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lacking algorithm » learning algorithms (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
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Variable Selection in Data Analysis: A Synthetic Data Toolkit
Published 2024“…Variable (feature) selection plays an important role in data analysis and mathematical modeling. This paper aims to address the significant lack of formal evaluation benchmarks for feature selection algorithms (FSAs). …”
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General applicability of genetic and simulated annealing algorithms for data mapping
Published 1995“…We experimentally analyze the general applicability of genetic algorithms (GA) and simulated annealing algorithms (SA) for mapping data to multicomputers. …”
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Properties of simulated annealing and genetic algorithms for mapping data to multicomputers
Published 1997“…We experimentally analyze some properties of simulated annealing algorithms (SA) and genetic algorithms (GA) for mapping data to multicomputers. …”
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Scalable parallel algorithms for dynamic programming on tree decomposition. (c2017)
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Social spider optimization algorithm: survey and new applications
Published 2024“…Based on gender, evolutionary factors simulate different behaviors usually found at their settlement based on the biological aspect. This survey studied the SSO and compared it with other PSO algorithms to find the best-performing algorithm based on a benchmark. …”
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An ant colony optimization algorithm to improve software quality prediction models
Published 2011“…However, building accurate prediction models is hard due to the lack of data in the domain of software engineering. …”
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Data-Driven Electricity Demand Modeling for Electric Vehicles Using Machine Learning
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Sentiment analysis for Arabizi in social media. (c2015)
Published 2015“…Yalla 7abibi, it is very useful to have a data mining tool that can analyze the sentiment of Twitter users in the Arab world. …”
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The use of multi-task learning in cybersecurity applications: a systematic literature review
Published 2024“…Cybersecurity has become vital in information technology, with data protection being a major priority. Despite government and corporate efforts, cybersecurity remains a significant concern. …”
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Diagnostic structure of visual robotic inundated systems with fuzzy clustering membership correlation
Published 2023“…Additionally, a clustering algorithm with a fuzzy membership function is implemented, allowing the robots to advance in accordance with predefined clusters and arrive at their starting place within a predetermined amount of time. …”
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Optimization of Commercially Off the Shelf (COTS) Electric Propulsion System for Low Speed Fuel Cell UAV
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Digital twin in energy industry: Proposed robust digital twin for power plant and other complex capital-intensive large engineering systems
Published 2022“…Data-driven algorithms with capabilities to predict the system’s dynamic behavior still need to be developed. …”
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A Robust Deep Learning Approach for Distribution System State Estimation with Distributed Generation
Published 2023“…Also, to evaluate the robustness of the algorithms, we test the neural network, without retraining it, on multiple scenarios with noisier data and bad data. …”
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An App for Navigating Patient Transportation and Acute Stroke Care in Northwestern Ontario Using Machine Learning: Retrospective Study
Published 2024“…The data were distributed for training (35%), testing (35%), and validation (30%) of the prediction model.…”
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Plant disease detection using drones in precision agriculture
Published 2023“…Color-infrared (CIR) images are the most preferred data used and field images are the main focus. The machine learning algorithm applied most is convolutional neural network (CNN). …”
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Sentiment Analysis of Dialectal Speech: Unveiling Emotions through Deep Learning Models
Published 2024“…Dialect Speech Sentiment Analysis is an evolutional field where machine learning algorithms are utilized to detect emotions in spoken language. …”
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Precision nutrition: A systematic literature review
Published 2021“…However, a systematic overview of the state-of-the-art on the use of machine learning in Precision Nutrition is lacking. Therefore, we carried out a Systematic Literature Review (SLR) to provide an overview of where and how machine learning has been used in Precision Nutrition from various aspects, what such machine learning models use as input features, what the availability status of the data used in the literature is, and how the models are evaluated. …”
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Multi Agent Reinforcement Learning Approach for Autonomous Fleet Management
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doctoralThesis