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Technology Forecasting (TF) using Hy...
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Garland, Genevieve Marie.
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Technology Forecasting (TF) using Hybrid Tech Mining, TRIZ TF for Research and Development Planning: Forecast for Nonwovens Air Filtration Media.
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Technology Forecasting (TF) using Hybrid Tech Mining, TRIZ TF for Research and Development Planning: Forecast for Nonwovens Air Filtration Media./
Author:
Garland, Genevieve Marie.
Description:
280 p.
Notes:
Source: Dissertation Abstracts International, Volume: 75-03(E), Section: B.
Contained By:
Dissertation Abstracts International75-03B(E).
Subject:
Textile Technology. -
Online resource:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3575725
ISBN:
9781303547065
Technology Forecasting (TF) using Hybrid Tech Mining, TRIZ TF for Research and Development Planning: Forecast for Nonwovens Air Filtration Media.
Garland, Genevieve Marie.
Technology Forecasting (TF) using Hybrid Tech Mining, TRIZ TF for Research and Development Planning: Forecast for Nonwovens Air Filtration Media.
- 280 p.
Source: Dissertation Abstracts International, Volume: 75-03(E), Section: B.
Thesis (Ph.D.)--North Carolina State University, 2013.
The objectives of this research were to identify the type of information found in tech mining and TRIZ TF forecasts and determine if combining tech mining and TRIZ TF forecast results offers improvements over either single method. The research was conducted in two phases. The first phase was to develop the hybrid, tech mining TRIZ TF methodology. In this phase a literature review was conducted on both methods then they were reviewed and combined to maximize the value of the hybrid forecast and minimize weaknesses in either method. In the second phase tech mining and TRIZ TF forecasts were conducted using data from 1950-2000 and forecasted for 2005 and 2010. To develop the forecasts nonwoven air filtration media was used as the forecasting topic. The two TF methodologies and hybrid forecast were described in detail and the results were evaluated for ease of use, time, value of information and accuracy. This research aimed to combine two methods not currently used in combination and compared the individual forecasts to the hybrid forecast. In addition this study contributed to the field of TF by offering an experimental, transparent approach for creating each forecast using the individual methods along with a systematic method for evaluating the forecasts.
ISBN: 9781303547065Subjects--Topical Terms:
1020710
Textile Technology.
Technology Forecasting (TF) using Hybrid Tech Mining, TRIZ TF for Research and Development Planning: Forecast for Nonwovens Air Filtration Media.
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Technology Forecasting (TF) using Hybrid Tech Mining, TRIZ TF for Research and Development Planning: Forecast for Nonwovens Air Filtration Media.
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280 p.
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Source: Dissertation Abstracts International, Volume: 75-03(E), Section: B.
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Adviser: William Oxenham.
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Thesis (Ph.D.)--North Carolina State University, 2013.
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The objectives of this research were to identify the type of information found in tech mining and TRIZ TF forecasts and determine if combining tech mining and TRIZ TF forecast results offers improvements over either single method. The research was conducted in two phases. The first phase was to develop the hybrid, tech mining TRIZ TF methodology. In this phase a literature review was conducted on both methods then they were reviewed and combined to maximize the value of the hybrid forecast and minimize weaknesses in either method. In the second phase tech mining and TRIZ TF forecasts were conducted using data from 1950-2000 and forecasted for 2005 and 2010. To develop the forecasts nonwoven air filtration media was used as the forecasting topic. The two TF methodologies and hybrid forecast were described in detail and the results were evaluated for ease of use, time, value of information and accuracy. This research aimed to combine two methods not currently used in combination and compared the individual forecasts to the hybrid forecast. In addition this study contributed to the field of TF by offering an experimental, transparent approach for creating each forecast using the individual methods along with a systematic method for evaluating the forecasts.
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http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3575725
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