Projects & Grants

Machine learning and fuzzy logic in biology
Project IdSGS05/ÚVAFM/2018
Main solverMgr. Stanislav Ožana
Periodr1/2018 - 12/2018
ProviderSpecifický VŠ výzkum
AnotationThis project should continue in developing applications for monitoring animal species (dragonflies, orthoptera, amphibians and reptiles) by utilizing fuzzy modeling and machine learning. In species conservation, it is essential to quantify accurately species occurrence and the degree of its endangerment. The existing approaches are highly dependent on the knowledge and experiences of the evaluator. This relates to uncertainty and subjectivity associated with incorrect data analysis and interpretation of results. The combination of mathematical, informatics and biological methods for creating new approaches for identifying species (with the possibility of using citizen science) or interpreting data seems to be ideal. The main aims of the project are as follows:1. Use of fuzzy logic and machine learning to improve classification algorithms in a freeware application - Dragonfly Hunter CZ2. Use of fuzzy logic and machine learning in creation of freeware application - amphibians and reptiles determination key of the Czech Republic3. Use of fuzzy logic and machine learning in the creation of backgrounds for freeware application - orthoptera determination key of the Czech Republic4. Design of a web map application for easy acquisition of environmental data from specific GPS points5. Use of fuzzy logic for language interpretation of biological dataThe research will be carried out by a collaboration of the Department of Biology and Ecology with the Department of Computer Science and the Institute for Research and Application of Fuzzy Modeling. The project results will be a new version of Dragonfly Hunter CZ with an innovative approach to species identification, an application designed to identify the amphibians and reptiles of the Czech Republic, publications in journals with IF and presentations at selected conferences (e.g. European Congress on Odonatology 2018).