Search Results - (( learning systematic learning algorithm ) OR ( java simulation optimization algorithm ))
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Application of deep learning algorithms in lung sound classification: A systematic review since 2015
Published 2025“…The article’s thorough analysis revealed that deep learning algorithms have outperformed traditional machine learning techniques in lung sound classification.…”
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Machine learning algorithms on price and rent predictions in real estate: A systematic literature review / Muhamad Harussani Abdul Salam ... [et al.]
Published 2022“…This study will provide new insights on the Machine Learning Algorithms in the real estate industry.…”
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Loan default prediction using machine learning algorithms: a systematic literature review 2020 -2023
Published 2024“…This study conducts a systematic literature review (SLR) on the prediction of loan defaults using machine learning algorithms (MLAs) from 2020 to 2023. …”
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A Systematic Literature Review of Machine Learning Methods for Short-term Electricity Forecasting
Published 2023“…Forecasting; Investments; Machine learning; Development investment; Energy prediction; Evaluation metrics; Long term planning; Machine learning methods; Metric evaluation; Resource planning; Systematic literature review; Learning algorithms…”
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A Systematic Review Of Machine Learning Algorithms For Mental Health Detection Using Social Media Data
Published 2026journal::journal article -
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A systematic review of machine learning techniques and applications in soil improvement using green materials
Published 2023“…The current study aims to comprehensively evaluate recent breakthroughs in machine learning algorithms for soil improvement using a systematic procedure known as PRISMA and meta-analysis. …”
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Deep learning convolutional neural network algorithms for the early detection and diagnosis of dental caries on periapical radiographs: a systematic review
Published 2021“…Studies published from 2015 to 2021 under the keywords (deep convolutional neural network) AND (caries), (deep learning caries) AND (convolutional neural network) AND (caries) were systematically reviewed. …”
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A Recent Research on Malware Detection Using Machine Learning Algorithm: Current Challenges and Future Works
Published 2023“…Barium compounds; Cybersecurity; Data mining; Decision trees; Evolutionary algorithms; K-means clustering; Learning algorithms; Malware; Network security; Sodium compounds; Support vector machines; 'current; Comparatives studies; Cyber security; K-means; Machine learning algorithms; Malware attacks; Malware detection; Metaheuristic; Recent researches; Systematic literature review; Nearest neighbor search…”
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Assessing the efficacy of machine learning algorithms for syncope classification: A systematic review
Published 2024“…The aims of the study were to systematically evaluate available machine learning (ML) algorithm for supporting syncope diagnosis to determine their performance compared to existing point scoring protocols. …”
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A systematic review of machine learning techniques and applications in soil improvement using green materials
Published 2023“…The current study aims to comprehensively evaluate recent breakthroughs in machine learning algorithms for soil improvement using a systematic procedure known as PRISMA and meta-analysis. …”
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…The simulation is implemented with iFogSim and java programming language. …”
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Machine Learning Algorithm for Malware Detection: Taxonomy, Current Challenges, and Future Directions
Published 2024“…This paper seeks to conduct a thorough systematic literature review (SLR) and offer a taxonomy of machine learning methods for malware detection that considers these problems by analyzing 77 chosen research works related to malware detection using machine learning algorithm. …”
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Deep learning algorithms for personalized services and enhanced user experience in libraries: a systematic review / Haziah Sa’ari, Mohd Dasuki Sahak and Stan Skrzeszewskis
Published 2023“…The integration of deep learning (DL) algorithms in library settings engenders a multitude of challenges and complexities, encompassing unintended ramifications, ethical quandaries, a dearth of specialized literature elucidating DL in library contexts, the intricacies of dataset selection and human intervention, and the inherent limitations when juxtaposed with the remarkable cognitive capabilities of the human brain. …”
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Meta-Heuristic Algorithms for Learning Path Recommender at MOOC
Published 2021“…Streamlining the order of courses to create a well-defined learning path can help e-learners achieve their learning goals effectively and systematically. …”
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Assessment and Evaluation of Different Machine Learning Algorithms for Predicting Student Performance
Published 2023“…Decision trees; Learning algorithms; Nearest neighbor search; Neural networks; Students; Support vector machines; Academic achievements; Effective tool; Key feature; Large volumes; Machine learning algorithms; Machine learning approaches; Student performance; Systematic searches; Tertiary institutions; Top qualities; Forecasting; algorithm; Bayes theorem; human; machine learning; student; support vector machine; Algorithms; Bayes Theorem; Humans; Machine Learning; Neural Networks, Computer; Students; Support Vector Machine…”
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Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing
Published 2011“…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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Deep learning algorithms for personalized services and enhanced user experience in libraries
Published 2023“…The integration of deep learning (DL) algorithms in library settings engenders a multitude of challenges and complexities, encompassing unintended ramifications, ethical quandaries, a dearth of specialized literature elucidating DL in library contexts, the intricacies of dataset selection and human intervention, and the inherent limitations when juxtaposed with the remarkable cognitive capabilities of the human brain. …”
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Depression Detection Based on Features of Depressive Behaviour Through Social Media Analytic: A Systematic Literature Review
Published 2024Subjects:Conference Paper
