Search Results - "Boosting algorithms"

XGBoost-Based 52-Week Peak-Load Forecasting Model with Monthly Adaptive Training and Sequential Prediction.

Authors: Kim, Kyeong-Hwan Kim, Tae-Geun Kwon, Bo-Sung et al.

Source: Energies (19961073). Jun2026, Vol. 19 Issue 11, p2683. 27p.

Subject Terms: *Load forecasting (Electric power systems), *Boosting algorithms, *Time, *Demand forecasting, *Photovoltaic power generation, *Feature selection, *Electric power production forecasting

Interpretable Tree‐Based Models for Predicting Short‐Term Rockburst Risk Considering Multiple Factors.

Authors: Chen, Shuai Dou, Linming Li, Atao et al.

Source: Energy Science & Engineering. Jun2026, Vol. 14 Issue 6, p2941-2960. 20p.

Subject Terms: *Boosting algorithms, *Shapley Additive Explanations, *Risk assessment, *Machine learning, *Coal mining safety, *Random forest algorithms

High-Resolution Data-Driven Energy Consumption Prediction for Battery-Electric Buses Using Boosting Algorithms.

Authors: Wu, Yong Xin, Zhichao Li, Jiachang et al.

Source: Energies (19961073). May2026, Vol. 19 Issue 9, p2058. 25p.

Subject Terms: *Boosting algorithms, *Energy consumption forecasting, *Real-time computing, *Electric motor buses, *Metadata, *Machine learning, *Public transit

Geographic Terms: Jinan (Shandong Sheng, China)

Prediction of Pipeline Defect Depth and Classification Based on CatBoost.

Authors: Chen, Cong Li, Rui Jia, Guanwei et al.

Source: Energy Science & Engineering. May2026, Vol. 14 Issue 5, p2429-2439. 11p.

Subject Terms: *Boosting algorithms, *Magnetic flux leakage, *Fault diagnosis, *Machine learning, *Structural health monitoring

Performance Analysis and Implementation of AdaBoost and K-Nearest Neighbour-Based Computation Offloading in Fog Architecture.

Authors: Gupta, Prince Dhankhar, Annu Singhal, Swasti et al.

Source: Ingénierie des Systèmes d'Information. May2026, Vol. 31 Issue 5, p1375-1387. 13p.

Explainable AI (XAI) in Auditing: Bridging the Gap Between Predictive Fraud Models and Regulatory Standards.

Authors: Faccia, Alessio¹ (AUTHOR)

Source: Journal of Risk & Financial Management. May2026, Vol. 19 Issue 5, p311. 15p.

Retrieval of All-Sky Land Surface Temperature from MERSI-II/FY-3D Data.

Authors: Zhang, Han-Hao Jiang, Geng-Ming

Source: Remote Sensing. Jun2026, Vol. 18 Issue 12, p1954. 22p.

Subjects: Land surface temperature, Boosting algorithms, Algorithms, Artificial satellites, Energy budget (Geophysics)

Machine Learning-Based Soil Moisture Retrieval from Sentinel-1A Observations over the International Soil Moisture Networks.

Authors: Wang, Jingyang Wang, Yuzhu Bai, Xiaojing et al.

Source: Remote Sensing. Jun2026, Vol. 18 Issue 12, p1914. 22p.

Subjects: Soil moisture, Boosting algorithms, Synthetic aperture radar, Machine learning, Agricultural remote sensing, Hydrological databases, Remote sensing, Artificial satellites

XGBoost-Based Corrections for Road Surface Temperature Forecasts.

Authors: Karsisto, Virve Hieta, Leila Kämäräinen, Matti

Source: Journal of Applied Meteorology & Climatology. Jun2026, Vol. 65 Issue 6, p1-17. 17p.

Subjects: Boosting algorithms, Freezing points, Temperature, Weather forecasting, Machine learning, Road safety measures, Forecasting

Construction and Comparison of Diabetes Prediction Models Based on GA-LightGBM.

Authors: Liu, Xingyue Qu, Zhenhua Cao, Yuan

Source: IAENG International Journal of Applied Mathematics. Jun2026, Vol. 56 Issue 6, p2140-2149. 10p.

