Verification and Validation of Complex Systems: Human Factors Issues

Verification and Validation of Complex Systems: Human Factors Issues
Author: John A. Wise
Publisher: Springer Science & Business Media
Total Pages: 682
Release: 2013-06-29
Genre: Computers
ISBN: 3662029332

Despite its increasing importance, the verification and validation of the human-machine interface is perhaps the most overlooked aspect of system development. Although much has been written about the design and developmentprocess, very little organized information is available on how to verifyand validate highly complex and highly coupled dynamic systems. Inability toevaluate such systems adequately may become the limiting factor in our ability to employ systems that our technology and knowledge allow us to design. This volume, based on a NATO Advanced Science Institute held in 1992, is designed to provide guidance for the verification and validation of all highly complex and coupled systems. Air traffic control isused an an example to ensure that the theory is described in terms that will allow its implementation, but the results can be applied to all complex and coupled systems. The volume presents the knowledge and theory ina format that will allow readers from a wide variety of backgrounds to apply it to the systems for which they are responsible. The emphasis is on domains where significant advances have been made in the methods of identifying potential problems and in new testing methods and tools. Also emphasized are techniques to identify the assumptions on which a system is built and to spot their weaknesses.

Methods and Procedures for the Verification and Validation of Artificial Neural Networks

Methods and Procedures for the Verification and Validation of Artificial Neural Networks
Author: Brian J. Taylor
Publisher: Springer Science & Business Media
Total Pages: 300
Release: 2006
Genre: Computers
ISBN: 9780387282886

Neural networks are members of a class of software that have the potential to enable intelligent computational systems capable of simulating characteristics of biological thinking and learning. This volume introduces some of the methods and techniques used for the verification and validation of neural networks and adaptive systems.

Guidance for the Verification and Validation of Neural Networks

Guidance for the Verification and Validation of Neural Networks
Author: Laura L. Pullum
Publisher: John Wiley & Sons
Total Pages: 146
Release: 2007-03-09
Genre: Computers
ISBN: 047008457X

This book provides guidance on the verification and validation of neural networks/adaptive systems. Considering every process, activity, and task in the lifecycle, it supplies methods and techniques that will help the developer or V&V practitioner be confident that they are supplying an adaptive/neural network system that will perform as intended. Additionally, it is structured to be used as a cross-reference to the IEEE 1012 standard.

Methods and Procedures for the Verification and Validation of Artificial Neural Networks

Methods and Procedures for the Verification and Validation of Artificial Neural Networks
Author: Brian J. Taylor
Publisher: Springer Science & Business Media
Total Pages: 280
Release: 2006-03-20
Genre: Computers
ISBN: 0387294856

Neural networks are members of a class of software that have the potential to enable intelligent computational systems capable of simulating characteristics of biological thinking and learning. Currently no standards exist to verify and validate neural network-based systems. NASA Independent Verification and Validation Facility has contracted the Institute for Scientific Research, Inc. to perform research on this topic and develop a comprehensive guide to performing V&V on adaptive systems, with emphasis on neural networks used in safety-critical or mission-critical applications. Methods and Procedures for the Verification and Validation of Artificial Neural Networks is the culmination of the first steps in that research. This volume introduces some of the more promising methods and techniques used for the verification and validation (V&V) of neural networks and adaptive systems. A comprehensive guide to performing V&V on neural network systems, aligned with the IEEE Standard for Software Verification and Validation, will follow this book.

RIACS Workshop on the Verification and Validation of Autonomous and Adaptive Systems

RIACS Workshop on the Verification and Validation of Autonomous and Adaptive Systems
Author: Charles Pecheur
Publisher:
Total Pages: 12
Release: 2001
Genre: Computer software
ISBN:

The long-term future of space exploration at NASA is dependent on the full exploitation of autonomous and adaptive systems : careful monitoring of missions from earth, as is the norm now, will be infeasible due to the sheer number of proposed missions and the communication lag for deep-space missions. Mission managers are however worried about the reliability of these more intelligent systems. The main focus of the workshop was to address these worries and hence we invited NASA engineers working on autonomous and adaptive systems and researchers interested in the verification and validation ( V & V ) of software systems. The dual purpose of the meeting was to (1) make NASA engineers aware of the V & V techniques they could be using and (2) make the V& V community aware of the complexity of the systems NASA is developing.

