这是你suan的第一个项目，每日电力负荷的时间序列预测模型,数据集格式模板为：'年/月/日 时:分'(year/month/day hour:minute ...

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...

The true nature of our universe as been an open debate for millennia, and recently, scientists and philosophers have pondered whether it might be a hyper-realistic simulation perpetuated by some super ...

ABSTRACT: The accurate prediction of backbreak, a crucial parameter in mining operations, has a significant influence on safety and operational efficiency. The occurrence of this phenomenon is ...

To overcome the limitations of traditional roller-compacted concrete (RCC) compaction monitoring—which relies on macroscopic experiments, overlooks microscopic mechanisms, and lacks model ...

The consortium running the European Space Agency's (ESA) Euclid mission has published the most extensive simulation of the cosmos to date. The modeling was based on algorithms developed by UZH ...

NVIDIA has unveiled a major milestone in scalable machine learning: XGBoost 3.0, now able to train gradient-boosted decision tree (GBDT) models from gigabytes up to 1 terabyte (TB) on a single GH200 ...

Purpose: To develop effective machine learning models that analyze pattern visual evoked potentials (PVEPs) to predict the stabilized visual acuity (VA) of patients with treated ocular trauma. Methods ...

Abstract: Water leakage in distribution networks poses significant challenges, including resource wastage and increased operational costs. This paper presents the ANN-XGBoost algorithm, an innovative ...

Classification of gas wells is an important part of optimizing development strategies and increasing the recovery. The original classification standard of gas wells in the Sulige gas field has weak ...