๐”– Bobbio Scriptorium
โœฆ   LIBER   โœฆ

An incorporative statistic and neural approach for crop yield modelling and forecasting

โœ Scribed by William W. Guo; Heru Xue


Book ID
106175718
Publisher
Springer-Verlag
Year
2011
Tongue
English
Weight
468 KB
Volume
21
Category
Article
ISSN
0941-0643

No coin nor oath required. For personal study only.


๐Ÿ“œ SIMILAR VOLUMES


An evaluation of a traditional and a neu
โœ David Cameron; Pauline Kneale; Linda See ๐Ÿ“‚ Article ๐Ÿ“… 2002 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 154 KB

## Abstract This study evaluates two (of the many) modelling approaches to flood forecasting for an upland catchment (the River South Tyne at Haydon Bridge, England). The first modelling approach utilizes โ€˜traditionalโ€™ hydrological models. It consists of a rainfallโ€“runoff model (the probability dis

An efficient neural network approach for
โœ M. S. Alam; A. Kranti; G. A. Armstrong ๐Ÿ“‚ Article ๐Ÿ“… 2009 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 401 KB

The present paper demonstrates the suitability of artificial neural network (ANN) for modelling of a FinFET in nano-circuit simulation. The FinFET used in this work is designed using careful engineering of source-drain extension, which simultaneously improves maximum frequency of oscillation f max b

Modeling and Forecasting the Yield Curve
โœ Rafael B. de Rezende; Mauro S. Ferreira ๐Ÿ“‚ Article ๐Ÿ“… 2011 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 376 KB ๐Ÿ‘ 2 views

## ABSTRACT This paper compares the inโ€sample fitting and the outโ€ofโ€sample forecasting performances of four distinct Nelsonโ€“Siegel class models: Nelsonโ€“Siegel, Bliss, Svensson, and a fiveโ€factor model we propose in order to enhance the fitting flexibility. The introduction of the fifth factor resu