☆ 3.8 Proceedings Paper

Machine Learning and Knowledge Extraction to Support Work Safety for Smart Forest Operations

MACHINE LEARNING AND KNOWLEDGE EXTRACTION, CD-MAKE 2022 (2022)

相关参考文献

注意：仅列出部分参考文献，下载原文获取全部文献信息。

Article Computer Science, Artificial Intelligence

Machine learning based accident prediction in secure IoT enable transportation system

Bhabendu Kumar Mohanta et al.

Summary: Smart city development has made significant progress with the advancement of emerging technologies, in which Intelligent Transportation System plays a crucial role. Research aims to predict automotive accident severity and has implemented various classification models to enhance prediction accuracy. The study also explores the implementation of secure communication architecture and a message alert system for users.

JOURNAL OF INTELLIGENT & FUZZY SYSTEMS (2022)

添加到收藏夹

Article Computer Science, Interdisciplinary Applications

Learning from major accidents: A machine learning approach

Nicola Tamascelli et al.

Summary: This study aims to exploit the advancements in data science and machine learning to build a predictive model for severity prediction in accidents. The results indicate that the Wide&Deep model offers the best performance.

COMPUTERS & CHEMICAL ENGINEERING (2022)

添加到收藏夹

Article Chemistry, Analytical

Digital Transformation in Smart Farm and Forest Operations Needs Human-Centered AI: Challenges and Future Directions

Andreas Holzinger et al.

Summary: The global efforts toward digital transformation are mainly driven by the great successes of artificial intelligence and machine learning, which are already playing important roles in sectors like agriculture and forestry and are expected to be indispensable in the future.

SENSORS (2022)

添加到收藏夹

Article Public, Environmental & Occupational Health

Occupational accidents in native and planted forests in Brazil: 2007-2018

Killian S. Lima et al.

Summary: This study analyzed data on occupational accidents in forestry operations in Brazil and found that mortality was higher in native forests, while the rate of serious accidents resulting in incapacity to work and sick leave was also high. The results highlight the importance of integrating an occupational safety system into forest management, accompanied by a review of labor and safety policies.

WORK-A JOURNAL OF PREVENTION ASSESSMENT & REHABILITATION (2022)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Deep learning and Boosted trees for injuries prediction in power infrastructure projects

Ahmed Oyedele et al.

Summary: Electrical injuries have substantial impacts, and machine learning algorithms, especially deep feedforward neural networks, have been proven to be effective in predicting and modeling causes of injuries. Sensitivity analysis has shown the strong generalization abilities of deep learning and boosted tree models, which are effective for safety risk management.

APPLIED SOFT COMPUTING (2021)

添加到收藏夹

Article Engineering, Industrial

Analysis of occupational accidents during the chainsaws use in Andalucia

Alberto A. Lopez-Toro et al.

Summary: This study investigated 373 registered occupational accidents related to chainsaws in the Andalusian region of Spain, revealing that the injured victims were mainly male workers aged 30 to 59 from the forestry or agricultural sector. The accidents typically occurred in forestry or agricultural areas, with loss of control of the chainsaw leading to injuries such as open wounds to the leg, knee or fingers.

SAFETY SCIENCE (2021)

添加到收藏夹

Article Agriculture, Multidisciplinary

Evaluation of occupational accidents in forestry in Europe and Turkey by k-means clustering analysis

Anil Orhan Akay et al.

Summary: This study classified 23 European Union countries and Turkey based on occupational accident evaluation criteria using the k-means clustering method. Turkey was in a cluster with lower occupational accident incidence rates in all categories compared to the other clusters and the average of all countries considered together.

TURKISH JOURNAL OF AGRICULTURE AND FORESTRY (2021)

添加到收藏夹

Article Engineering, Industrial

Predicting and analyzing injury severity: A machine learning-based approach using class-imbalanced proactive and reactive data

Sobhan Sarkar et al.

SAFETY SCIENCE (2020)

添加到收藏夹

Article Environmental Sciences

The Influence of the Privatization Process on Accident Rates in the Forestry Sector in Poland

Witold Grzywinski et al.

INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH (2020)

添加到收藏夹

Article Computer Science, Interdisciplinary Applications

Application of optimized machine learning techniques for prediction of occupational accidents

Sobhan Sarkar et al.

COMPUTERS & OPERATIONS RESEARCH (2019)

添加到收藏夹

Article Environmental Sciences

What Are the Occupational Risks in Forestry? Results of a Long-Term Study in Slovakia

Martin Jankovsky et al.

INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH (2019)

添加到收藏夹

Proceedings Paper Computer Science, Artificial Intelligence

Insights into Learning Competence Through Probabilistic Graphical Models

Anna Saranti et al.

MACHINE LEARNING AND KNOWLEDGE EXTRACTION, CD-MAKE 2019 (2019)

添加到收藏夹

Article Engineering, Electrical & Electronic

Advanced accident prediction models and impacts assessment

Fabio Galatioto et al.

IET INTELLIGENT TRANSPORT SYSTEMS (2018)

添加到收藏夹

Article Forestry

Work accidents during cable yarding operations in Central Europe 2006-2014

Michal Allman et al.

FOREST SYSTEMS (2017)

添加到收藏夹

Article Engineering, Industrial

Identifying causes, dynamics and consequences of work accidents in forest operations in an alpine context

Andrea Laschi et al.

SAFETY SCIENCE (2016)

添加到收藏夹

Article Engineering, Industrial

Designing sustainable work systems: The need for a systems approach

Klaus J. Zink

APPLIED ERGONOMICS (2014)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Explaining prediction models and individual predictions with feature contributions

Erik Strumbelj et al.

KNOWLEDGE AND INFORMATION SYSTEMS (2014)

添加到收藏夹

Article Engineering, Industrial

Wood harvesting accidents in the Austrian State Forest Enterprise 2000-2009

Petros A. Tsioras et al.

SAFETY SCIENCE (2014)

添加到收藏夹

Article Ergonomics

Relating safety, productivity and company type for motor-manual logging operations in the Italian Alps

Niccolo Brachetti Montorselli et al.

ACCIDENT ANALYSIS AND PREVENTION (2010)

添加到收藏夹

Article Engineering, Industrial

A Bayesian network analysis of workplace accidents caused by falls from a height

J. E. Martin et al.

SAFETY SCIENCE (2009)

添加到收藏夹

Article Forestry

The human factor in forest operations: Engineering for health and safety

Jeremy Rickards

FORESTRY CHRONICLE (2008)

添加到收藏夹

Article Mathematics, Applied

A machine learning methodology for the analysis of workplace accidents

J. M. Matias et al.

INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS (2008)

添加到收藏夹

Article Engineering, Industrial

Understanding felling safety in the New Zealand forest industry

TA Bentley et al.

APPLIED ERGONOMICS (2005)

添加到收藏夹

© Peeref 2019-2024. All rights reserved.