Verification And Validation Of Neural Networks For Aerospace Systems
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Methods And Procedures For The Verification And Validation Of Artificial Neural Networks
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Author : Brian J. Taylor
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-03-20
Methods And Procedures For The Verification And Validation Of Artificial Neural Networks written by Brian J. Taylor and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-03-20 with Computers categories.
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.
Guidance For The Verification And Validation Of Neural Networks
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Author : Laura L. Pullum
language : en
Publisher: John Wiley & Sons
Release Date : 2007-03-09
Guidance For The Verification And Validation Of Neural Networks written by Laura L. Pullum and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-03-09 with Computers categories.
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.
Verification And Validation Of Neural Networks For Aerospace Systems
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Author : Dale Mackall
language : en
Publisher:
Release Date : 2002
Verification And Validation Of Neural Networks For Aerospace Systems written by Dale Mackall and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with Adaptive control systems categories.
Adaptive Control Approach For Software Quality Improvement
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Author : W. Eric Wong
language : en
Publisher: World Scientific
Release Date : 2011
Adaptive Control Approach For Software Quality Improvement written by W. Eric Wong and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Computers categories.
This book focuses on the topic of improving software quality using adaptive control approaches. As software systems grow in complexity, some of the central challenges include their ability to self-manage and adapt at run time, responding to changing user needs and environments, faults, and vulnerabilities. Control theory approaches presented in the book provide some of the answers to these challenges. The book weaves together diverse research topics (such as requirements engineering, software development processes, pervasive and autonomic computing, service-oriented architectures, on-line adaptation of software behavior, testing and QoS control) into a coherent whole. Written by world-renowned experts, this book is truly a noteworthy and authoritative reference for students, researchers and practitioners to better understand how the adaptive control approach can be applied to improve the quality of software systems. Book chapters also outline future theoretical and experimental challenges for researchers in this area.
Issues In Verification And Validation Of Neural Network Based Approaches For Fault Diagnosis In Autonomous Systems
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Author : Uma Bharathi Ramachandran
language : en
Publisher:
Release Date : 2005
Issues In Verification And Validation Of Neural Network Based Approaches For Fault Diagnosis In Autonomous Systems written by Uma Bharathi Ramachandran and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with categories.
Autonomous systems are those that evolve over time, and through learning, can make intelligent decisions when faced with unidentified and unknown situations. Artificial Neural Networks (ANN) has been applied to an increasing number of real-world problems with considerable complexity. Due to their learning abilities, ANN-based systems have been increasingly attracting attention in applications where autonomy is critical and where identification of possible fault scenarios is not exhaustive before hand. We have proposed a methodology in which the learning rules that a trained network has adapted can be extracted and refined using rule extraction and rule refinement techniques, respectively, and then these refined rules are subsequently formally specified and verified against requirements specification using formal methods. The effectiveness of the proposed approach has been demonstrated using a case study of an attitude control subsystem of a satellite.
Formal Approaches To Agent Based Systems
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Author : Michael G. Hinchey
language : en
Publisher: Springer
Release Date : 2005-01-25
Formal Approaches To Agent Based Systems written by Michael G. Hinchey and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-01-25 with Computers categories.
The 3rd Workshop on Formal Approaches to Agent-Based Systems (FAABS-III) was held at the Greenbelt Marriott Hotel (near NASA Goddard Space Flight Center) in April 2004 in conjunction with the IEEE Computer Society. The first FAABS workshop was help in April 2000 and the second in October 2002. Interest in agent-based systems continues to grow and this is seen in the wide range of conferences and journals that are addressing the research in this area as well as the prototype and developmental systems that are coming into use. Our third workshop, FAABS-III, was held in April, 2004. This volume contains the revised papers and posters presented at that workshop. The Organizing Committee was fortunate in having significant support in the planning and organization of these events, and were privileged to have wor- renowned keynote speakers Prof. J Moore (FAABS-I), Prof. Sir Roger Penrose (FAABS-II), and Prof. John McCarthy (FAABS-III), who spoke on the topic of se- aware computing systems, auguring perhaps a greater interest in autonomic computing as part of future FAABS events. We are grateful to all who attended the workshop, presented papers or posters, and participated in panel sessions and both formal and informal discussions to make the workshop a great success. Our thanks go to the NASA Goddard Space Flight Center, Codes 588 and 581 (Software Engineering Laboratory) for their financial support and to the IEEE Computer Society (Technical Committee on Complexity in Computing) for their sponsorship and organizational assistance.
Neural Information Processing
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Author : Jun Wang
language : en
Publisher: Springer
Release Date : 2006-10-03
Neural Information Processing written by Jun Wang and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-10-03 with Computers categories.
The three volume set LNCS 4232, LNCS 4233, and LNCS 4234 constitutes the refereed proceedings of the 13th International Conference on Neural Information Processing, ICONIP 2006, held in Hong Kong, China in October 2006. The 386 revised full papers presented were carefully reviewed and selected from 1175 submissions.
Applications Of Neural Networks In High Assurance Systems
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Author : Johann M.Ph. Schumann
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-02-28
Applications Of Neural Networks In High Assurance Systems written by Johann M.Ph. Schumann and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-02-28 with Mathematics categories.
"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.
Applications Of Neural Networks In High Assurance Systems
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Author : Johann M.Ph. Schumann
language : en
Publisher: Springer
Release Date : 2010-03-10
Applications Of Neural Networks In High Assurance Systems written by Johann M.Ph. Schumann and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-03-10 with Technology & Engineering categories.
"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.
Deep Learning For Autonomous Vehicle Control
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Author : Sampo Kuutti
language : en
Publisher: Springer Nature
Release Date : 2022-06-01
Deep Learning For Autonomous Vehicle Control written by Sampo Kuutti and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-01 with Technology & Engineering categories.
The next generation of autonomous vehicles will provide major improvements in traffic flow, fuel efficiency, and vehicle safety. Several challenges currently prevent the deployment of autonomous vehicles, one aspect of which is robust and adaptable vehicle control. Designing a controller for autonomous vehicles capable of providing adequate performance in all driving scenarios is challenging due to the highly complex environment and inability to test the system in the wide variety of scenarios which it may encounter after deployment. However, deep learning methods have shown great promise in not only providing excellent performance for complex and non-linear control problems, but also in generalizing previously learned rules to new scenarios. For these reasons, the use of deep neural networks for vehicle control has gained significant interest. In this book, we introduce relevant deep learning techniques, discuss recent algorithms applied to autonomous vehicle control, identify strengths and limitations of available methods, discuss research challenges in the field, and provide insights into the future trends in this rapidly evolving field.