Зображення обкладинки

New Advances in Soft Computing in Civil Engineering AI-Based Optimization and Prediction /

Soft computing applications plays a crucial role in civil engineering applications, with engineers striving to create outstanding designs that prioritize safety, aesthetics, cost-efficiency, and environmental considerations. Advanced optimization techniques are especially valuable for complex system...

Повний опис

Збережено в:
Бібліографічні деталі
Співавтор: SpringerLink (Online service)
Інші автори: Bekdaş, Gebrail (Редактор), Nigdeli, Sinan Melih (Редактор)
Формат: Електронний ресурс eКнига
Мова:Англійська
Опубліковано: Cham : Springer Nature Switzerland : Imprint: Springer, 2024.
Редагування:1st ed. 2024.
Серія:Studies in Systems, Decision and Control, 547
Предмети:
Civil engineering.
Computational intelligence.
Artificial intelligence.
Civil Engineering.
Computational Intelligence.
Artificial Intelligence.
Онлайн доступ:https://doi.org/10.1007/978-3-031-65976-8
Теги: Додати тег
Немає тегів, Будьте першим, хто поставить тег для цього запису!
Зміст:
  • Introduction to Data Analysis and Machine Learning Applications in Civil Engineering
  • Application of Artificial Intelligence (AI) in Civil Engineering
  • Machine Learning Applications in Structural Engineering
  • A Multi Objective Optimal Design Process for Determination of Link Capacity Expansions
  • IoT with Deep Learning in Pipeline Risk Estimation Using Smart Cities Development
  • Forecasting of Lake Level by Soft Computing Approaches
  • Structural health monitoring using artificial intelligence Challenges, advances and applications
  • Optimizing Tuned Mass Damper by Examining Displacement Ratios with and without TMD System
  • Evaluation of Predictive Models for Mechanical Properties of Earth Based Composites for Sustainable Building Applications
  • Shear Wall Cost Optimization by Employing Harmony Search
  • Effect of CatBoost Parameters on Cost Minimiza-tion of Rectangular Section Reinforced Concrete Co lumns Under Uniaxial Bending Effect
  • Machine Learning Approaches for Predicting Compressive and Shear Strength of EB FRP Reinforced Concrete Elements: A Comprehensive Review
  • A modified Jaya algorithm for optimum design of carbon fiber reinforced polymers
  • Prediction of bi-linear strength envelope of unsaturated brazilian soils using machine learning techniques
  • Assessment of Unconfined Compressive Strength of Stabilized Soil using Artificial Intelligence Tools A Scientometrics Review
  • A Review of Deformations Prediction for Oil and Gas Pipelines using Machine and Deep Learning
  • Determination of the Effect of XGBoost's Parameters on a Structural Problem
  • Area Optimization of Bending Members with Different Shapes in terms of Pure Bending
  • A simplified flower pollination algorithm for structural optimization of trusses
  • Investigation of the effect of initial parameters on the performance of metaheuristic algorithms on a structural engineering problem
  • Geospatial Multi Criteria Decision Framework for Sanitary Landfill Site Selection in New Delhi, India
  • Comparing Classification Algorithms for Predicting Spatial Land Cover via Landscape Indices in Nashik, India.

Схожі ресурси