Jan Caha
Mendel University
24 Papers
58 Citations
Jan Caha is an academic researcher from Mendel University. The author has contributed to research in topics: Fuzzy logic & Computer science. The author has an hindex of 5, co-authored 21 publications. Previous affiliations of Jan Caha include Palacký University, Olomouc & Technical University of Ostrava.
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Papers
Forest vulnerability zones in the Czech Republic
TL;DR: In this paper, a model of forest vulnerability zones (FVZ) constitutes an alternative to existing zones of forest health hazard caused by emissions, based on subjective classification of existing incidence of damage in forests.
19
Nontuberculous mycobacteria in the environment of Hranice Abyss, the world’s deepest flooded cave (Hranice karst, Czech Republic)
Ivo Pavlik,Milan Geršl,Milan Bartos,Vit Ulmann,Petra Kaucká,Jan Caha,Adrian Unc,Dana Hübelová,Ondrej Konecny,Helena Modra +9 more
TL;DR: The aim of the study was to ascertain the occurrence of NTM in the extreme environment of the water zone of the Hranice Abyss (HA) and the adjacent Zbrašov Aragonite Caves with consideration of their pathogenic relevance.
18
Discrimination between acute and chronic decline of Central European forests using map algebra of the growth condition and forest biomass fuzzy sets: A case study
TL;DR: The fuzzy model used suggests that improvement in forest health will depend on decreasing environmental load and restoration concordance between growth conditions and tree species composition.
10
Comparison of Fuzzy AHP Algorithms for Land Suitability Assessment
Jan Caha,Jaroslav Burian +1 more
- 22 Mar 2017
TL;DR: This paper focuses on a fuzzy Analytical Hierarchy Process (AHP) which is based on pairwise comparisons of criterion importance and, unlike the classic (crisp) AHP, it can contain uncertainty which allows the user to include imprecise or incomplete knowledge in an MCDM problem.
7
Optimal Path Problem with Possibilistic Weights
Jan Caha,Jiří Dvorský +1 more
- 01 Jan 2015
TL;DR: The ranking system based on the Theory of Possibility very well addresses the indistinguishability of fuzzy numbers and offers the user more information than only the optimal path.
7