“Forecasting and analysing the characteristics of 3G and 4G mobile broadband diffusion in India: A comparative evaluation of Bass, Norton-Bass, Gompertz, and logistic growth models”

Jha, Ashutosh; Saha, Debashis

doi:10.1016/j.techfore.2019.119885

Cited by 39 publications

(24 citation statements)

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“…For building the data-driven proxy model which can accurately and efficiently predict the Cum-oil production profile of the SAGD process, an appropriate knowledge-based performance indicator must be found and clearly defined. Various growth mathematic models derived from the biological growth field have been widely used in the research of population growth problems, cell growth problems, and other domains of life, social, and economic sciences. , Growth is a common feature in various scenarios including reservoir production. Among the aforementioned application scenarios, the growth mathematic model offers an effective tool to account the growth under given confronting expansion and restraint forces .…”

Section: Methodsmentioning

confidence: 99%

Data-Driven Proxy Model for Forecasting of Cumulative Oil Production during the Steam-Assisted Gravity Drainage Process

Liu

et al. 2021

ACS Omega

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The purpose of this study is to develop a data-driven proxy model for forecasting of cumulative oil (Cum-oil) production during the steam-assisted gravity drainage process. During the model building process, an artificial neural network (ANN) is used to offer a complementary and computationally efficient tool for the physics-driven model, and the von Bertalanffy performance indicator is used to bridge the physics-driven model with the ANN. After that, the accuracy of the model is validated by blind-testing cases. Average absolute percentage error of related parameters of the performance indicator in the testing data set is 0.77%, and the error of Cum-oil production after 20 years is 0.52%. The results illustrate that the integration of performance indicator and ANN makes it possible to solve time series problems in an efficient way. Besides, the data-driven proxy model could be applied to fast parametric studies, quick uncertainty analysis with the Monte Carlo method, and average daily oil production prediction. The findings of this study could help for better understanding of combination of physics-driven model and data-driven model and illustrate the potential for application of the data-driven proxy model to help reservoir engineers, making better use of this significant thermal recovery technology for oil sands or heavy oil reservoirs.

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Section: Methodsmentioning

confidence: 99%

Data-Driven Proxy Model for Forecasting of Cumulative Oil Production during the Steam-Assisted Gravity Drainage Process

Liu

et al. 2021

ACS Omega

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“…This models the adoption of new products or technologies in a given population m. It follows a binary diffusion pattern that has been classified into two types of adopters [45]:…”

Section: ) Bass Diffusion Model Explainedmentioning

confidence: 99%

Techno-Economic Analysis of 5G Non-Public Network Architectures

et al. 2022

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The adoption of private 5G networks or Non-Public Networks (NPN) by industry verticals is igniting a digital transformation across various sectors and also leading to industry 4.0. This impetus comes from the integration of private wireless networks with 5G capabilities. Currently, a range of innovative applications and use cases are emerging and resulting in improved enterprise performance and solutions. The potential to boost revenue, stimulate cost reduction, and accelerate Return Of Investment (ROI) makes 5G NPN adoption attractive to industry verticals, network operators and other third-party stakeholders. However, a significant infrastructure upgrade is required, which demands understanding of the complexities of 5G NPN deployment scenarios and their economic implications. This paper addresses these needs by conducting a detailed techno-economic analysis on 5G NPN deployment. The study formulates a technoeconomic model that focuses on; (i) Cost savings in support of ROI achieved by enabling Network Function Virtualization (NFV) technology and Neutral Host (NH) concept; (ii) The trade-off study between enterprise goals (cost vs deployment technologies) with a multi-objective sensitive analysis; And (iii) the trends of 5G NPN adoption worldwide. Analytical results confirm savings of up to 53% in Total Cost of Ownership (TCO) reflecting a significant reduction in Capital and Operation Expenditures (Capex and Opex). Simulation analysis identifies a ranking order of deployment parameters, which prioritise the use of Cost saving strategies and Deployment type. And finally, it offers a prediction of a starting annual average worldwide adoption rate of 82.2% with an expected height by 2026.

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“…The number of subscriptions supportable by the constellation uses the total constellation throughput, a 10 Mbps user data rate, and a conservative over subscription ratio of 5:1 [33]. A logistic curve [34,35] using satellite internet market growth projections published in Ref. [36] caps the subscriber base, .…”

Section: B Satcom System Modelmentioning

confidence: 99%