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: () allowing undetermined number of multigeneration technologies and inconsecutive adoption of new technologies and () requiring less data for forecasting newborn technologies.
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Background Although pneumonia is a leading cause of death in New York City (NYC), limited data exist about the settings in which pneumonia ...
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Summary We tested whether prophylactic droperidol and ondansetron, in combination with a moderate dose of dexamethasone, were equally effe...
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by Demin Li, Carol Bentley, Jenna Yates, Maryam Salimi, Jenny Greig, Sarah Wiblin, Tasneem Hassanali, Alison H. Banham Therapeutic monoclon...
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ACS Nano DOI: 10.1021/acsnano.6b08567 from #AlexandrosSfakianakis via Alexandros G.Sfakianakis on Inoreader http://ift.tt/2oNpdhD via...
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Abstract Dermoscopy has demonstrated clinical benefits in improving early melanoma diagnosis and reducing unnecessary biopsies. Despite th...
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