Deep learning on binary classification to identify concrete strength through cube, cylinder, and beam parameters

Vijayan, Dhanasingh Sivalinga and Parthiban, Devarajan and Sankaran, Naveen and Sangma, Sangsangrach and Sivasuriyan, Arvindan (2025) Deep learning on binary classification to identify concrete strength through cube, cylinder, and beam parameters. In: Deep learning on binary classification to identify concrete strength through cube, cylinder, and beam parameters.

Full text not available from this repository.

Abstract

The study's objective was to assess the Indoor Environmental Quality (IEQ) of 32 naturally ventilated classrooms using spider monkey metaheuristic regression in Bangalore, India. These classrooms, which had a total seating capacity of 805 students, were selected from various educational institutions throughout southern India. The researchers evaluated PM2.5 levels, carbon dioxide levels, water vapor levels, and ozone levels as factors. They used the spider monkey approach for multilinear regression analysis. The findings revealed that individuals are willing to tolerate higher temperatures for better Indoor Air Quality (IAQ). However, it is crucial to consider all aspects of IEQ, as dissatisfaction with a single component may not lead to widespread discomfort unless it is a significant issue. By identifying the most critical building controls, designers can ensure their clients' comfort. © 2025 Elsevier B.V., All rights reserved.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Cited by: 0
Subjects: Engineering > Civil and Structural Engineering
Divisions: Medicine > Vinayaka Mission's Kirupananda Variyar Medical College and Hospital, Salem > Medicine
Depositing User: Unnamed user with email techsupport@mosys.org
Date Deposited: 26 Nov 2025 07:00
Last Modified: 26 Nov 2025 07:00
URI: https://vmuir.mosys.org/id/eprint/139

Actions (login required)

View Item
View Item