Suchergebnisse - "Learning algorithm"

Sustainable Selection of Machine Learning Algorithm for Gender-bias Attenuated Prediction

Autoren: Orbay, Raik Wikner, Evelina

Quelle: IEEE Open Journal of Vehicular Technology. 6:348-358

Schlagwörter: Feature engineering, Energy consumption, Battery electric vehicles, Unsupervised/supervised learning, Driving style classification, Machine learning

Dateibeschreibung: electronic

Zugangs-URL: https://research.chalmers.se/publication/543996
https://research.chalmers.se/publication/543996/file/543996_Fulltext.pdf

Machine learning algorithm for GPCR-A17 ligand action prediction: A Novel Approach to Drug Discovery

MACHINE LEARNING ALGORITHM FOR GPCR-A17 LIGAND ACTION PREDICTION: A Novel Approach to Drug Discovery

Autoren: Silva, Rodolfo Miguel Tavares da

Schlagwörter: GPCRs, Artificial Intelligence, Machine Learning, Deep Learning, Drug Discovery, Inteligência Artificial, Descoberta de Medicamentos

Verfügbarkeit: https://hdl.handle.net/10316/117960

Review on PAPR Reduction and Improvement of OFDM System Performance Using Artificial Intelligence Machine Learning Algorithm

Autoren: Rahul Mishra

Quelle: International Journal of Scientific Research and Engineering Trends. 11:106-110

Assemble like expert: Multitask-meta hierarchical imitation learning algorithm guided by an expert skill model for robot polygonal peg-in-hole assembly

Autoren: Hubo Chu Tie Zhang Yanbiao Zou et al.

Quelle: Journal of Manufacturing Systems. 83:82-102

Differentiating Type 1 and Type 2 myocardial infarction using a machine learning algorithm and biomarkers

Autoren: Anna Snavely Laurel Jackson Christian John Hunter et al.

Quelle: The American Journal of Emergency Medicine. 98:50-56

Online Reinforcement Learning Algorithm Design for Adaptive Optimal Consensus Control Under Interval Excitation

Autoren: Yong Xu Qi-Yue Che Meng-Ying Wan et al.

Quelle: IEEE Transactions on Systems, Man, and Cybernetics: Systems. 55:7325-7334

SPOT: An Active Learning Algorithm for Efficient Deep Neural Network Training

Autoren: Luyang Fang Cheng Meng Lin Zhao et al.

Quelle: Big Data Mining and Analytics. 8:1060-1074

An Integrated Mathematical Programming and Reinforcement Learning Algorithm for the Flexible Job Shop Scheduling with Variable Lot-sizing

Autoren: Chuanzhao Yu Chunjiang Zhang Jiaxin Fan et al.

Quelle: Journal of Manufacturing Systems. 82:210-223

DAQFL: Dynamic Aggregation Quantum Federated Learning Algorithm for Intelligent Diagnosis in Internet of Medical Things

Autoren: Zhiguo Qu Xuemeng Zhao Le Sun et al.

Quelle: IEEE Internet of Things Journal. 12:39313-39325

Development and Evaluation of a Deep Learning Algorithm to Differentiate Between Membranes Attached to the Optic Disc on Ultrasonography

Autoren: Vaidehi Bhatt Nikhil Shah Deepak Bhatt et al.

Quelle: Clin Ophthalmol

Schlagwörter: retinal detachment, POSTERIOR VITREOUS DETACHMENT, posterior vitreous detachment, ultrasonography, artificial intelligence, deep learning algorithm, Original Research

Zugangs-URL: https://pubmed.ncbi.nlm.nih.gov/40125481

Robot path planning using enhanced Q-learning algorithm based on single parameter

Autoren: Noor Fallooh Ahmed Sadiq Eyad Abbas et al.

Quelle: Engineering and Technology Journal, Vol 43, Iss 2, Pp 159-173 (2025)

Schlagwörter: reinforcement learning, learning rate (α), Technology, Science, robot path planning, discount factor (γ), q-learning algorithm

Zugangs-URL: https://doaj.org/article/0b469032802f48b4804aab3aa7a703f1

Intelligent Robot Trajectory Tracking Control Combining Mamdani Theory and Q-Learning Algorithm

Autoren: Qiong Wu Hua Chen Baolong Liu

Quelle: IEEE Access, Vol 13, Pp 91276-91289 (2025)

Schlagwörter: Q-learning algorithm, reward function, Fuzzy controller, trajectory tracking, robot, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

