Comparisons of Prediction Efficiency of Learning Effect between Neural Network and Learning Curve

碩士 === 朝陽科技大學 === 營建工程系碩士班 === 92 === In a repeatable construction project, same activity is repeatedly performed. Each time the activity is performed, the workers presumably discover how to make it better and quicker and such phenomena is called learning effect. The learning effect is usually forec...

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Main Authors:	Yeng-fu Lu, 盧彥夫
Other Authors:	none
Format:	Others
Language:	zh-TW
Published:	2004
Online Access:	http://ndltd.ncl.edu.tw/handle/tar8hv

id	ndltd-TW-092CYUT5582010
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spelling	ndltd-TW-092CYUT55820102019-05-15T20:21:34Z http://ndltd.ncl.edu.tw/handle/tar8hv Comparisons of Prediction Efficiency of Learning Effect between Neural Network and Learning Curve 類神經網路與學習曲線預測學習效應成效比較之研究 Yeng-fu Lu 盧彥夫碩士朝陽科技大學營建工程系碩士班 92 In a repeatable construction project, same activity is repeatedly performed. Each time the activity is performed, the workers presumably discover how to make it better and quicker and such phenomena is called learning effect. The learning effect is usually forecasted by learning curves for the sake of predicting completion time for a project. However, learning curves are usually more accurate for forecast duration in early construction stage than later one of a project. This research aims at comparing the efficiency of applying neural network and learning curves for the prediction of learning effect. Case study shows neural network providing a better quality in the forecasting learning phenomena. none 鄭道明 2004 學位論文 ; thesis 62 zh-TW
collection	NDLTD
language	zh-TW
format	Others
sources	NDLTD
description	碩士 === 朝陽科技大學 === 營建工程系碩士班 === 92 === In a repeatable construction project, same activity is repeatedly performed. Each time the activity is performed, the workers presumably discover how to make it better and quicker and such phenomena is called learning effect. The learning effect is usually forecasted by learning curves for the sake of predicting completion time for a project. However, learning curves are usually more accurate for forecast duration in early construction stage than later one of a project. This research aims at comparing the efficiency of applying neural network and learning curves for the prediction of learning effect. Case study shows neural network providing a better quality in the forecasting learning phenomena.
author2	none
author_facet	none Yeng-fu Lu 盧彥夫
author	Yeng-fu Lu 盧彥夫
spellingShingle	Yeng-fu Lu 盧彥夫 Comparisons of Prediction Efficiency of Learning Effect between Neural Network and Learning Curve
author_sort	Yeng-fu Lu
title	Comparisons of Prediction Efficiency of Learning Effect between Neural Network and Learning Curve
title_short	Comparisons of Prediction Efficiency of Learning Effect between Neural Network and Learning Curve
title_full	Comparisons of Prediction Efficiency of Learning Effect between Neural Network and Learning Curve
title_fullStr	Comparisons of Prediction Efficiency of Learning Effect between Neural Network and Learning Curve
title_full_unstemmed	Comparisons of Prediction Efficiency of Learning Effect between Neural Network and Learning Curve
title_sort	comparisons of prediction efficiency of learning effect between neural network and learning curve
publishDate	2004
url	http://ndltd.ncl.edu.tw/handle/tar8hv
work_keys_str_mv	AT yengfulu comparisonsofpredictionefficiencyoflearningeffectbetweenneuralnetworkandlearningcurve AT lúyànfū comparisonsofpredictionefficiencyoflearningeffectbetweenneuralnetworkandlearningcurve AT yengfulu lèishénjīngwǎnglùyǔxuéxíqūxiànyùcèxuéxíxiàoyīngchéngxiàobǐjiàozhīyánjiū AT lúyànfū lèishénjīngwǎnglùyǔxuéxíqūxiànyùcèxuéxíxiàoyīngchéngxiàobǐjiàozhīyánjiū
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Comparisons of Prediction Efficiency of Learning Effect between Neural Network and Learning Curve

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