Search Results - "learning algorithm"

Intelligent secondary control for energy management in a micro-grid by using multi-agent system

Authors: Selseleh Jonban, Mansour

Contributors: University/Department: Universitat Politècnica de Catalunya. Departament d'Enginyeria Electrònica

Thesis Advisors: Romeral Martínez, José Luis

Source: TDX (Tesis Doctorals en Xarxa)

Subject Terms: Energy management system, Multi-agent system, Self-healing, Faulttolerance, Artificial intelligence, Subsumption architecture, Smart contract, Tendering process, First-price sealed-bid algorithm, Reinforcement learning, Markov decision process, C-means algorithm, Q-learning algorithm, Àrees temàtiques de la UPC::Enginyeria electrònica, Àrees temàtiques de la UPC::Energies, Àrees temàtiques de la UPC::Informàtica

Time: 621.3

File Description: application/pdf

Access URL: http://hdl.handle.net/10803/690063
https://dx.doi.org/10.5821/dissertation-2117-402147

Yoga practices effect on VCSS-based classification of patients with chronic venous insufficiency based on hybrid machine learning algorithms

Authors: Changhong Pan Lu Qi Lili Zhao et al.

Source: International Journal of Cognitive Computing in Engineering, Vol 6, Iss, Pp 255-266 (2025)

Subject Terms: Yoga practices, Venous clinical severity score, Decision Tree classifier, Electronic computers. Computer science, Science, Chronic venous insufficiency, QA75.5-76.95, Hybrid Machine Learning Algorithm

Access URL: https://doaj.org/article/094f4d3829df4bb496d23b86d20d4fbe

Determination of Alzheimer's Disease Stages by Artificial Learning Algorithms

Authors: Bulut, Nurgül Çakar, Tuna Arslan, İlker et al.

Source: International Journal of Statistics in Medical Research. 14:532-542

Subject Terms: Matplotlib 3.6.0, Adult, Explainable Artificial Intelligence, Scikit-Learn 1.1.3, Major Clinical Study, Neuropsychiatric Inventory, Deep Neural Network, Python Programming Language Version 3.10, Learning Algorithm, Alzheimer's Disease, Sensitivity and Specificity, Article, Machine Learning, Python Libraries Numpy 1.23.0, Artificial Intelligence, Alzheimer Disease, Controlled Study, Neuropathology, Artificial Learning Algorithm, Aged, Principal Component Analysis, Tensorflow 2.10, Nuclear Magnetic Resonance Imaging, Random Forest, Receiver Operating Characteristic, National Alzheimer's Coordinating Center, Depression, Bayesian Learning, Geriatric Depression Scale, Machine Learning Algorithm, Mini Mental State Examination, Decision Support System, Shapley Addictive Explanations, Statsmodel 0.13.5, Logistic Regression Analysis, Montreal Cognitive Assessment, Physician, Pandas 1.5.0, Diagnostic Test Accuracy Study, Cognitive Defect, XGBoost, Human

Access URL: https://hdl.handle.net/20.500.11779/3094
https://doi.org/10.6000/1929-6029.2025.14.50

Identification of protein biomarkers to differentiate between gram-negative and gram-positive infections in adults suspected of sepsis

Authors: Irani Shemirani, Mahnaz Pernestig, Anna-Karin Björkman, Jens et al.

Source: BMC Infectious Diseases. 25(1)

Subject Terms: Biomarkers, Diagnostics, Gram-negative bacteria, Gram-positive bacteria, Machine learning, Proteomics, Sepsis, biological marker, C reactive protein, procalcitonin, adult, algorithm, analytic method, area under the curve, Article, blood sampling, clinical article, cohort analysis, controlled study, diagnostic test accuracy study, enzyme linked immunosorbent assay, Escherichia coli, female, Gram negative sepsis, Gram positive bacterium, Gram positive infection, Haemophilus influenzae, human, Klebsiella pneumoniae infection, learning algorithm, leukocyte count, liquid chromatography-mass spectrometry, major clinical study, male, mass spectrometry, predictive value, principal component analysis, protein expression, Pseudomonas infection, quality control, random forest, retrospective study, sensitivity and specificity, Staphylococcus aureus, Streptococcus agalactiae, urea nitrogen blood level, diagnosis, Gram negative bacterium, Infection Biology, Infektionsbiologi

File Description: electronic

Access URL: https://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-26016
https://doi.org/10.1186/s12879-025-11973-5

A Deep Learning Approach for Tracking Colorectal Cancer-Derived Extracellular Vesicles in Colon and Lung Models

Authors: Chiabotto, Giulia Dumontel, Bianca Zilli, Luca et al.

Source: ACS Biomaterials Science & Engineering. 11:5343-5355

Subject Terms: colorectal cancer, extracellular vesicles, metastasis, deep learning algorithm, 2D and 3D models

File Description: application/pdf

Federated Deep Reinforcement Learning for ENDC Optimization

Authors: Adrian Martin Isabel de-la-Bandera Adriano Mendo et al.

