Skip to main content

Prediction of mean monthly total ozone time series - application of radial basis function network

Buy Article:

$60.90 plus tax (Refund Policy)

Abstract:

The primary objective of the present paper is to apply Artificial Neural Network in the form of Radial Basis Function network to predict the mean monthly total ozone concentration over Arosa, Switzerland (46.8° N/9.68° E). The satellite observations of the total ozone content are based on the total ozone observations performed by the ground-based instrumentation. While analysing the dataset it was found that January, February and March are the months of maximum variability in the mean monthly total ozone over the stated region. Then, these three months were considered as the target months to frame the predictive model. After appropriate training and testing, it was found that Radial Basis Function network is a suitable neural net type for predicting the aforesaid time series. Moreover, this kind of neural net was found most adroit in predicting the mean monthly total ozone in the month of January.

Document Type: Research Article

DOI: http://dx.doi.org/10.1080/01431160701227695

Affiliations: Department of Information Technology, Pailan College of Management and Technology, Bengal Pailan Park, Kolkata - 700 104, India

Publication date: January 1, 2007

More about this publication?
tandf/tres/2007/00000028/00000018/art00005
dcterms_title,dcterms_description,pub_keyword
6
5
20
40
5

Access Key

Free Content
Free content
New Content
New content
Open Access Content
Open access content
Subscribed Content
Subscribed content
Free Trial Content
Free trial content
Cookie Policy
X
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more