Recent Advances in Civil Engineering for Sustainable Communities Select Proceeding of IACESD 2023
This book presents select proceedings of the International Conference on Interdisciplinary Approaches in Civil Engineering for Sustainable Development (IACESD 2023). The topics covered include geographic information systems (GIS) and building information modeling (BIM), integration of numerical meth...
Other Authors: | , , , |
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Format: | eBook |
Language: | English |
Published: |
Singapore
Springer Nature Singapore
2024, 2024
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Edition: | 1st ed. 2024 |
Series: | Lecture Notes in Civil Engineering
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Subjects: | |
Online Access: | |
Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
Table of Contents:
- Recent Advances in Civil Engineering for Sustainable Communities - An Introduction
- Investigation on Compressive Strength of Fibre Reinforced Concrete Using Artificial Neural Network
- Conventional and Ensemble Machine Learning Techniques to Predict the Compressive Strength of Sustainable Concrete
- Experimental Study on Strength Properties of Concrete Incorporated with Bacteria
- Predicting the Porosity of SCM-blended Concrete Composites Using Ensemble Machine Learning Models
- Ensemble Machine Learning Models to Predict the Compressive Strength and Ultrasonic Pulse Velocity of Sustainable Concrete
- Prognosis of Concrete Strength: The State of Art in Using Different Machine Learning Algorithms
- Experimental Study on Strength and Durability Characteristics of Mortars with TiO2 Nanoparticles
- Optimizing Sustainable Construction Materials with Machine Learning Algorithms: Predicting Compressive Strength of Concrete Composites
- Group Indexing of Fly Ashes using Unsupervised
- Learning and Fuzzy Clustering Techniques
- Study on Self-Healing Properties of Bacteria based Cement Mortar with Eggshell Powder and Jute fibre
- A Study on Repair Effectiveness of Damaged RC Beams with Circular Openings Using CFRP Sheet
- ELA and AAR Dynamics of Glaciers in Chandra Basin, Western Himalayas
- GIS Applications and Machine Learning Approaches in Civil Engineering
- Structural Health Monitoring by Simultaneous Measurement of Strain and Temperature Using Different Materials