Artificial Intelligence in Civil Engineering : Recent Advances / edited by Gebrail Bekdaş, Sinan Melih Nigdeli.

Format:

Book

Author/Creator:

Bekdaş, Gebrail.

Series:

Studies in Systems, Decision and Control, 2198-4190 ; 643

Language:

English

Subjects (All):

Computational intelligence.

Civil engineering.

Artificial intelligence.

Machine learning.

Computational Intelligence.

Civil Engineering.

Artificial Intelligence.

Machine Learning.

Local Subjects:

Computational Intelligence.

Civil Engineering.

Artificial Intelligence.

Machine Learning.

Physical Description:

1 online resource (700 pages)

Edition:

1st ed. 2026.

Place of Publication:

Cham : Springer Nature Switzerland : Imprint: Springer, 2026.

Summary:

Artificial Intelligence in Civil Engineering: Recent Advances provides a comprehensive overview of the latest developments in applying artificial intelligence (AI) techniques to solve complex civil engineering problems. Civil engineers today face challenges that demand not only safety and cost-effectiveness, but also sustainability and resilience against natural hazards. This volume demonstrates how AI offers powerful tools to meet these demands by transforming traditional engineering methodologies. The chapters present a broad spectrum of applications, including predicting shear wave velocity, slope stability, estimating uniaxial compressive strength of soils, optimization-based design of reinforced concrete retaining walls, structural control strategies for seismic resilience, and the integration of Building Information Modeling (BIM) with AI-driven solutions. Machine learning, deep learning, and metaheuristic algorithms are explored in detail, supported by real-world case studies and experimental data. By bridging theory with practice, the book highlights how AI enhances predictive accuracy, optimizes design processes, and reduces computational effort in engineering tasks. Researchers, graduate students, and practicing engineers will find this volume a timely reference, offering both methodological foundations and practical insights into AI-powered approaches that are reshaping the future of civil engineering.

Contents:

Recent Advences of Artificial Intelligence in Civil Engineering

Metaheuristic-based optimization and application of metaheuristics on reinforced concrete structure

Artificial neural networks model for natural frequency prediction in reinforced concrete slabs

Human-inspired optimization algorithms for cost minimization in reinforced concrete column design.-Multioutput Regression for Reinforced Retaining Wall Optimum Design with Machine Learning

Advanced Regression Strategies for Concrete Strength Estimation: A Comparative Ensemble Approach

Optimization of Triangular Reinforced Concrete Beam with Various Metaheuristic Algorithms

Metaheuristic-based Detailed Optimization of Reinforced Concrete T-beams and Evaluation of the Effect of Concrete Class

Artificial Intelligence for Structural Vibration Control: A Review of Previous Studies and Methodologies

Isolator Damping Capacity with Catboost Algorithm Hyperparameter Optimization in Classification

Optimum Multiple Tuned Mass Dampers for Soft Story Structure

Artificial Intelligence for Structural Health Monitoring: Techniques, Applications, and Future Directions

Surface Crack Detection Using Deep Learning and Stacking Ensemble

Optimization of Time-Cost-Environmental Impact Problems in Construction Projects with Grey Wolf Algorithm

Automated Machine Learning for the Prediction of Compression Index of Soils

Shear Wave Velocity Prediction Using Machine Learning

Geospatial LULC and LST Change Analysis with Future Growth Prediction Using Random-Forest and MLP-MCA Algorithms

Precipitation Forecasting in the Konya Closed Basin Using LSTM: A Comparative Analysis of Optimization Algorithms

Machine Learning for Water Quality Monitoring: Comparative Analysis of AI Models in River Assessment

A deep learning application to predict reservoir operations

Global Impact of Artificial Intelligence on the Sustainability of Civil Engineering Infrastructure

An Analysis of Rolling Horizon based Route Optimization for the Pickup-and-Delivery Problem with Time Windows in the Context of Paratransit Applications

Development of Feature Selection Based Preventive Railway Track Maintenance Decision System

Development of Machine Learning Algorithms Based Prediction of Power Efficient Railway Track Maintenance Model

Impact Of Artificial Intelligence in Civil Engineering Education.

Notes:

Description based on publisher supplied metadata and other sources.

ISBN:

3-032-07738-9

9783032077387

OCLC:

1568053390