Subjects: Boosting algorithms, Genetic algorithms, Machine learning, Feature selection, Blood sugar monitoring, Medical forecasting

A Refined Prediction Model for Regional Zenith Troposphere Combining ICEEMDAN and BiLSTM-XGBoost.

Authors: Chen, Chao Zhao, Yinghao Zhang, Wenyuan et al.

Source: Remote Sensing. May2026, Vol. 18 Issue 9, p1381. 17p.

Subjects: Long short-term memory, Boosting algorithms, Satellite meteorology, Time series analysis

Geographic Terms: China

MultTransNet: A Novel Multimodal Transformer Network for Retrieving Significant Wave Height Using GNSS-R Data.

Authors: Cui, Yinghua Cai, Min Du, Yuxuan et al.

Source: Remote Sensing. May2026, Vol. 18 Issue 9, p1351. 21p.

Subjects: Feature selection, Boosting algorithms, Marine ecology, Remote sensing, Deep learning

Rating Curve Modeling Using Machine Learning: A Case Study in the Largest Gauging Stations in the Amazon River.

Authors: Paca, Victor Hugo da Motta Espinoza Dávalos, Gonzalo E. de Souza, Everaldo Barreiros et al.

Source: Remote Sensing. May2026, Vol. 18 Issue 9, p1337. 21p.

Subjects: Machine learning, Boosting algorithms, Streamflow, Stream measurements, Water levels, Hydrology, Remote sensing

Geographic Terms: Brazil, Amazon River Watershed, Amazon River

Strength Prediction Models for Concrete Incorporating Fly Ash as a Waste Material.

Authors: Kumar, M. Kumar, V. Priyadarshee, A. et al.

Source: Journal of Applied Engineering Sciences. May2026, Vol. 16 Issue 1, p47-56. 10p.

Subjects: Machine learning, Boosting algorithms, Random forest algorithms, Compressive strength, Concrete, Multiple regression analysis, Support vector machines

Transformer Fault Diagnosis Based on Adaptive Boosting and Bidirectional Long Short-Term Memory Neural Network.

Authors: Shang, Liqun Ma, Chuang Li, Aolong et al.

Source: IAENG International Journal of Computer Science. May2026, Vol. 53 Issue 5, p1846-1854. 9p.

Subjects: Fault diagnosis, Boosting algorithms, Long short-term memory, Gas chromatography, Recurrent neural networks, Ensemble learning, Optimization algorithms, Principal components analysis

Enhancing hazard prediction in coal mining with an optimized extra gradient boosting classification model for seismic bump processes.

Authors: Li, Fei¹ (AUTHOR) feili@zzuli.edu.cn

Source: Sādhanā: Academy Proceedings in Engineering Sciences. Jun2026, Vol. 51 Issue 2, p1-20. 20p.

Subjects: Coal mining, Boosting algorithms, Loss control, Risk assessment, Mine safety, Prediction models, Optimization algorithms, Rock bursts

Applicability of machine learning for shear-wave velocity prediction from conventional well logs: the LSBoost approach.

Authors: WIBOWO, Rahmat Catur ARBY, Fadsyah Muhammad MULYATNO, Bagus Sapto et al.

Source: Turkish Journal of Earth Sciences. 2026, Vol. 35 Issue 3, p236-249. 18p.

Subjects: Boosting algorithms, Geophysical well logging, Geotechnical engineering, Machine learning, Multiple regression analysis, Model validation, Support vector machines

Machine learning models and ensemble methods for stock index return forecasting.

Authors: Bielskis, Aivaras Belovas, Igoris

Source: Networks & Heterogeneous Media; 2026, Vol. 21 Issue 3, p1-17, 17p

Privacy-Preserving, Multi-Objective Whale-Bat Optimized XGBoost for Early Diagnosis of Insulin Resistance in Non-Diabetic Women: Development and Validation Using NHANES 2007–2020.

Authors: Nassar, Mohammad Othman¹, moanassar@aau.edu.jo

Source: Journal of Intelligent & Fuzzy Systems; Jul2026, Vol. 50 Issue 7, p2017-2047, 31p

Teaching machine learning by implementing automatic detection of pavement in bicycles rides using smartphone accelerometer data.

Authors: Maruyama, Martin H. M. de Souza, Carlos E.

Source: International Journal of Mechanical Engineering Education; Jul2026, Vol. 54 Issue 3, p600-620, 21p