Aug 2026· International Journal of Occupational Safety and Ergonomics· pp.
1-14
· 0 citations· 22 references
Medicine
Abstract
This study analyzes China's national coal mine accident data (2000-2025) to evaluate safety performance. Using one-way analysis of variance and random forest regression model, the study quantitatively analyzes temporal trends, spatial clustering, accident causes and types. A time-series model was developed to predict the million-ton mortality rate, and the optimal ETS(M,Ad,N) realizes a dynamic 5-year mortality rate forecast. Results show fatal accidents peak in March, June-August and November-December. Geographically, central and southwestern regions are high-risk, with Shanxi Province alone accounting for 15.6% of accidents. Analysis of accident causes revealed that 47.2% were attributable to human factors. By type, mechanical accidents were most common, and fire accidents were the least. Based on historical statistical trends, the ETS(M,Ad,N) model projects that the mortality rate per million tons will continue to decline from 2026 to 2030. These quantitative findings provide a data-driven reference for prioritizing safety interventions and targeted risk management strategies.
This study establishes a coherent mathematical model for the investigation of road accidents in Bangladesh by integrating nonlinear deterministic modeling, count regression with exposure, normalized fatality-rate estimation and seasonal time-series forecasting. The analysis constructs a balanced monthly panel from Janu...
S. Sarker, M. Ma'mun· International Journal of Tra...· 0 citations
Road traffic accidents remain a major public health concern, requiring systematic analyses of temporal trends to support evidence-based road safety planning. This retrospective longitudinal study analyzes traffic accident-related injuries and fatalities in Diyarbakir Province, Türkiye, based on official records from 20...
Ayse Unal, İ. Gokalp, S. Ekinci et al.· Gazi university journal of s...· 0 citations
Disaster impact severity is typically assessed only after casualty and damage data have been collected, even though the spatial-temporal characteristics of an event are known from the outset. This study aims to construct a disaster severity index using multi-component Principal Component Analysis (PCA) and to classify...
Firman Almaliky Gapri Amra· Journal of Computation Physi...· 0 citations
Accurate assessment of accident severity and regulatory deficiencies is essential for improving safety management and intelligent decision-making in complex industrial systems. This study proposes an interpretable machine learning framework to evaluate the influence of regulatory variables on coal mine accident severit...
Results show that the tree-based ensemble models Random Forest and XGBoost outperform Logistic Regression and MLP in terms of overall predictive performance, with XGBoost exhibiting better overall performance.
Zi-Yu Cao· Frontiers in Computing and I...· 0 citations
Abstract Flood is a devastating phenomenon responsible for the loss of human lives, destruction of roads, buildings, electric systems and damage to hydraulic structures, leading to a great economic loss to the country. This study aims to identify a suitable time series model.Forecasting plays a major role in environmen...
S. P· Current World Environment· 0 citations
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