Articles | Volume 19
Adv. Sci. Res., 19, 9–12, 2022
Adv. Sci. Res., 19, 9–12, 2022
23 Mar 2022
23 Mar 2022

“My personal forecast”: the digital transformation of the weather forecast communication using a fuzzy logic recommendation system

Dimitrios S. Stamoulis and Panos A. Giannopoulos

Cited articles

Agboola, A. H., Gabriel, A. J., Aliyu, E. O., and Alese, B. K.: Development of a fuzzy logic based rainfall prediction model, International Journal of Engineering and Technology, 3, 427–435, 2013. 
Al-Matarneh, L., Sheta, A., Bani-Ahmad, S., Alshaer, J., and Al-Oqily, I.: Development of temperature-based weather forecasting models using neural networks and fuzzy logic, International Jjournal of Multimedia and Ubiquitous Engineering, 9, 343–366, 2014. 
Boland, B., Charchenko, E., and Sehdev, S.: Ensuring adaptation and resilience to climate change,, last access: 22 September 2021. 
Cao, Y. and Li, Y.: An intelligent fuzzy-based recommendation system for consumer electronic products, Expert Syst. Appl., 33, 230–240, 2007. 
Fischhoff, B. and Scheufele, D. A.: The science of science communication, P. Natl. Acad. Sci. USA, 110, 14031–14032, 2013. 
Short summary
Weather forecast refers to objective estimations of parameters such as temperature, wind, humidity etc. However, attempts have been made to communicate the weather forecast into a more subjective approach, such as the "feels like" temperature. We propose an architecture for an artificial intelligence-based system to provide a forecast that could be more meaningful and actionable for each individual person; a forecast much closer to the way that this person "lives" the weather conditions.