Latent heat and sensible heat flux simulation in maize using artificial neural networks

摘要

Latent Heat (LE) and Sensible Heat (H) flux are two major components of the energy balance at the earth's surface, which play important roles in the water cycle and global warming. There are various methods for their estimation or measurement. Eddy covariance is a direct and accurate technique for their measurement. Some limitations lead to prevention of the extensive use of the eddy covariance technique. Therefore, simulation approaches can be utilized for their estimation. ANNs are the information processing systems, which can inspect the empirical data and investigate the relations (hidden rules) among them, and then make the network structure.