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Expert Systems and Related Topics by Marlene A. Palmer Pdf
This comprehensive reference to all areas of expert systems and applications, plus advanced related topics, lets you spend your time reading expert systems literature rather than searching for it. It gives you a source of historical perspectives and outlooks on the future of the field. Whether you are a manager, a developer or an end user or researcher, Expert Systems and Related Topics: Selected Bibliography & Guide to Information Sources puts all the sources of expert systems literature at your fingertips.
Topics in Expert System Design by C. Tasso,G. Guida Pdf
Expert Systems are so far the most promising achievement of artificial intelligence research. Decision making, planning, design, control, supervision and diagnosis are areas where they are showing great potential. However, the establishment of expert system technology and its actual industrial impact are still limited by the lack of a sound, general and reliable design and construction methodology. This book has a dual purpose: to offer concrete guidelines and tools to the designers of expert systems, and to promote basic and applied research on methodologies and tools. It is a coordinated collection of papers from researchers in the USA and Europe, examining important and emerging topics, methodological advances and practical experience obtained in specific applications. Each paper includes a survey introduction, and a comprehensive bibliography is provided.
Artificial Intelligence and Expert Systems for Engineers by C.S. Krishnamoorthy,S. Rajeev Pdf
This book provides a comprehensive presentation of artificial intelligence (AI) methodologies and tools valuable for solving a wide spectrum of engineering problems. What's more, it offers these AI tools on an accompanying disk with easy-to-use software. Artificial Intelligence and Expert Systems for Engineers details the AI-based methodologies known as: Knowledge-Based Expert Systems (KBES); Design Synthesis; Design Critiquing; and Case-Based Reasoning. KBES are the most popular AI-based tools and have been successfully applied to planning, diagnosis, classification, monitoring, and design problems. Case studies are provided with problems in engineering design for better understanding of the problem-solving models using the four methodologies in an integrated software environment. Throughout the book, examples are given so that students and engineers can acquire skills in the use of AI-based methodologies for application to practical problems ranging from diagnosis to planning, design, and construction and manufacturing in various disciplines of engineering. Artificial Intelligence and Expert Systems for Engineers is a must-have reference for students, teachers, research scholars, and professionals working in the area of civil engineering design in particular and engineering design in general.
Managing Expert Systems by Efraim Turban,Jay Liebowitz Pdf
Managing Expert Systems explores the trends in expert systems development and implementation. As top authorities in the field of ES, Turban and Liebowitz examine the factors that contribute to the development of a successful expert system.
An expert system, also known as a knowledge based system, is a computer program that contains some of the subject-specific knowledge of one or more human experts. This class of program was first developed by researchers in artificial intelligence during the 1960s and 1970s and applied commercially throughout the 1980s. The most common form of expert systems is a program made up of a set of rules that analyse information usually supplied by the user of the system) about a specific class of problems, as well as providing mathematical analysis of the problem(s), and, depending upon their design, recommend a course of user action in order to implement corrections. It is a system that utilises what appear to be reasoning capabilities to reach conclusions. This book presents important research on in this dynamic field.
This paper is an overview of Expert Systems, currently the most popular topic in Artificial Intelligence. Expert Systems are computer programs that use knowledge and reasoning techniques to solve problems difficult enough to normally require the services of a human expert. Topics covered include: what an Expert System is, the structure of Expert Systems, existing systems, constructing an expert system and future trends and applications. (Author).
A concise practical introduction to the history, characteristics, structure, operation, and use of expert systems. Provides programmers with sufficient insight and guidance to enable them to construct an expert system shell using a favorite programming language. Shows how to develp and maintain expert systems, and how to tackle technical problems unique to the field. There's also advice on how to access new applications.
The Handbook of Applied Expert Systems by Jay Liebowitz Pdf
The Handbook of Applied Expert Systems is a landmark work dedicated solely to this rapidly advancing area of study. Edited by Jay Liebowitz, a professor, author, and consultant known around the world for his work in the field, this authoritative source covers the latest expert system technologies, applications, methodologies, and practices. The book features contributions from more than 40 of the world's foremost expert systems authorities in industry, government, and academia. The Handbook is organized into two major sections. The first section explains expert systems technologies while the second section focuses on applied examples in a wide variety of industries. Key topics covered include fuzzy systems, genetic algorithm development, machine learning, knowledge representation, and much more.
