| dc.contributor.author | Kalimuthu, Bavithra | |
| dc.contributor.author | Rajendran, Mohana | |
| dc.date.accessioned | 2026-08-20T21:25:39Z | |
| dc.date.available | 2026-08-20T21:25:39Z | |
| dc.date.copyright | 2026/05/15 | |
| dc.date.issued | 2026 | |
| dc.identifier.other | JCCEE5.CPENG-6792.pdf | |
| dc.identifier.uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4314435 | |
| dc.description.abstract | AbstractEmerging infrastructure development demands the use of advanced construction materials
such as nanomaterials and high-performance concrete (HPC). Simultaneously, assessing
the environmental impact (EI) of these materials is critically important ...Practical ApplicationsFrom a practical standpoint, the developed ANN-based framework serves as a decision-support
tool for engineers, researchers, and policymakers. Unlike conventional LCA tools that
require extensive manual data entry and provide single-... | |
| dc.publisher | American Society of Civil Engineers | |
| dc.title | ANN-Based Machine Learning Approach for Predicting the Environmental Impacts of Emerging Nano Impregnated High-Performance Concrete | |
| dc.type | Journal Article | |
| dc.journal.volume | 40 | |
| dc.journal.issue | 4 | |
| dc.journal.title | Journal of Computing in Civil Engineering | |
| dc.identifier.doi | 10.1061/JCCEE5.CPENG-6792 | |
| dc.journal.fristpage | 04026049-1 | |
| dc.journal.lastpage | 04026049-24 | |
| dc.page | 24 | |
| dc.tree | Journal of Computing in Civil Engineering:;2026:;Volume ( 040 ):;issue: 004 | |
| dc.contenttype | Fulltext | |