Results 111 to 120 of about 32,654 (268)

ОПТИМІЗАЦІЯ ГІБРИДНИХ МОДЕЛЕЙ НА ОСНОВІ TCN, LSTM, LIGHTGBM ДЛЯ ПРОГНОЗУВАННЯ ЕНЕРГОСПОЖИВАННЯ В РОЗУМНИХ БУДИНКАХ

Кібербезпека: освіта, наука, техніка
Точне короткострокове прогнозування навантаження є ключовим завданням для ефективного управління енергоресурсами в системах розумного будинку. Гібридні моделі, що поєднують архітектури глибокого навчання (DL) та ансамблі дерев рішень, є провідним ...
Дмитро Ніщеменко
doaj   +1 more source

Non-linear and synergistic effects of built environment factors on older adults’ walking behavior: An analysis integrating LightGBM and SHAP

Transactions in Urban Data, Science, and Technology
Examining the relationship between the built environment and older adults’ walking behavior is of critical importance for the development of aging-friendly cities and communities.
Linchuan Yang, Haosen Yang, Jianqiang Cui, Ya Zhao, Fan Gao   +4 more
semanticscholar   +1 more source

DNAwhisper: An Integrated Deep Learning Pyramidal Framework for Multi‐Trait Genomic Prediction and Adaptive Marker Prioritisation

Plant Biotechnology Journal, EarlyView.
ABSTRACT Genomic selection (GS) is critical for accelerating genetic gain in modern plant breeding. Deep learning approaches offer powerful non‐linear representation capabilities for modelling non‐additive effects. However, their application in GS remains restricted, as high‐dimensional, low‐sample and noisy data hinder the identification of ...
Yuexin Ma, Xiang Li, Xiaohao Ji, Chunying Wang, Di Zhang, Tingting Zhai, Haibo Wang, Ping Liu   +7 more
wiley   +1 more source

Comparison of Random Forest, XGBoost, and LightGBM Methods for the Human Development Index Classification

Jambura Journal of Mathematics
Machine learning classification is an effective tool for categorizing data based on patterns, which is particularly useful in analyzing the Human Development Index (HDI) in Indonesia. HDI serves as a key indicator of regional development progress, making
Yunna Mentari Indah, Rafika Aristawidya, Anwar Fitrianto, Erfiani Erfiani, L.M. Risman Dwi Jumansyah   +4 more
doaj   +1 more source

Based on PCA and SSA-LightGBM oil-immersed transformer fault diagnosis method

PLoS ONE
A fault diagnosis method for oil immersed transformers based on principal component analysis and SSA LightGBM is proposed to address the problem of low diagnostic accuracy caused by the complexity of current oil immersed transformer faults. Firstly, data
Jizhong Wang, Jianfei Chi, Yeqiang Ding, Haiyan Yao, Qiang Guo   +4 more
semanticscholar   +1 more source

A Comparative Study of Context‐Aware Modeling Approaches for Specific Heat Load Profiles for Residential Consumers in District Heating Simulations

Proceedings in Applied Mathematics and Mechanics, Volume 26, Issue 2, June 2026.
ABSTRACT Accurate, time‐resolved heat load profiles are essential for realistic district heating simulations, enabling optimized network operation and long‐term transformation planning. In this work, we systematically evaluate modeling approaches for generating such profiles, comparing data‐driven methods (e.g., regression and machine learning) with ...
Johanna Heidrich, Nicolas Krummenauer, Jan Mohring   +2 more
wiley   +1 more source

Research Topics and Trends in MIMIC‐IV: A Large ICU Database Relevant for Critical Care Nursing

Nursing in Critical Care, Volume 31, Issue 3, May 2026.
ABSTRACT Background The Medical Information Mart for Intensive Care‐IV (MIMIC‐IV) clinical database has become a central resource for data‐driven critical care research, enabling advances in clinical informatics, machine learning and nursing science.
Yuh‐Shan Ho, Ahmed Ben Salem, Mahdi Kchaou, Abdulhameed Dere, Yosra Mzid, Houcemeddine Turki   +5 more
wiley   +1 more source

Interpretable LightGBM model with SHAP analysis predicts non‐excellent response to initial radioiodine therapy in differentiated thyroid carcinoma

Journal of Applied Clinical Medical Physics, Volume 27, Issue 4, April 2026.
Abstract Purpose To identify independent determinants influencing therapeutic outcomes of initial radioactive iodine (131I) therapy in differentiated thyroid carcinoma (DTC) and establish an interpretable predictive framework for clinical decision‐making.
Zhaoxia Luo, Yangyang Lei, Qing Zhang
wiley   +1 more source

Deep Quake Dynamics: A Multimodal Fault‐Aware Approach to Earthquake Magnitude and Occurrence Time Forecasting

Geoscience Data Journal, Volume 13, Issue 2, April 2026.
EQMT integrates earthquake catalog data, fault‐network geometry, engineered features, and graph embeddings in a unified framework for forecasting earthquake magnitude and occurrence time. The framework is designed to reflect inter‐fault spatial dependencies together with temporal seismic patterns, addressing limitations of approaches based only on ...
Kiymet Kaya, Murat Sahin, Furkan Mangir, Alp Baris Beydemir, Cenk Yaltirak, Sule Gunduz Oguducu   +5 more
wiley   +1 more source

Machine learning versus traditional formulas for fetal weight estimation: An international multicenter study evaluating prediction accuracy across birth weight percentiles

International Journal of Gynecology &Obstetrics, Volume 173, Issue 1, Page 456-462, April 2026.
Abstract Objective To assess whether machine learning (ML) offers improved birth weight prediction accuracy, since despite numerous models, the Hadlock formula remains the clinical standard. Methods A multicenter retrospective study analyzed data from 9674 singleton pregnancies with estimated fetal weight (EFW) within 7 days of delivery.
Omer Dor, Eran Ashwal, May Cohen, Ori Rottenstreich, Yariv Yogev, Noam Shomron, Misgav Rottenstreich   +6 more
wiley   +1 more source