✦ LIBER ✦

Application of an artificial neural network to typhoon rainfall forecasting

✍ Scribed by Gwo-Fong Lin; Lu-Hsien Chen

Publisher: John Wiley and Sons
Year: 2005
Tongue: English
Weight: 163 KB
Volume: 19
Category: Article
ISSN: 0885-6087
DOI: 10.1002/hyp.5638

No coin nor oath required. For personal study only.

✦ Synopsis

A neural network with two hidden layers is developed to forecast typhoon rainfall. First, the model configuration is evaluated using eight typhoon characteristics. The forecasts for two typhoons based on only the typhoon characteristics are capable of showing the trend of rainfall when a typhoon is nearby. Furthermore, the influence of spatial rainfall information on rainfall forecasting is considered for improving the model design. A semivariogram is also applied to determine the required number of nearby rain gauges whose rainfall information will be used as input to the model. With the typhoon characteristics and the spatial rainfall information as input to the model, the forecasting model can produce reasonable forecasts. It is also found that too much spatial rainfall information cannot improve the generalization ability of the model, because the inclusion of irrelevant information adds noise to the network and undermines the performance of the network.

📜 SIMILAR VOLUMES

Performance of an artificial neural netw

Performance of an artificial neural network on forecasting the daily occurrence and annual depth of rainfall at a tropical site

✍ Akila D. Kumarasiri; Upul J. Sonnadara 📂 Article 📅 2008 🏛 John Wiley and Sons 🌐 English ⚖ 244 KB 👁 1 views

## Abstract Performance of a feed‐forward back‐propagation artificial neural network on forecasting the daily occurrence and annual depth of rainfall at a single meteorological station is presented. Both short‐term and long‐term forecasting was attempted, with ground level data collected by the met

Applications of artificial neural networ

Applications of artificial neural networks to RF and microwave measurements

✍ Jeffrey A. Jargon; K. C. Gupta; Donald C. DeGroot 📂 Article 📅 2001 🏛 John Wiley and Sons 🌐 English ⚖ 433 KB

This article describes how artificial neural networks (ANNs) can be used to benefit a number of RF and microwave measurement areas including vector network analysis (VNA). We apply ANNs to model a variety of on-wafer and coaxial VNA calibrations, including open-short-load-thru (OSLT) and line-reflec

Short-term electric load forecasting usi

Short-term electric load forecasting using an artificial neural network: case of Northern Vietnam

✍ Subhes C. Bhattacharyya; Le Tien Thanh 📂 Article 📅 2004 🏛 John Wiley and Sons 🌐 English ⚖ 131 KB 👁 1 views

Short-term electric load forecasting is an important requirement for electric system operation. This paper employs a feed-forward neural network with a back-propagation algorithm for three types of short-term electric load forecasting: daily peak (valley) load, hourly load and the total load. The fo

Application of tank, NAM, ARMA and neura

Application of tank, NAM, ARMA and neural network models to flood forecasting

✍ Tawatchai Tingsanchali; Mahesh Raj Gautam 📂 Article 📅 2000 🏛 John Wiley and Sons 🌐 English ⚖ 166 KB 👁 2 views

Two lumped conceptual hydrological models\ namely tank and NAM and a neural network model are applied to ~ood forecasting in two river basins in Thailand\ the Wichianburi on the Pasak River and the Tha Wang Pha on the Nan River using the ~ood forecasting procedure developed in this study[ The tank a

Forecasting Austrian IPOs: An applicatio

Forecasting Austrian IPOs: An application of linear and neural network error-correction models

✍ Christian Haefke; Christian Helmenstein 📂 Article 📅 1996 🏛 John Wiley and Sons 🌐 English ⚖ 942 KB

In this paper we apply cointegration and Granger-causality analyses to construct linear and neural network error-correction models for an Austrian Initial Public Offerings Index (IPOX,,). We use the significant relationship between the IPOX,, and the Austrian Stock Market Index ATX to forecast the I

Applications of knowledge-based artifici

Applications of knowledge-based artificial neural network modeling to microwave components

✍ P. M. Watson; K. C. Gupta; R. L. Mahajan 📂 Article 📅 1999 🏛 John Wiley and Sons 🌐 English ⚖ 197 KB 👁 2 views

This paper expands upon reported methods for utilizing prior knowledge for reducing complexity of input-output relationships that an ANN must learn. Previously, two simple methods, difference method and prior knowledge input method, were demonstrated for new model developments. This paper utilizes k