专刊征稿
Artificial Intelligence and Data Driven Methods for Environmental Research
Artificial intelligence (AI) with promising data-driven methods such as machine learning is being developed to analyze high-throughput data with a novel view to obtaining useful insights, classifying, predicting, and making evidence-based decisions in many aspects of fundamental sciences. Nevertheless, these emerging techniques have not been widely applied in the field of environmental science and engineering (ESE). This special issue covers a range of topics that shed light on the infusion of AI into ESE, enabling worldwide researchers to better understand how advanced data-driven approaches can help in making predictions, extracting features, detecting anomalies, discovering new materials, and so on in ESE.
We welcome original scientific publications on the following topics (but are not limited to):
1. AI methodologies for environmental and ecological system monitoring;
2. Explainable machine learning methods for prediction and early warning of environmental pollution events;
3. Data acquisition, fusion, and interpretation across planning, design, operation, assessment and anomaly detection of environmental and water systems;
4. Integration of data-driven methods with conventional kinetics models for interpretation of contaminant degradation/resource recovery processes;
5. AI-based discovering of environmental functional materials;
6. Prediction and identification of health risk of emerging concerns of contaminants.
Guest editors:
Dr. Xu Wang
School of Civil and Environmental Engineering, Harbin Institute of Technology (Shenzhen), China
Dr. Guangtao Fu
Centre for Water Systems, College of Engineering, Mathematics and Physical Science, University of Exeter, UK
Manuscript submission information:
Submission deadline: March 15, 2023
Acceptance deadline: June 15, 2023
All accepted papers are free of charges.
You are invited to submit your manuscript at any time before the submission deadline. For any inquiries about the appropriateness of contribution topics, please contact Prof. Xu Wang [email protected] , or Editorial Office via [email protected]; [email protected]".
The journal’s submission platform (Editorial Manager®) is now available for receiving submissions to this Special Issue at https://www.editorialmanager.com/ese/default.aspx
Please refer to the Guide for Authors to prepare your manuscript, and select the article type of “AI for Environment” when submitting your manuscript online. Both the Guide for Authors and the submission portal could be found on the Journal Homepage here: https://www.journals.elsevier.com/environmental-science-and-ecotechnology