21st EANN 2020, 5 -7 June 2020, Greece

Application of Algorithmic Fuzzy Implications on Climatic Data

Stefanos Makariadis, Georgios Souliotis, Basil Papadopoulos


  In this paper we present a new Fuzzy Implication Generator via Fuzzy Negations which was generated via conical sections, in combination with the well-known Fuzzy Conjunction T-norm = min. Among these implications we choose the most appropriate one, after comparing them with the empiristic implication, which was created with the help of real temperature and humidity data from the Hellenic Meteorological Service. The use of the empiristic implication is based on real data and also it reduces the volume of the data but without cancelling them. Finally, the pseudo-code, which was used in the programming part of the paper, uses the new Fuzzy Implication Generator and approaches the empiristic implication satisfactorily which is our final goal.  

*** Title, author list and abstract as seen in the Camera-Ready version of the paper that was provided to Conference Committee. Small changes that may have occurred during processing by Springer may not appear in this window.