𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Forecasting Air Quality Parameters Using Hybrid Neural Network Modelling

✍ Scribed by Mikko Kolehmainen; Hannu Martikainen; Teri Hiltunen; Juhani Ruuskanen


Book ID
110236108
Publisher
Springer
Year
2000
Tongue
English
Weight
102 KB
Volume
65
Category
Article
ISSN
0167-6369

No coin nor oath required. For personal study only.


πŸ“œ SIMILAR VOLUMES


Modelling of a direct evaporative air co
✍ M. Hosoz; H. M. Ertunc; A. F. Ozguc πŸ“‚ Article πŸ“… 2007 πŸ› John Wiley and Sons 🌐 English βš– 147 KB πŸ‘ 1 views

This paper proposes the use of artificial neural networks (ANNs) to predict various performance parameters of a direct evaporative air cooler. For this aim, an experimental evaporative cooler was operated at steady-state conditions, while varying the dry bulb temperature and relative humidity of the

Short-term inflow forecasting using an a
✍ Z. X. Xu; J. Y. Li πŸ“‚ Article πŸ“… 2002 πŸ› John Wiley and Sons 🌐 English βš– 230 KB πŸ‘ 1 views

## Abstract The primary objective of this study is to investigate the possibility of including more temporal and spatial information on short‐term inflow forecasting, which is not easily attained in the traditional time‐series models or conceptual hydrological models. In order to achieve this objec

Modelling of hot strip rolling process u
✍ H.J. Kim; M. Mahfouf; Y.Y. Yang πŸ“‚ Article πŸ“… 2008 πŸ› Elsevier Science 🌐 English βš– 931 KB

A neural network-based approach is developed to predict a mechanical property for the hot-rolled alloy strip. Using a data set containing critical information on the mechanical property which was obtained from a POSCO hot strip mill, a neural network-based model is elicited. A compact set of process