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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Purpose: The MHC-unrestricted activity of cytokine-induced killer (CIK) cells against chemo-surviving melanoma cancer stem cells (mCSC) was...
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Publication date: 18 April 2017 Source: Cell Reports, Volume 19, Issue 3 Author(s): David Estoppey, Chia Min Lee, Marco Janoschke, Boon He...
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from #AlexandrosSfakianakis via Alexandros G.Sfakianakis on Inoreader http://ift.tt/2oLOayI via IFTTT
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Abstract Functionalised electrospun polyamide-6 (PA-6) nanofibres incorporating gadolinium oxide nanoparticles conjugated to zinc tetracar...
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Cytokine-dependent renewal of stem cells is a fundamental requisite for tissue homeostasis and regeneration. Spermatogonial progenitor cells...
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Vol.20 No.1 from #AlexandrosSfakianakis via Alexandros G.Sfakianakis on Inoreader http://ift.tt/2seUCMY via IFTTT
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Abstract This paper addresses the hybrid consensus-based formation keeping problem for nonholonomic mobile robots in the presence of a nov...
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