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02472nam a22002417a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
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ft8859 |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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20251209141517.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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251209b ||||| |||| 00| 0 eng d |
| 041 ## - LANGUAGE CODE |
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| Language code of text/sound track or separate title |
engtag |
| 050 ## - LIBRARY OF CONGRESS CALL NUMBER |
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| Classification number |
T58.65 A68 2025 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
. |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Aquino, Althea Joie P.; Balajediong, Daphne Elaine D.; Manalo, Chris Czar J. |
| 245 ## - TITLE STATEMENT |
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| Title |
An A.I. based cost estimation system for material sourcing with product recommendations for architectural designs |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
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| Place of production, publication, distribution, manufacture |
. |
| Name of producer, publisher, distributor, manufacturer |
. |
| Date of production, publication, distribution, manufacture, or copyright notice |
c2025 |
| 300 ## - PHYSICAL DESCRIPTION |
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Capstone Project: (Bachelor of Science in Information Technology) - Pamantasan ng Lungsod ng Maynila, 2025 |
| 336 ## - CONTENT TYPE |
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text |
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text |
| Content type code |
text |
| 337 ## - MEDIA TYPE |
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unmediated |
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unmediated |
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unmediated |
| 338 ## - CARRIER TYPE |
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volume |
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volume |
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volume |
| 505 ## - FORMATTED CONTENTS NOTE |
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ABSTRACT: 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 ## - STUDY PROGRAM INFORMATION NOTE |
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| Classification |
Filipiniana |
| 655 ## - INDEX TERM--GENRE/FORM |
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academic writing |
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| Item type |
Thesis/Dissertation |