Nowadays, sustainable development is one of the priorities of states policies. Decision making is based on correct information on environmental data, high quality models and future forecasting.
Due to the large connection between the environmental phenomena and processes, modeling is an important part of critical evaluation of the data issued from experimental observation. Therefore, the aim of this session is to improve the knowledge on the environmental systems’ behavior, based on models developed using new techniques and validated on reliable data bases.
Thematic areas include, but are not limited to:
- Statistical methods for data analysis with applications to real data
- Parametrical versus non-parametric approach in environment data modeling
- Critical evaluation and comparisons of alternative approaches and existing models used for solving specific environmental problems
- New models with applications in different environment sectors
- Optimization of decision making in environmental management
- Environmental software for data analysis – development and applications
- Soft computing and fuzzy techniques for trend seasonality/ciclicity detection;
- Techniques for spatial data analysis