Cost overrun prediction for building construction projects in UAE using artificial neural networks / by Ahmed Abu Zanat

By:

Zanat, Ahmed Abu

Description: i, 113 p. : ill. ; 30 cmContent type:

text

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unmediated

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volume

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Dissertation note: Master of Science in Construction Management American University in Dubai 2018 Summary: This thesis looks at the cost overrun prediction model to be used in the pre-construction stage, tailored to the UAE construction industry to help decision makers in financial and investment planning using artificial neural networks.

Holdings
Item type	Current library	Home library	Collection	Call number	Materials specified	Status	Notes	Barcode
Theses and Dissertations	American University in Dubai	American University in Dubai	Non-fiction	THESIS 2018 ZANA (Browse shelf(Opens below))	Thesis	Available	Within Library Use (no photocopying permitted)	5180591

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Previous	THESIS 2017 AYYA Evaluating the effect of TQM on MEP construction productivity in Dubai	THESIS 2018 MAWA An enhanced method to schedule the operation of vertical supply systems of high-rise projects	THESIS 2018 SARR A comprehensive near-optimal, cost-based planning method for construction projects /	THESIS 2018 ZANA Cost overrun prediction for building construction projects in UAE using artificial neural networks /	THESIS 2019 ALFAW Assessing the impact of autonomous vehicles on signalized intersection efficiency and pavement life cycle	THESIS 2019 DABA A comparative study of local and international green building rating systems	THESIS 2019 ELKH Feasibility study of retrofitting schools using green building rating systems	Next

Master of Science in Construction Management American University in Dubai 2018

Includes bibliographical references (pages 63-70).

This thesis looks at the cost overrun prediction model to be used in the pre-construction stage, tailored to the UAE construction industry to help decision makers in financial and investment planning using artificial neural networks.

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Cost overrun prediction for building construction projects in UAE using artificial neural networks / by Ahmed Abu Zanat

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