Hybrid Architectures for Intelligent Systems

Hybrid Architectures for Intelligent Systems
Author: Abraham Kandel
Publisher: CRC Press
Total Pages: 448
Release: 2020-09-10
Genre: Computers
ISBN: 1000102947

Hybrid architecture for intelligent systems is a new field of artificial intelligence concerned with the development of the next generation of intelligent systems. This volume is the first book to delineate current research interests in hybrid architectures for intelligent systems. The book is divided into two parts. The first part is devoted to the theory, methodologies, and algorithms of intelligent hybrid systems. The second part examines current applications of intelligent hybrid systems in areas such as data analysis, pattern classification and recognition, intelligent robot control, medical diagnosis, architecture, wastewater treatment, and flexible manufacturing systems. Hybrid Architectures for Intelligent Systems is an important reference for computer scientists and electrical engineers involved with artificial intelligence, neural networks, parallel processing, robotics, and systems architecture.

Leveraging Applications of Formal Methods, Verification and Validation. Adaptation and Learning

Leveraging Applications of Formal Methods, Verification and Validation. Adaptation and Learning
Author: Tiziana Margaria
Publisher: Springer Nature
Total Pages: 483
Release: 2022-10-19
Genre: Computers
ISBN: 3031197593

This four-volume set LNCS 13701-13704 constitutes contributions of the associated events held at the 11th International Symposium on Leveraging Applications of Formal Methods, ISoLA 2022, which took place in Rhodes, Greece, in October/November 2022. The contributions in the four-volume set are organized according to the following topical sections: specify this - bridging gaps between program specification paradigms; x-by-construction meets runtime verification; verification and validation of concurrent and distributed heterogeneous systems; programming - what is next: the role of documentation; automated software re-engineering; DIME day; rigorous engineering of collective adaptive systems; formal methods meet machine learning; digital twin engineering; digital thread in smart manufacturing; formal methods for distributed computing in future railway systems; industrial day.

Neural Networks and Their Applications

Neural Networks and Their Applications
Author: John G. Taylor
Publisher: John Wiley & Sons
Total Pages: 336
Release: 1996
Genre: Computers
ISBN:

Neural networks are one of the fast-growing paradigms for learning systems with a wide variety of potential applications in industry. In particular there are general results which prove the universal applicability of neural networks to many problems. There is also an ever greater understanding of the underlying manner in which tasks such as classification can be solved optimally by this host of techniques. Through the application of ideas of statistics, dynamical systems theory and information theory the methods are likely to become ever more effective for solving problems previously found to be difficult to tackle using standard techniques. This book compares and contrasts the academic theory and the industrial reality, with case studies and latest research findings from international experts. The contributions describe application areas including finance, digital data transmission, hybrid systems, automotive and aerospace industries, pattern analysis in clinical psychiatry, time series prediction, and genetic and neural algorithms. This book demonstrates the vigour and strength of the subject in solving hard problems and as such will be of great interest to all researchers and professionals with an interest in neural networks.

Verification and Validation of Rule-Based Expert Systems

Verification and Validation of Rule-Based Expert Systems
Author: Suzanne Smith
Publisher: CRC Press
Total Pages: 224
Release: 2018-10-08
Genre: Computers
ISBN: 1351830120

This book presents an innovative approach to verifying and validating rule-based expert systems. It features a complete set of techniques and tools that provide a more formal, objective, and automated means of carrying out verification and validation procedures. Many of the concepts behind these procedures have been adapted from conventional software, while others have required that new techniques or tools be created because of the uniqueness of rule-based expert systems. Verification and Validation of Rule-Based Expert Systems is a valuable reference for electrical engineers, software engineers, artificial intelligence experts, and computer scientists involved with object-oriented development, expert systems, and programming languages.

Applications of Neural Networks in High Assurance Systems

Applications of Neural Networks in High Assurance Systems
Author: Johann M.Ph. Schumann
Publisher: Springer Science & Business Media
Total Pages: 255
Release: 2010-02-28
Genre: Mathematics
ISBN: 3642106897

"Applications of Neural Networks in High Assurance Systems" is the first book directly addressing a key part of neural network technology: methods used to pass the tough verification and validation (V&V) standards required in many safety-critical applications. The book presents what kinds of evaluation methods have been developed across many sectors, and how to pass the tests. A new adaptive structure of V&V is developed in this book, different from the simple six sigma methods usually used for large-scale systems and different from the theorem-based approach used for simplified component subsystems.