Knowledge-based Systems for Engineers and Scientists

Hopgood, Adrian A.

ISBN 10: 0849386160 / ISBN 13: 9780849386169

Editore: CRC Press, U.S.A., 1993

Riguardo questo articolo

1993 CRC Press first edition hardback, laminated pictorial boards, no dj; very good appearing, used copy, some highlighting of first 40 pages.; minor cover wear. 386 pages, index. 8vo. UK dealer.

Codice articolo 176W16

Dati bibliografici

• Titolo: Knowledge-based Systems for Engineers and Scientists
• Editore: CRC Press, U.S.A.
• Data di pubblicazione: 1993
• Lingua: Inglese
• ISBN 10: 0849386160
• ISBN 13: 9780849386169
• Rilegatura: Hardcover
• Edizione: 1st Edition
• Condizione: Good
• Condizione della sovraccoperta: No Jacket

Descrizione articolo

Riassunto

Knowledge-Based Systems for Engineers and Scientists describes the principles of knowledge-based systems and related techniques and their use in solving practical problems. The book explains a variety of techniques including the use of artificial intelligence toolkits and languages, rule-based systems, uncertainty, blackboard systems, object-oriented systems, and machine learning. The techniques are illustrated through their applications to practical problems in interpretation and diagnosis, design and selection, planning, and control. Knowledge-Based Systems for Engineers and Scientists is designed for practicing engineers and scientists wanting to learn about this exciting area of computing. It is also an excellent text for final-year undergraduate as well as graduate engineering and computer students wishing to strengthen their specialized computing skills.

Contenuti

Introduction
Artificial Intelligence
Knowledge-Based Systems
The Knowledge Base
Deduction, Abduction and Induction
The Inference Engine
Expert Systems
Knowledge Acquisition
Search
Integration with Other Software
Tools and Languages
Declarative Versus Procedural Programming
Expert System Shells
Artificial Intelligence Toolkits
Artificial Intelligence Languages
Lisp
Prolog
Pop-11
Comparison of AI Languages
Rule-Based Systems
Rules and Facts
A Rule-Based System for Boiler Control
Rule Examination and Rule Firing
Maintaining Consistency
The Closed World Assumption
Use of Variables within Rules
Forward Chaining (A Data-Driven Strategy)
Conflict Resolution
Backward Chaining (A Goal-Driven Strategy)
A Hybrid Strategy
Explanation Facilities
Dealing with Uncertainty
Sources of Uncertainty
Bayesian Updating
Certainty Theory
Possibility Theory-Fuzzy Sets and Fuzzy Logic
Other Techniques
Object-Oriented Systems
An Illustrative Example
Data Abstraction
Inheritance
Encapsulation
Dynamic (or Late) Binding
Type Checking
Message Passing and Function Calls
Class and Instance Relationships
Further Aspects of OOP
Frame-Based Systems
Machine Learning
Symbolic Learning by Induction
Optimization Algorithms
Neural Networks
Systems for Interpretation and Diagnosis
Deduction and Abduction for Diagnosis
Depth of Knowledge
Case-Based Reasoning
Model-Based Reasoning
Case-Study: A Blackboard System for Interpreting Ultrasonic Images
Systems for Design and Selection
The Design Process
Design as a Search Problem
Computer Aided Design
The Product Design Specification (PDS): A Case Study in Telecommunications
Conceptual Design
Constraint Propagation and Truth Maintenance
Case Study: The Design of a Lightweight Beam
Design as a Selection Exercise
Failure Modes Effects Analysis (FMEA)
Systems for Planning
Classical Planning Systems
STRIPS
Considering the Side-Effects of Actions
Hierarchical Planning
Postponement of Commitment
Job Shop Scheduling
Constraint-Based Analysis
Replanning and Reactive Planning
Systems for Control
Low-Level Control
Requirements of High-Level (Supervisory) Control
Blackboard Maintenance
Time-Constrained Reasoning
Fuzzy Controllers
The BOXES Controller
Neural Network Controllers
Statistical Process Control (SPC)
Concluding Remarks
Benefits
How to Proceed
Trends
Index