WEATHER FORECASTING VIA THE MODELING OF TEMPERATURE

Abstract

The present work emphasizes on the geographical perspectives of temperature fluctuations and related environmental issues. In this scenario, we study weather forecasting via the techniques of simulated annealing. Simulated annealing provides significant tools in optimizing complex problems, relating socioeconomic importance in the contemporary sciences, engineering, economics and statistics. For the given shape parameter of the probing material and artificial time, we examine optimization properties of the environmental temperature beyond the notion of Boltzmann machine. As per the above analysis, for a given finite artificial temperature, we find that its fluctuations over the system parameters yield a stable configuration, depending on the signature of parameters. In addition, our investigation anticipates computational weather forecasting and modeling of climate changing effects in the light of quenching, optimal theory, artificial intelligence and neural networks.