Articles | Volume 19
https://doi.org/10.5194/asr-19-9-2022
https://doi.org/10.5194/asr-19-9-2022
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, https://www.mckinsey.com/business-functions/operations/our-insights/ensuring-adaptation-and-resilience-to-climate-change?cid=eml-web, 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. 
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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.