published 2020“…Moreover, we allow the new vertex splitting operation, which allows the resulting clusters to overlap. In other words, data elements (or vertices) will be allowed to be members in more than one cluster instead of limiting them to only one single cluster, as in classical clustering methods. …”
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Using Machine Learning Algorithms to Forecast Solar Energy Power Output
Published 2025“…The data forecasting horizon used was a 24-h window in steps of 30 min. …”
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Predictive Model of Psychoactive Drugs Consumption using Classification Machine Learning Algorithms
Published 2023“…Eighteen classification models were built using different classification algorithms such as Gaussian Naive Bais, Logistic Regression, k-nearest neighbors, Random Forest, and Decision Tree. …”
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Time-varying volatility model equipped with regime switching factor: valuation of option price written on energy futures
Published 2025“…To determine the parameters of the regime switching model and identify when economic states change, we employ the EM algorithm, utilizing real gas futures price data. …”
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