framework of perfect competition. It is strengthened here in the more general case of imperfect markets. We construct a simple …

model is also compared with five more models: multiple linear regression (MLR), artificial neural network (ANN), wavelet …-based MLR (WMLR), wavelet-based ANN (WANN) and wavelet–bootstrap–ANN (WBANN) models. Seven years of discharge data from seven … time series that are used as inputs to the MLR and ANN models to develop the WMLR and WANN models, respectively. Effective …

in this study. The system consists of multiple linear regression (MLR) equations, and the purpose is to nowcast the … MLR models are formulated with the cloud parameters as input and the target output being the peak wind speed associated … with the pre-monsoon thunderstorms. The MLR model is trained with the data and records from 2002 to 2009, and the results …

(MLR) were used to simulate daily pan evaporation (E<Subscript>p</Subscript>) at Pantnagar, located at the foothills of … December 31, 2004 were used for developing the ANN, CANFIS and MLR models. A comparison based on statistical indices such as … magnitudes of E<Subscript>p</Subscript> by the ANN, CANFIS and the MLR models. The architecture of ANN and CANFIS were managed by …