A grey system approach for forecasting disposable computer waste quantities: a case study of Delhi
Preeti Loonker Kothari,
Poonam Ahluwalia and
Arvind K. Nema
International Journal of Business Continuity and Risk Management, 2011, vol. 2, issue 3, 203-218
Abstract:
An optimised long-term planning for the management of disposable computer waste is a dire need of present owing to the exponentially growing waste quantities. Assessment of waste inventory is one of the first steps in the planning process. An efficient planning needs assessment of waste generation quantities and for long term planning, forecasting future quantities is of prime importance. This study presents a grey approach for forecasting computer waste quantities. The approach has been applied to a case study of computer waste generation in Delhi. Based on grey relational analysis, the key variables (personal computer penetration rate, population, gross domestic product, and gross national income per capita) were identified and their effect on computer waste generation was determined. Generalised regression neural network was used to minimise errors in the forecasted waste quantities.
Keywords: computer waste; forecasting; grey system theory; grey relational analysis; GRA; waste management; waste generation quantities; long term planning; India; personal computers; PCs; generalised regression NNs; GRNNs; neural networks. (search for similar items in EconPapers)
Date: 2011
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.inderscience.com/link.php?id=42300 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:ids:ijbcrm:v:2:y:2011:i:3:p:203-218
Access Statistics for this article
More articles in International Journal of Business Continuity and Risk Management from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().