Forecasting the Compressive Strength of SCC by ANNs

CHF 84.15
Auf Lager
SKU
QVAL9LU9DPL
Stock 1 Verfügbar
Geliefert zwischen Mo., 26.01.2026 und Di., 27.01.2026

Details

The book is subdivided into five chapters. Each chapter is briefly described as follows: Chapter 1 gives a general background of the subject matter and serves as an introductory chapter. It incorporates the background of the study, problem statement, objectives of the research and a brief on the outline. Chapter 2 comprises of information relevant to this work. It includes background information on concrete characteristics, self compacting concrete, artificial intelligence, and the application of artificial neural networks in concrete research. Chapter 3 is devoted to the methodology adopted to achieve the objectives of the research. This includes investigation of the best network used for the prediction of self compacting concrete characteristics by using published experimental data. Chapter 4 describes the details on modelling and programming. It also presents all steps in designing artificial neural network and comprises the results of the main proposed training functions to obtain the best network. Chapter 5 contains the conclusions arrived at and gives the recommendations for future works.

Autorentext

Civil and Energy Saving Engineer

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09783659199202
    • Genre Elektrotechnik
    • Sprache Englisch
    • Anzahl Seiten 180
    • Größe H220mm x B150mm x T11mm
    • Jahr 2012
    • EAN 9783659199202
    • Format Kartonierter Einband (Kt)
    • ISBN 978-3-659-19920-2
    • Titel Forecasting the Compressive Strength of SCC by ANNs
    • Autor Ali Papzan , Taksiah A. Majid , Azmi Megat Johari Megat
    • Untertitel The Application of Artificial Neural Networks to Predict the Compressive Strength of Self-Compacting Concretes
    • Gewicht 284g
    • Herausgeber LAP Lambert Academic Publishing

Bewertungen

Schreiben Sie eine Bewertung
Nur registrierte Benutzer können Bewertungen schreiben. Bitte loggen Sie sich ein oder erstellen Sie ein Konto.
Made with ♥ in Switzerland | ©2025 Avento by Gametime AG
Gametime AG | Hohlstrasse 216 | 8004 Zürich | Schweiz | UID: CHE-112.967.470