This paper presents review of application of artificial neural networks in weather classification and prediction; some existing weather forecasting models have limitations and also benefits of neural network are discussed in this paper. Accurate weather prediction is important in today’s world as agricultural sector is widely dependent on it. Since there is non-linearity in weather data therefo...

Despite the existence of several weather studies in the tourism literature, there remain some gaps in knowledge. Uncertainty about weather conditions persists despite the impressive improvements in modern forecasting techniques. This study is a first attempt to investigate how weather uncertainty affects tourism demand. The findings indicate that the impact of weather on tourism demand is likel...

Weather forecasting in the short range and long range has improved dramatically over the years (Anderson et al. 1999; Barnston et al. 2005; Lupo and Market, 2002, 2003). Weather forecasts in the short range are routinely issued for as long as seven to ten days. Long range forecasts are routinely issued at least one month to more than a year in advance. Short range forecasting is an initial valu...

Multilayered feed forward neural networks possess a number of properties which make them particularly suited to complex problems. Neural networks have been in use in numerous meteorological applications including weather forecasting. As Neural Networks are being more and more widely used in recent years, the need for their more formal definition becomes increasingly apparent. This paper present...

Space weather forecasting critically depends upon availability of timely and reliable observational data. It is therefore particularly important to understand how existing and newly planned observational assets perform during periods of severe space weather. Extreme space weather creates challenging conditions under which instrumentation and spacecraft may be impeded or in which parameters reac...