Topical Collection on "Global Change and Environmental Problems"

Deadline for manuscript submissions: 03 February 2025

Collection Editor

Topical Collection Information

Dear Colleagues,

This project innovatively integrates projection tracking and fuzzy iterative clustering techniques, providing a new model for environmental risk assessment in oil and gas development. This model enables the entirely objective and reasonable determination of environmental risk parameters, overcoming the subjectivity and arbitrariness in sample clustering present in environmental risk assessments conducted without international, national, or industry standards. Additionally, through an enhanced swarm intelligence optimization algorithm, the project significantly improves the processing efficiency of data dependency, thus bolstering the effectiveness and accuracy of clustering, and further enhancing the precision of environmental risk assessments. The practicality of the constructed model will be validated through the projects as a case study and preventive environmental protection measures will be proposed. This initiative aims to support green cooperation in the oil and gas development sector. This innovative research approach not only enhances the scientific rigor and practicality of assessment technologies but also provides solid academic support for collaboration in environmental risk management strategies. It holds significant value for international cooperation and practical application prospects.

Collection Editor

Associate Professor. Dr. Alexey Mikhaylov

Keywords:

• Machine learning
• Oil
• Gas