A Modified Lotka–Volterra Model for Diffusion and Substitution of Multigeneration DRAM Processing Technologies. (21st May 2017)
- Record Type:
- Journal Article
- Title:
- A Modified Lotka–Volterra Model for Diffusion and Substitution of Multigeneration DRAM Processing Technologies. (21st May 2017)
- Main Title:
- A Modified Lotka–Volterra Model for Diffusion and Substitution of Multigeneration DRAM Processing Technologies
- Authors:
- Hung, Hui-Chih
Chiu, Yu-Chih
Wu, Muh-Cherng - Other Names:
- Mahomed Fazal M. Academic Editor.
- Abstract:
- Abstract : We attempt to develop an effective forecasting model for the diffusion and substitution of multigeneration Dynamic Random Access Memory (DRAM) processing technologies. We consider market share data and propose a modified Lotka–Volterra model, in which an additional constraint on the summation of market share is introduced. The mean absolute error is used to measure the accuracy of our market share predictions. Market share data in DRAM industries from quarter one (Q1) of 2005 to 2013 Q4 is collected to validate the prediction accuracy. Our model significantly outperforms other benchmark forecasting models of both revenue and market share data, including the Bass and Lotka–Volterra models. Compared to prior studies on forecasting the diffusion and substitution of multigeneration technologies, our model has two new perspectives: (1 ) allowing undetermined number of multigeneration technologies and inconsecutive adoption of new technologies and (2 ) requiring less data for forecasting newborn technologies.
- Is Part Of:
- Mathematical problems in engineering. Volume 2017(2017)
- Journal:
- Mathematical problems in engineering
- Issue:
- Volume 2017(2017)
- Issue Display:
- Volume 2017, Issue 2017 (2017)
- Year:
- 2017
- Volume:
- 2017
- Issue:
- 2017
- Issue Sort Value:
- 2017-2017-2017-0000
- Page Start:
- Page End:
- Publication Date:
- 2017-05-21
- Subjects:
- Engineering mathematics -- Periodicals
510.2462 - Journal URLs:
- https://www.hindawi.com/journals/mpe/ ↗
http://www.gbhap-us.com/journals/238/238-top.htm ↗ - DOI:
- 10.1155/2017/3038203 ↗
- Languages:
- English
- ISSNs:
- 1024-123X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 23548.xml