A primer on machine learning applications in civil engineering

著者

    • Deka, Paresh Chandra

書誌事項

A primer on machine learning applications in civil engineering

Paresh Chandra Deka

CRC Press, c2020

  • hbk.

大学図書館所蔵 件 / 全1件

この図書・雑誌をさがす

注記

Includes bibliographical references and index

内容説明・目次

内容説明

Machine learning has undergone rapid growth in diversification and practicality, and the repertoire of techniques has evolved and expanded. The aim of this book is to provide a broad overview of the available machine-learning techniques that can be utilized for solving civil engineering problems. The fundamentals of both theoretical and practical aspects are discussed in the domains of water resources/hydrological modeling, geotechnical engineering, construction engineering and management, and coastal/marine engineering. Complex civil engineering problems such as drought forecasting, river flow forecasting, modeling evaporation, estimation of dew point temperature, modeling compressive strength of concrete, ground water level forecasting, and significant wave height forecasting are also included. Features Exclusive information on machine learning and data analytics applications with respect to civil engineering Includes many machine learning techniques in numerous civil engineering disciplines Provides ideas on how and where to apply machine learning techniques for problem solving Covers water resources and hydrological modeling, geotechnical engineering, construction engineering and management, coastal and marine engineering, and geographical information systems Includes MATLAB (R) exercises

目次

1. Introduction 2. Artificial Neural Networks 3. Fuzzy Logic 4. Support Vector Machine 5. Genetic Algorithm (GA) 6. Hybrid Systems 7. Data Statistics and Analytics 8. Applications in the Civil Engineering Domain 9. Conclusion and Future Scope of Work

「Nielsen BookData」 より

詳細情報

ページトップへ