Abstracts – Browse Results
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Ababutain, A Y (2002) A multi-criteria decision-making model for selection of BOT toll road proposals within the public sector, Unpublished PhD Thesis, , University of Pittsburgh.
Aktas, C B (2011) Impact of product lifetime on life cycle assessment results, Unpublished PhD Thesis, , University of Pittsburgh.
Aktas, E (2001) Structural design code calibration using reliability-based cost optimization, Unpublished PhD Thesis, , University of Pittsburgh.
Alkhathami, M M (2004) Examination of the correlation of critical success and delay factors in construction projects in the kingdom of Saudi Arabia, Unpublished PhD Thesis, , University of Pittsburgh.
Almazroa, D A (2003) Project delivery system decision framework using the weighting factors and analytic hierarchy process methods, Unpublished PhD Thesis, , University of Pittsburgh.
Amruthapuri, R S G R (2021) Partnership between diverse stakeholders: A potential solution to issues migrant construction workers face in Bengaluru, India, Unpublished PhD Thesis, , University of Pittsburgh.
Banawi, A A (2013) Improving construction processes by integrating lean, green, and six-sigma, Unpublished PhD Thesis, , University of Pittsburgh.
Bilec, M M (2007) A hybrid life cycle assessment model for construction processes, Unpublished PhD Thesis, , University of Pittsburgh.
Campion, N A (2015) Advancing life cycle assessment: Perspectives from the building and healthcare industries, Unpublished PhD Thesis, , University of Pittsburgh.
Hussain, M A D (2001) Value engineering expert system in suburban highway design (VEESSHD), Unpublished PhD Thesis, , University of Pittsburgh.
- Type: Thesis
- Keywords: highway; artificial neural network; creativity; expert system; investment; programming; value engineering; neural network
- ISBN/ISSN:
- URL: https://www.proquest.com/docview/276409254
- Abstract:
Value Engineering (VE) is a professionally applied, function-oriented, systematic team approach used to analyze and improve value in a product, facility design, system or service. VE is a powerful methodology for solving problems and/or reducing costs while improving performance/quality requirements. By enhancing value characteristics, VE increases customer satisfaction and adds value to an investment. Several studies have been developed to computerize this process. Most of them concentrate on the quantitative part of the process. The VE process consists of several phases, including the creativity phase and evaluation phase. Creativity depends on the human brain and cannot be computerized easily by conventional programming techniques. For this reason, the present research attempts to design an ES called Value Engineering Expert System in Suburban Highway Design (VEESSHD). VEESSHD employs the power and abilities of Expert Systems (ES) in solving complex problems to assist VE team in suburban highway design. The required knowledge and data for VEESSHD was extracted from the National Cooperative Highway Research Program (NCHRP) Report 282. Artificial Neural Networks (ANN) were employed as a complementary technique to treat the missing data. VEESSHD is intended to save experts' time and to encourage the exchange experience amongst team members. VEESSHD has been validated and found to be efficient based on the goal of this research and compared to the examples in NCHRP Report 282. Some future improvements are recommended to make the system more useful and to cover more areas in highway design.
Kalainesan, S (2007) Best management practices for highway construction site sedimentation basins, Unpublished PhD Thesis, , University of Pittsburgh.
Osman, A E (2006) Life cycle optimization model for integrated cogeneration and energy systems applications in buildings, Unpublished PhD Thesis, , University of Pittsburgh.
Rajagopalan, N (2011) Residential life cycle assessment modeling for green buildings and building products, Unpublished PhD Thesis, , University of Pittsburgh.
Sanoubar, S (2022) Temporal and spatial considerations in maintenance planning, Unpublished PhD Thesis, , University of Pittsburgh.