A Symbiotic Model for Accurate Weather Forecasting

Abstract

AbstractWith the advent and evolution of AI, ML and predictive analytics, weather forecasting has become an important area of research in the last few years. As the non-linearity in the nature of weather data is widely known, emphasis has been on non-linear prediction of the weather. However, despite the technological sophistication, weather prediction has lacked precision. The paper proposes a symbiotic model that harnesses the collaborative intelligence of all species and integrates it with modern forecasting systems to predict weather with pin-point accuracy. The developed system decodes the variables processed by various bio-indicators—plants, insects, birds and animals that are currently not a part of any weather forecasting system. Hence, the developed model shows multi-fold increase in the accuracy of weather prediction as it blends the intelligence of biomarkers and modern systems to forecast weather better.KeywordsWeather forecastingBio-indicatorsSymbiotic modelCollaborative intelligenceTraditional knowledge