Source: RIUMA. Repositorio Institucional de la Universidad de Málaga
Universidad de Málaga

Subject Terms: Optimization, Handover, Learning agent, Optimal network, Deep reinforcement learning algorithm, Network capacity, Federated learning, Heterogeneous network, Deep neural network, Small step, Deep reinforcement learning agent, Key performance indicators, Aprendizaje automático (Inteligencia artificial), Reinforcement learning algorithm, Training, Heuristic algorithms, Training phase, Training cell, Individual agency, Neighboring cells, Long term evolution, Deep reinforcement learning, 5 G NSA, Telecomunicaciones, Multi party computation, Hysteresis, Cell clusters, Rest of the cells, Reinforcement learning agent, Event B 1, Cellular networks, Deep learning, RAN Optimization, Rate of network, Throughput, 5 G Mobile communication, User equipment, Mobile edge computing

Access URL: https://hdl.handle.net/10630/38565

Multimedia Information Technology and Applications

Contributors: Kim, Byung-Gyu Sekiya, Hiroo Lee, Deokwoo

Subject Terms: Open Access, Machine Learning Algorithm, Mobile Information Processing Systems, Computer Vision Representations, Multimedia Information Systems, Artificial intelligence, Human Computer Interaction (HCI), Visualization, Theory and Algorithms for Application Domains, Graphical and digital media applications, Image processing, Virtual reality, Augmented reality (AR), Human–computer interaction

File Description: application/pdf

Relation: Communications in Computer and Information Science; Computer Science; Computer Science (R0)

Access URL: https://library.oapen.org/handle/20.500.12657/108690

Comparative analysis of regression models to predict the performance of the dual fuel engine operating on diesel and hydrogen gas

Authors: Priya S C. Feenita Uday Goel et al.

Source: International Journal of Hydrogen Energy. 141:585-597

Subject Terms: Regression Models, Machine Learning Algorithm, Dual Fuel Engine, Hydrogen

File Description: application/pdf

Access URL: https://hdl.handle.net/20.500.12713/6203

Post-Transplant Liver Monitoring Utilizing Integrated Surface-Enhanced Raman and AI in Hepatic Ischemia-Reperfusion Injury Animal Model

Authors: Sanghwa Lee Hyunhee Kwon Jeongmin Oh et al.

Source: Int J Nanomedicine
International Journal of Nanomedicine, Vol Volume 20, Iss Issue 1, Pp 6743-6755 (2025)

Subject Terms: machine learning algorithm, Medicine (General), R5-920, liver function, discriminant analysis, Liver ischemia-reperfusion injury, surface-enhanced Raman spectroscopy, Original Research

Access URL: https://doaj.org/article/39a17464f1cd45b687112eadf3d93767

Development of machine learning models for survival prediction in nasopharyngeal carcinoma using population-based data

Authors: Guoxiang Lin Qiyan Mo Lu Han et al.

Source: Discover Oncology, Vol 16, Iss 1, Pp 1-20 (2025)

Subject Terms: Nasopharyngeal carcinoma, Machine learning algorithm, Survival prediction, Survival probability calculator, Cancer-specific survival, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282

File Description: electronic resource

Relation: https://doaj.org/toc/2730-6011

Access URL: https://doaj.org/article/aaf2365b8fc0411582ea53cc3829b974

deepBreaks identifies and prioritizes genotype–phenotype associations using machine learning

Authors: Mahdi Baghbanzadeh Tyson Dawson Bahar Sayoldin et al.

Source: Scientific Reports, Vol 15, Iss 1, Pp 1-13 (2025)

Subject Terms: Phenotype-genotype association, Machine learning algorithm, Sequence analysis, SNP prioritization, Medicine, Science

File Description: electronic resource

Relation: https://doaj.org/toc/2045-2322

Access URL: https://doaj.org/article/ef9fd0409eaf44f9b9b70de91cb7c849

Development of a diagnostic model for ovarian cancer based on machine learning algorithms and functional analysis of key biomarker SOX17

Authors: Xueyan Geng Maopeng Yin Hongxi Zhao et al.

Source: Journal of Ovarian Research, Vol 18, Iss 1, Pp 1-13 (2025)

Subject Terms: Ovarian cancer, Diagnostic model, Machine learning algorithm, Immune cell infiltration, SOX17, Gynecology and obstetrics, RG1-991

File Description: electronic resource

Relation: https://doaj.org/toc/1757-2215

Access URL: https://doaj.org/article/8ea98b961ee4485287af14d7cfd7292e

A Predictive Model Based on Machine Learning Algorithm for Vein Thrombosis After Ovarian Cancer Resection

Authors: Zhao L Yao L

Source: International Journal of Women's Health, Vol 17, Iss Issue 1, Pp 4207-4226 (2025)

Subject Terms: Ovarian cancer, machine learning algorithm, predictive model, postoperative venous thromboembolism, risk factors, XGBoost, Gynecology and obstetrics, RG1-991

File Description: electronic resource

Relation: https://www.dovepress.com/a-predictive-model-based-on-machine-learning-algorithm-for-vein-thromb-peer-reviewed-fulltext-article-IJWH; https://doaj.org/toc/1179-1411

Access URL: https://doaj.org/article/cd604138211242819ddaf9f0071c8d74

Association between SHR and mortality in critically ill patients with CVD: a retrospective analysis and machine learning approach

Authors: Wanlu Zhou Junxi Liao Ting Wu et al.

