Výsledky vyhľadávania - "Learning Algorithm"

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

Autori: Selseleh Jonban, Mansour

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

Thesis Advisors: Romeral Martínez, José Luis

Zdroj: TDX (Tesis Doctorals en Xarxa)

Predmety: 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

Popis súboru: application/pdf

Prístupová URL adresa: 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

Autori: Changhong Pan Lu Qi Lili Zhao a ďalší

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

Predmety: 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

Prístupová URL adresa: https://doaj.org/article/094f4d3829df4bb496d23b86d20d4fbe

Determination of Alzheimer's Disease Stages by Artificial Learning Algorithms

Autori: Bulut, Nurgül Çakar, Tuna Arslan, İlker a ďalší

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

Predmety: 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

Prístupová URL adresa: 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

Autori: Irani Shemirani, Mahnaz Pernestig, Anna-Karin Björkman, Jens a ďalší

Zdroj: BMC Infectious Diseases. 25(1)

Predmety: 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

Popis súboru: electronic

Prístupová URL adresa: 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

Autori: Chiabotto, Giulia Dumontel, Bianca Zilli, Luca a ďalší

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

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

Popis súboru: application/pdf

Federated Deep Reinforcement Learning for ENDC Optimization

Autori: Adrian Martin Isabel de-la-Bandera Adriano Mendo a ďalší

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

Predmety: 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

Prístupová URL adresa: https://hdl.handle.net/10630/38565

Multimedia Information Technology and Applications

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

Predmety: 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

Popis súboru: application/pdf

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

Prístupová URL adresa: 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

Autori: Priya S C. Feenita Uday Goel a ďalší

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

Predmety: Regression Models, Machine Learning Algorithm, Dual Fuel Engine, Hydrogen

Popis súboru: application/pdf

Prístupová URL adresa: 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

Autori: Sanghwa Lee Hyunhee Kwon Jeongmin Oh a ďalší

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

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

Prístupová URL adresa: https://doaj.org/article/39a17464f1cd45b687112eadf3d93767

Multi-element geochemical anomaly recognition applying geologically-constrained convolutional deep learning algorithm with Butterworth filtering of frequency domain information

Autori: Hamid Sabbaghi Seyed Hassan Tabatabaei Nader Fathianpour

Zdroj: Scientific Reports, Vol 15, Iss 1, Pp 1-14 (2025)

Predmety: Cr mineralization, Convolutional deep learning algorithm, Geologically-constrained neural network, Frequency domain data, Geochemical anomaly recognition, Butterworth filter, Medicine, Science

Popis súboru: electronic resource

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

Prístupová URL adresa: https://doaj.org/article/be643ff904c240688621ec70f5f1597f

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

Autori: Guoxiang Lin Qiyan Mo Lu Han a ďalší

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

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

Popis súboru: electronic resource

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

Prístupová URL adresa: https://doaj.org/article/aaf2365b8fc0411582ea53cc3829b974

deepBreaks identifies and prioritizes genotype–phenotype associations using machine learning

Autori: Mahdi Baghbanzadeh Tyson Dawson Bahar Sayoldin a ďalší

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

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

Popis súboru: electronic resource

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

Prístupová URL adresa: 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

Autori: Xueyan Geng Maopeng Yin Hongxi Zhao a ďalší

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

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

Popis súboru: electronic resource

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

Prístupová URL adresa: https://doaj.org/article/8ea98b961ee4485287af14d7cfd7292e

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

Autori: Zhao L Yao L

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

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

Popis súboru: 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

Prístupová URL adresa: https://doaj.org/article/cd604138211242819ddaf9f0071c8d74

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

Autori: Wanlu Zhou Junxi Liao Ting Wu a ďalší

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

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

Popis súboru: electronic resource

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

Prístupová URL adresa: https://doaj.org/article/86cfed1ace6d4b6888918076bf96bf03

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

Autori: P. Chinnasamy Sarojini Yarramsetti Ramesh Kumar Ayyasamy a ďalší

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

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

Popis súboru: electronic resource

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

Prístupová URL adresa: https://doaj.org/article/dbfea69878be45228cb523a2507c9520

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

Autori: Gao Yunxiang Tang Bangying

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

Predmety: 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

Popis súboru: electronic resource

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

Prístupová URL adresa: https://doaj.org/article/ea0dd1c5fe3c4c01b7c171ce10c6ea3d

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

Autori: JIN Qiuxiang WANG Wei TAI Jiu a ďalší

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

Predmety: 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

Popis súboru: electronic resource

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

Prístupová URL adresa: https://doaj.org/article/4c5699d323614627a835dc0eb243849b

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

Autori: Fei Li

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

Predmety: 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

Popis súboru: 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

Prístupová URL adresa: https://doaj.org/article/094ebe14a9074629b6494998ceeda020

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

Autori: Gizem Demir Senoglu Ezgi Kara Timucin Serdar Kırısoglu

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

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

Popis súboru: electronic resource

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

Prístupová URL adresa: https://doaj.org/article/1c27ed3a3a714cefaed1e34970af51d9