Advanced Computing Methods for Environmental Sustainability
A special issue of Mathematical and Computational Applications (ISSN 2297-8747).
Deadline for manuscript submissions: 15 May 2025 | Viewed by 65
Special Issue Editors
Interests: sustainable development; water resources management; hydrological modeling; artificial intelligence; time series analysis; rainfall–runoff relationship; wind energy; sediment load; evaporation; evapotranspiration; hydro-meteorological droughts; groundwater; water quality parameters modeling; novel meta-heuristic approaches applications; trend analysis; clustering; watershed planning and management
Special Issues, Collections and Topics in MDPI journals
2. Department of Civil Engineering, Ilia State University, 0162 Tbilisi, Georgia
Interests: developing novel algorithms and methods towards the innovative solution of hydrologic forecasting and modeling; suspended sediment modeling; forecasting, estimating, spatial and temporal analysis of hydro-climatic variables such as precipitation, streamflow, suspended sediment, evaporation, evapotranspiration, groundwater, lake level and water quality parameters; hydro-informatics
Special Issues, Collections and Topics in MDPI journals
Interests: storm water management; scenario modeling; climate change; low impact development; best management practices
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The rational management of a city and its infrastructure in response to increased pollution, climate change, natural and other disasters, for daily operation and emergency responses, is becoming critical to enhance livability for citizens. Creating healthy, sustainable urban environments necessitates advanced numerical tools for optimal design and management processes. Extreme weather events cause numerous economic and life losses in the changing climate and environment. It is, therefore, important to keep developing and improving our knowledge in the field of extreme weather vulnerability assessment and hazard alleviation. The main aim of this Special Issue is to explore various implementations of machine learning methods (MLMs) improved with metaheuristic algorithms (MAs) to advance the prediction and/or modeling of environmental variables, which have vital importance in sustainable and resilient environments. The topics of this Special Issue include, but are not limited to, the following:
- Forecasting of sustainable environmental variables (modeling streamflow, sediment, groundwater, lake level, evaporation, evapotranspiration, etc.) with advanced MLM;
- Optimization of available environmental variables with advanced computing methods;
- Probalistic and suspectibility studies with artifical intelligence to sustain environmental resources;
- Spatial and temporal extreme events modeling with novel models to conserve environmental resources (ER);
- Implementation of MLM with new metaheuristic algorithms in environmental variables Modeling.
Dr. Rana Muhammad Adnan
Prof. Dr. Ozgur Kisi
Dr. Mo Wang
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Mathematical and Computational Applications is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- sustainability in environmental
- machine learning in ER
- hybrid modeling with MLM
- hydrologic modeling with advanced MLM
- MAs implementation in ER
