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    Generating Technology Evolution Prediction Intervals Using a Bootstrap Method

    Source: Journal of Mechanical Design:;2019:;volume( 141 ):;issue: 006::page 61401
    Author:
    Zhang, Guanglu
    ,
    Allaire, Douglas
    ,
    McAdams, Daniel A.
    ,
    Shankar, Venkatesh
    DOI: 10.1115/1.4041860
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Technology evolution prediction is critical for designers, business managers, and entrepreneurs to make important decisions during product development planning such as R&D investment and outsourcing. In practice, designers want to supplement point forecasts with prediction intervals to assess future uncertainty and make contingency plans accordingly. However, prediction intervals generation for technology evolution has received scant attention in the literature. In this paper, we develop a generic method that uses bootstrapping to generate prediction intervals for technology evolution. The method we develop can be applied to any model that describes technology performance incremental change. We consider parameter uncertainty and data uncertainty and establish their empirical probability distributions. We determine an appropriate confidence level to generate prediction intervals through a holdout sample analysis rather than specify that the confidence level equals 0.05 as is typically done in the literature. In addition, our method provides the probability distribution of each parameter in a prediction model. The probability distribution is valuable when parameter values are associated with the impact factors of technology evolution. We validate our method to generate prediction intervals through two case studies of central processing units (CPU) and passenger airplanes. These case studies show that the prediction intervals generated by our method cover every actual data point in the holdout sample tests. We outline four steps to generate prediction intervals for technology evolution prediction in practice.
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      Generating Technology Evolution Prediction Intervals Using a Bootstrap Method

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    contributor authorZhang, Guanglu
    contributor authorAllaire, Douglas
    contributor authorMcAdams, Daniel A.
    contributor authorShankar, Venkatesh
    date accessioned2019-03-17T09:51:36Z
    date available2019-03-17T09:51:36Z
    date copyright1/31/2019 12:00:00 AM
    date issued2019
    identifier issn1050-0472
    identifier othermd_141_06_061401.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4255727
    description abstractTechnology evolution prediction is critical for designers, business managers, and entrepreneurs to make important decisions during product development planning such as R&D investment and outsourcing. In practice, designers want to supplement point forecasts with prediction intervals to assess future uncertainty and make contingency plans accordingly. However, prediction intervals generation for technology evolution has received scant attention in the literature. In this paper, we develop a generic method that uses bootstrapping to generate prediction intervals for technology evolution. The method we develop can be applied to any model that describes technology performance incremental change. We consider parameter uncertainty and data uncertainty and establish their empirical probability distributions. We determine an appropriate confidence level to generate prediction intervals through a holdout sample analysis rather than specify that the confidence level equals 0.05 as is typically done in the literature. In addition, our method provides the probability distribution of each parameter in a prediction model. The probability distribution is valuable when parameter values are associated with the impact factors of technology evolution. We validate our method to generate prediction intervals through two case studies of central processing units (CPU) and passenger airplanes. These case studies show that the prediction intervals generated by our method cover every actual data point in the holdout sample tests. We outline four steps to generate prediction intervals for technology evolution prediction in practice.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleGenerating Technology Evolution Prediction Intervals Using a Bootstrap Method
    typeJournal Paper
    journal volume141
    journal issue6
    journal titleJournal of Mechanical Design
    identifier doi10.1115/1.4041860
    journal fristpage61401
    journal lastpage061401-9
    treeJournal of Mechanical Design:;2019:;volume( 141 ):;issue: 006
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
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