However, the forecast data obtained from regional models are available only for a specific country, and end-users cannot find them all in one place. They use global forecasting model and sensor-based weather monitoring network as the input parameters (global atmospheric situation at regional model geographic boundaries, description of atmospheric condition in numerical form), and because the analysed area is much smaller (typically one country), computing power allows them to use even higher resolution for key meteorological parameters prediction. Although ECMWF is currently the global weather system with the highest horizontal resolution, this resolution is still two times worse than the one offered by limited area (regional) numeric models (e.g., ALADIN that is used in many European and north African countries). This model is capable of providing forecast up to 10 days with horizontal resolution of 9 km. The European Centre for Medium-Range Weather Forecasts (ECMWF) model serves as the main base for medium-range predictions among the European countries. Sensor data collection and its processing is a necessity for finding the optimal weather conditions estimation. This data is obtained from automatic weather stations by intelligent sensors. Numerical weather models require real measured data for the correct forecast run. Predicted parameters, such as air temperature or precipitation, play a crucial role not only in the transportation sector but they also influence people’s everyday activities. If (slot) slot.addService(googletag.This paper presents a neural network approach for weather forecast improvement. (function (a, d, o, r, i, c, u, p, w, m) Tunnels used for missile production in Syria attacked in Monday strike - The Jerusalem Post
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