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contributor authorKalimuthu, Bavithra
contributor authorRajendran, Mohana
date accessioned2026-08-20T21:25:39Z
date available2026-08-20T21:25:39Z
date copyright2026/05/15
date issued2026
identifier otherJCCEE5.CPENG-6792.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4314435
description abstractAbstractEmerging 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-...
publisherAmerican Society of Civil Engineers
titleANN-Based Machine Learning Approach for Predicting the Environmental Impacts of Emerging Nano Impregnated High-Performance Concrete
typeJournal Article
journal volume40
journal issue4
journal titleJournal of Computing in Civil Engineering
identifier doi10.1061/JCCEE5.CPENG-6792
journal fristpage04026049-1
journal lastpage04026049-24
page24
treeJournal of Computing in Civil Engineering:;2026:;Volume ( 040 ):;issue: 004
contenttypeFulltext


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