000			02472nam a22002417a 4500
003			ft8859
005			20251209141517.0
008			251209b ||||| |||| 00| 0 eng d
041			_aengtag
050			_aT58.65 A68 2025
082			_a.
100	1		_a Aquino, Althea Joie P.; Balajediong, Daphne Elaine D.; Manalo, Chris Czar J.
245			_aAn A.I. based cost estimation system for material sourcing with product recommendations for architectural designs
264		1	_a. _b. _cc2025
300			_bCapstone Project: (Bachelor of Science in Information Technology) - Pamantasan ng Lungsod ng Maynila, 2025
336			_2text _atext _btext
337			_2unmediated _aunmediated _bunmediated
338			_2volume _avolume _bvolume
505			_aABSTRACT: Accurate early-stage cost estimation is crucial in architectural design, yet it remains a challenge due to various project complexities and client-specific requirements. This study introduces ArchEstimate, an intelligent system that enhances the pre-evaluation and cost estimation process for architectural projects in the Philippines. The system integrates Fuzzy Logic for the initial evaluation phase, taking into account client preferences, project type, and material selection criteria to suggest suitable materials based on predefined rules. In then employs an Artificial Neural Network (ANN) with ReLU activation to estimate the total project cost, using calculated Gross Floor Area (GFA) and selected materials to compute the cost per square meter. In addition, Multi-Criteria Decision Analysis (MCDA) is implemented to support product comparison and provide alternative recommendations based on supplier reliability, quality, and affordability. The system was trained and tested using historical cost data, achieving a precision rate between 90% and 97%, aligning with findings from existing literature that report ANN accuracy between 87% and 98% for similar tasks. The results demonstrate that ArchEstimate significantly improves the accuracy of architectural cost estimation and material selection, serving as a reliable decision-support tool for architects. Future iterations may include collaboration features for subcontractors and expanded databases to enhance usability across broader construction applications. This approach positions ArchEstimates as a valuable innovation in digital construction planning and project managem
526			_aF
655			_aacademic writing
942			_2lcc _cMS
999			_c37310 _d37310