Rainfall prediction has advanced rapidly with the adoption of machine learning, but most models remain optimized for overall ...

These open-source MMM tools solve different measurement problems, from budget optimization to forecasting and preprocessing.

Machine learning requires humans to manually label features while deep learning automatically learns features directly from raw data. ML uses traditional algorithms like decision tress, SVM, etc., ...

Machine learning models are increasingly applied across scientific disciplines, yet their effectiveness often hinges on heuristic decisions such as data transformations, training strategies, and model ...

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 ...

1 Faculty of Land Resources Engineering, Kunming University of Science and Technology Kunming, Kunming, China 2 Pangang Group Mining Company Limited Panzhihua, Panzhihua, Sichuan, China The stability ...

Abstract: With the continuous advancement of very-large-scale integra tion technology, high-speed interconnect systems are increasingly challenged by signal integrity (SI) issues arising from feature ...

Tumor Site–Specific Radiation-Induced Lymphocyte Depletion Models After Fractionated Radiotherapy: Considerations of Model Structure From an Aggregate Data Meta-Analysis Lymphocytes play critical ...

1 State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu, China 2 State Key Laboratory of Mountain Bridge and Tunnel Engineering, ...

Abstract: Data acquisition for training machine learning (ML) models in resource-intensive scientific fields is challenging [1]. Recognizing the high computational costs associated with generating ...