Zugangs-URL: https://doaj.org/article/fc08fcf1ba4a443e85b0ed6b2eee5be5

Data-Selective Learning Algorithm Using Resonance Parameters Based on Stacked Data Augmentation for Wideband Impedance Prediction of Printed Spiral Coils

Autoren: Joojoong Kim Eakhwan Song

Quelle: Journal of Electromagnetic Engineering and Science, Vol 25, Iss 2, Pp 190-201 (2025)

Schlagwörter: data selective learning algorithm, Electricity and magnetism, printed spiral coils, QC501-766, stacked data augmentation, resonance parameters, Electrical engineering. Electronics. Nuclear engineering, wideband impedance prediction, TK1-9971

Zugangs-URL: https://doaj.org/article/bc286054a65b49e1b9e5a408ffcaf8d7

New Maps of Lunar Surface Oxide Abundances and Mg# Using an Optimized Ensemble Learning Algorithm

Autoren: Chaofa Bian Kefei Zhang Yunzhao Wu et al.

Quelle: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 18, Pp 9119-9134 (2025)

Schlagwörter: KAGUYA multiband imager (MI), Ocean engineering, Chang'e-5 (ce-5), QC801-809, Geophysics. Cosmic physics, improved ensemble learning algorithm, christiansen feature (CF), TC1501-1800, lunar oxide

Zugangs-URL: https://doaj.org/article/843d0ab5d3dc4222b3dcd7f19bec4132

Factors associated with the presence of anxiety and depression symptoms in rural hypertensive adults in Bangladesh: leveraging extreme gradient booster machine learning algorithm

Autoren: Raihana, Zarin Kader, Manzur Islam, Md Zahidul et al.

Quelle: Frontiers in Psychology. 16

Schlagwörter: anxiety, depression, hypertension, logistic regression, machine learning

Dateibeschreibung: electronic

Zugangs-URL: https://urn.kb.se/resolve?urn=urn:nbn:se:du-51403
https://doi.org/10.3389/fpsyg.2025.1650667

A deep-learning algorithm (AIFORIA) for classification of hematopoietic cells in bone marrow aspirate smears based on nine cell classes-a feasible approach for routine screening?

Autoren: Saft, L Vaara, E Ljung, E et al.

Quelle: JOURNAL OF HEMATOPATHOLOGY. 18(1)

Zugangs-URL: http://kipublications.ki.se/Default.aspx?queryparsed=id:161391855

A novel deep learning algorithm for Phaeocystis counting and density estimation based on feature reconstruction and multispectral generator

Autoren: Si, Yifan Li, Shuo He, Sailing

Quelle: Neurocomputing. 611

Schlagwörter: Deep learning, Density map, Multispectral reconstruction, Phaeocystis counting

Dateibeschreibung: print

Zugangs-URL: https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-354916
https://doi.org/10.1016/j.neucom.2024.128674

External validation of a deep learning algorithm for automated echocardiographic strain measurements

Autoren: Myhre, PL Hung, C-L Frost, MJ et al.

Quelle: EUROPEAN HEART JOURNAL: DIGITAL HEALTH. 5(1):60-68

Zugangs-URL: http://kipublications.ki.se/Default.aspx?queryparsed=id:238264705

Estimation of Potato Water Footprint Using Machine Learning Algorithm Models in Arid Regions

Autoren: Abdel-Hameed, Amal Mohamed Abuarab, Mohamed Al-Ansari, Nadhir et al.

Quelle: Potato Research. 67(4):1755-1774

Schlagwörter: Artifcial neural network, Blue water footprint, Random forest, Support vector regression, Water management, Soil Mechanics, Geoteknik

Dateibeschreibung: electronic

Zugangs-URL: https://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-104949
https://doi.org/10.1007/s11540-024-09716-1

Preliminary Study of a Federated Learning Algorithm Based on an Evolutionary Random Subspace Forest

Autoren: Van Doninck, Thibo Barbé, Kurt Faculty of Medicine and Pharmacy et al.

Weitere Verfasser: Van Doninck, Thibo Barbé, Kurt Faculty of Medicine and Pharmacy et al.

Quelle: 2025 IEEE Medical Measurements & Applications (MeMeA). :1-5

Schlagwörter: Random Forest, evolutionary algorithm, regression, Federated Learning

Zugangs-URL: https://biblio.vub.ac.be/vubir/preliminary-study-of-a-federated-learning-algorithm-based-on-an-evolutionary-random-subspace-forest(b85442df-c9bb-4c7f-ac12-8f66b39f7b74).html