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Artificial Intelligence in Structural Engineering

Overview of attention for book
Cover of 'Artificial Intelligence in Structural Engineering'

Table of Contents

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    Book Overview
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    Chapter 1 Structural monitoring of civil structures using vibration measurement Current practice and future
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    Chapter 2 Object-oriented software patterns for engineering design standards processing
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    Chapter 3 Design and verification of real-time systems
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    Chapter 4 Using knowledge nodes for knowledge discovery and collaboration
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    Chapter 5 Heating system design support
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    Chapter 6 Collaborative desktop engineering
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    Chapter 7 Towards personalized structural engineering tools
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    Chapter 8 Complex systems: Why do they need to evolve and how can evolution be supported
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    Chapter 9 Formalizing product model transformations: Case examples and applications
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    Chapter 10 Internet-based web-mediated collaborative design and learning environment
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    Chapter 11 Wearable computers for field inspectors: Delivering data and knowledge-based support in the field
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    Chapter 12 Conceptual designing as a sequence of situated acts
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    Chapter 13 Some personal experience in computer aided engineering research
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    Chapter 14 Knowledge discovery from multimedia case libraries
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    Chapter 15 Customisable knowledge bases for conceptual design
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    Chapter 16 Articulate design of free-form structures
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    Chapter 17 Applying quantitative constraint satisfaction in preliminary design
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    Chapter 18 Agents in computer-assisted collaborative design
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    Chapter 19 A collaborative negotiation methodology for large scale civil engineering and architectural projects
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    Chapter 20 An investigation into the integration of neural networks with the structured genetic algorithm to aid conceptual design
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    Chapter 21 Finding the right model for bridge diagnosis
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    Chapter 22 Knowledge-based assistants in collaborative engineering
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    Chapter 23 CAD modelling in multidisciplinary design domains
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    Chapter 24 A family of software components to deliver solutions for the interpretation of monitoring data
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    Chapter 25 AI methods in concurrent engineering
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    Chapter 26 A new collaborative design environment for engineers and architects
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    Chapter 27 Intelligent structures: A new direction in structural control
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    Chapter 28 Integration of expert systems in a structural design office
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    Chapter 29 Teaching knowledge engineering: Experiences
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    Chapter 30 Design support for viaducts
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    Chapter 31 Converting function into object
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    Chapter 32 Software agent techniques in design
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    Chapter 33 Case-based design process facilitating collaboration and information evolution
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    Chapter 34 Shared experiences: Management of experiential knowledge in the building industry
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    Chapter 35 Dam safety: Improving management
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    Chapter 36 Artificial Intelligence in Structural Engineering
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    Chapter 37 Proposal for 4.5 dimensional design via product models and expert system
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    Chapter 38 A product information system based on dynamic classification
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    Chapter 39 Structural monitoring: Decision-support through multiple data interpretations
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    Chapter 40 Augmented reality applications to structural monitoring
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    Chapter 41 Analysis and design of the as-built model
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    Chapter 42 On theoretical backgrounds of CAD
Overall attention for this book and its chapters
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Citations

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Title
Artificial Intelligence in Structural Engineering
Published by
Springer Berlin Heidelberg, January 1998
DOI 10.1007/bfb0030438
ISBNs
978-3-54-064806-2, 978-3-54-068593-7
Editors

Ian Smith

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X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
 Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 2 40%
Student > Master 1 20%
Student > Ph. D. Student 1 20%
Unspecified 1 20%
Readers by discipline Count As %
Computer Science 3 60%
Business, Management and Accounting 1 20%
Unspecified 1 20%

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