Source: Diabetology & Metabolic Syndrome, Vol 17, Iss 1, Pp 1-11 (2025)

Subject Terms: Stress hyperglycemia ratio, Cardiovascular disease, Mortality risk, Machine learning algorithm, Nutritional diseases. Deficiency diseases, RC620-627

File Description: electronic resource

Relation: https://doaj.org/toc/1758-5996

Access URL: https://doaj.org/article/86cfed1ace6d4b6888918076bf96bf03

AI-Driven intrusion detection and prevention systems to safeguard 6G networks from cyber threats

Authors: P. Chinnasamy Sarojini Yarramsetti Ramesh Kumar Ayyasamy et al.

Source: Scientific Reports, Vol 15, Iss 1, Pp 1-26 (2025)

Subject Terms: 6G network, Cyber-attack monitoring, Intrusion detection system, Machine learning algorithm, Binary wolf optimization, Medicine, Science

File Description: electronic resource

Relation: https://doaj.org/toc/2045-2322

Access URL: https://doaj.org/article/dbfea69878be45228cb523a2507c9520

Research on the implementation and effectiveness evaluation of deep reinforcement learning algorithms for portfolio optimisation

Authors: Gao Yunxiang Tang Bangying

Source: Discover Artificial Intelligence, Vol 5, Iss 1, Pp 1-12 (2025)

Subject Terms: Deep reinforcement learning algorithm, Portfolio optimisation, Effectiveness evaluation, A2C, PPO, Computational linguistics. Natural language processing, P98-98.5, Electronic computers. Computer science, QA75.5-76.95

File Description: electronic resource

Relation: https://doaj.org/toc/2731-0809

Access URL: https://doaj.org/article/ea0dd1c5fe3c4c01b7c171ce10c6ea3d

Comparative analysis of different machine learning algorithms for calculating paddy field evapotranspiration in the Huai River Basin

Authors: JIN Qiuxiang WANG Wei TAI Jiu et al.

Source: Guan'gai paishui xuebao, Vol 44, Iss 10, Pp 120-132 (2025)

Subject Terms: paddy field, evapotranspiration, machine learning algorithm, single crop coefficient model, automated machine learning framework, Agriculture (General), S1-972, Irrigation engineering. Reclamation of wasteland. Drainage, TC801-978

File Description: electronic resource

Relation: https://www.ggpsxb.com/jgpxxben/ch/reader/view_abstract.aspx?file_no=20251014&flag=1; https://doaj.org/toc/1672-3317

Access URL: https://doaj.org/article/4c5699d323614627a835dc0eb243849b

Machine Learning for Seismic Bump Prediction: A Comparative Study of Different Algorithms and Features

Authors: Fei Li

Source: Journal of Applied Science and Engineering, Vol 29, Iss 5, Pp 1035-1051 (2025)

Subject Terms: random forest classification, seismic bump, dwarf mongoose optimization algorithm, machine learning algorithm, Engineering (General). Civil engineering (General), TA1-2040, Chemical engineering, TP155-156, Physics, QC1-999

File Description: electronic resource

Relation: http://jase.tku.edu.tw/articles/jase-202605-29-05-02; https://doaj.org/toc/2708-9967; https://doaj.org/toc/2708-9975

Access URL: https://doaj.org/article/094ebe14a9074629b6494998ceeda020

Evaluation of anthropometric and ultrasonographic measurements with different machine learning methods in predicting difficult intubation: a prospective observational study

Authors: Gizem Demir Senoglu Ezgi Kara Timucin Serdar Kırısoglu

Source: BMC Anesthesiology, Vol 25, Iss 1, Pp 1-11 (2025)

Subject Terms: Difficult intubation, Upper airway measurement, Machine learning algorithm, Anesthesiology, RD78.3-87.3

File Description: electronic resource

Relation: https://doaj.org/toc/1471-2253

Access URL: https://doaj.org/article/1c27ed3a3a714cefaed1e34970af51d9

A hybrid MARL clustering framework for real time open pit mine truck scheduling

Authors: Xiaolei Xiang Wei Lin Danqi Li

Source: Scientific Reports, Vol 15, Iss 1, Pp 1-23 (2025)

Subject Terms: Multi-agent deep reinforcement learning algorithm, QMIX, Gaussian mixture model, Open-pit mining, Truck scheduling, Medicine, Science

File Description: electronic resource

Relation: https://doaj.org/toc/2045-2322

Access URL: https://doaj.org/article/f7ac25e2b3aa4d10b60e96df41633cce