| Titre : |
Machine learning for civil and environmental engineers : a practical approach to data-driven analysis, axplainability, and causality |
| Type de document : |
document électronique |
| Auteurs : |
M.-Z. Naser, Auteur |
| Editeur : |
Hoboken, NJ : Wiley |
| Année de publication : |
2023 |
| Importance : |
1 fichier PDF |
| Présentation : |
ill. |
| ISBN/ISSN/EAN : |
978-1-119-89762-0 |
| Note générale : |
Mode d'accès : accès au texte intégral par :
- authentification après inscription à la plateforme EBSCOhost
ou
- adresse IP de l'École.
Bibliogr.- Index |
| Langues : |
Anglais (eng) |
| Mots-clés : |
Machine learning
Civil engineering--Data processing
Environmental engineering--Data processing |
| Index. décimale : |
004.8 Intelligence artificielle |
| Résumé : |
This textbook introduces engineers and engineering students to the applications of artificial intelligence (AI), machine learning (ML), and machine intelligence (MI) in relation to civil and environmental engineering projects and problems, presenting state-of-the-art methodologies and techniques to develop and implement algorithms in the engineering domain. Through real-world projects like analysis and design of structural members, optimizing concrete mixtures for site applications, examining concrete cracking via computer vision, evaluating the response of bridges to hazards, and predicating water quality and energy expenditure in buildings, this textbook offers readers in-depth case studies with solved problems that are commonly faced by civil and environmental engineers |
| Note de contenu : |
Summary :
1. Teaching methods for this textbook
2. Introduction to machine learning
3. Data and statistics
4. Machines learning algorithms
5. Performance fitness indicators and error metrics
... |
Machine learning for civil and environmental engineers : a practical approach to data-driven analysis, axplainability, and causality [document électronique] / M.-Z. Naser, Auteur . - Hoboken, NJ : Wiley, 2023 . - 1 fichier PDF : ill. ISBN : 978-1-119-89762-0 Mode d'accès : accès au texte intégral par :
- authentification après inscription à la plateforme EBSCOhost
ou
- adresse IP de l'École.
Bibliogr.- Index Langues : Anglais ( eng)
| Mots-clés : |
Machine learning
Civil engineering--Data processing
Environmental engineering--Data processing |
| Index. décimale : |
004.8 Intelligence artificielle |
| Résumé : |
This textbook introduces engineers and engineering students to the applications of artificial intelligence (AI), machine learning (ML), and machine intelligence (MI) in relation to civil and environmental engineering projects and problems, presenting state-of-the-art methodologies and techniques to develop and implement algorithms in the engineering domain. Through real-world projects like analysis and design of structural members, optimizing concrete mixtures for site applications, examining concrete cracking via computer vision, evaluating the response of bridges to hazards, and predicating water quality and energy expenditure in buildings, this textbook offers readers in-depth case studies with solved problems that are commonly faced by civil and environmental engineers |
| Note de contenu : |
Summary :
1. Teaching methods for this textbook
2. Introduction to machine learning
3. Data and statistics
4. Machines learning algorithms
5. Performance fitness indicators and error metrics
... |
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