Probabilistic Expert Systems emphasizes the basic computational principles that make probabilistic reasoning feasible in expert systems. The key to computation in these systems is the modularity of the probabilistic model. Shafer describes and compares the principal architectures for exploiting this modularity in the computation of prior and posterior probabilities. He also indicates how these similar yet different architectures apply to a wide variety of other problems of recursive computation in applied mathematics and operations research. The field of probabilistic expert systems has continued to flourish since the author delivered his lectures on the topic in June 1992, but the understanding of join-tree architectures has remained missing from the literature. This monograph fills this void by providing an analysis of join-tree methods for the computation of prior and posterior probabilities in belief nets. These methods, pioneered in the mid to late 1980s, continue to be central to the theory and practice of probabilistic expert systems. In addition to purely probabilistic expert systems, join-tree methods are also used in expert systems based on Dempster-Shafer belief functions or on possibility measures. Variations are also used for computation in relational databases, in linear optimization, and in constraint satisfaction. This book describes probabilistic expert systems in a more rigorous and focused way than existing literature, and provides an annotated bibliography that includes pointers to conferences and software. Also included are exercises that will help the reader begin to explore the problem of generalizing from probability to broader domains of recursive computation.
Time Series Clustering and Classification by Elizabeth Ann Maharaj,Pierpaolo D'Urso,Jorge Caiado Pdf
The beginning of the age of artificial intelligence and machine learning has created new challenges and opportunities for data analysts, statisticians, mathematicians, econometricians, computer scientists and many others. At the root of these techniques are algorithms and methods for clustering and classifying different types of large datasets, including time series data. Time Series Clustering and Classification includes relevant developments on observation-based, feature-based and model-based traditional and fuzzy clustering methods, feature-based and model-based classification methods, and machine learning methods. It presents a broad and self-contained overview of techniques for both researchers and students. Features Provides an overview of the methods and applications of pattern recognition of time series Covers a wide range of techniques, including unsupervised and supervised approaches Includes a range of real examples from medicine, finance, environmental science, and more R and MATLAB code, and relevant data sets are available on a supplementary website
Database and Expert Systems Applications by Heinrich C. Mayr,Jiri Lazansky,Gerald Quirchmayr,Pavel Vogel Pdf
th DEXA 2001, the 12 International Conference on Database and Expert Systems Applications was held on September 3–5, 2001, at the Technical University of Munich, Germany. The rapidly growing spectrum of database applications has led to the establishment of more specialized discussion platforms (DaWaK conference, EC Web conference, and DEXA workshop), which were all held in parallel with the DEXA conference in Munich. In your hands are the results of much effort, beginning with the preparation of the submitted papers. The papers then passed through the reviewing process, and the accepted papers were revised to final versions by their authors and arranged with the conference program. All this culminated in the conference itself. A total of 175 papers were submitted to this conference, and I would like to thank all the authors. They are the real base of the conference. The program committee and the supporting reviewers produced altogether 497 referee reports, on average of 2.84 reports per paper, and selected 93 papers for presentation. Comparing the weight or more precisely the number of papers devoted to particular topics at several recent DEXA conferences, an increase can be recognized in the areas of XMS databases, active databases, and multi and hypermedia efforts. The space devoted to the more classical topics such as information retrieval, distribution and Web aspects, and transaction, indexing and query aspects has remained more or less unchanged. Some decrease is visible for object orientation.
Expert Systems in Finance by Noura Metawa,Mohamed Elhoseny,Aboul Ella Hassanien,M. Kabir Hassan Pdf
Throughout the industry, financial institutions seek to eliminate cumbersome authentication methods, such as PINs, passwords, and security questions, as these antiquated tactics prove increasingly weak. Thus, many organizations now aim to implement emerging technologies in an effort to validate identities with greater certainty. The near instantaneous nature of online banking, purchases, transactions, and payments puts tremendous pressure on banks to secure their operations and procedures. In order to reduce the risk of human error in financial domains, expert systems are seen to offer a great advantage in big data environments. Besides their efficiency in quantitative analysis such as profitability, banking management, and strategic financial planning, expert systems have successfully treated qualitative issues including financial analysis, investment advisories, and knowledge-based decision support systems. Due to the increase in financial applications’ size, complexity, and number of components, it is no longer practical to anticipate and model all possible interactions and data processing in these applications using the traditional data processing model. The emergence of new research areas is clear evidence of the rise of new demands and requirements of modern real-life applications to be more intelligent. This book provides an exhaustive review of the roles of expert systems within the financial sector, with particular reference to big data environments. In addition, it offers a collection of high-quality research that addresses broad challenges in both theoretical and application aspects of intelligent and expert systems in finance. The book serves to aid the continued efforts of the application of intelligent systems that respond to the problem of big data processing in a smart banking and financial environment.
Frontiers of Expert Systems by Chilukuri Krishna Mohan Pdf
The development of modern knowledge-based systems, for applications ranging from medicine to finance, necessitates going well beyond traditional rule-based programming. Frontiers of Expert Systems: Reasoning with Limited Knowledge attempts to satisfy such a need, introducing exciting and recent advances at the frontiers of the field of expert systems. Beginning with the central topics of logic, uncertainty and rule-based reasoning, each chapter in the book presents a different perspective on how we may solve problems that arise due to limitations in the knowledge of an expert system's reasoner. Successive chapters address (i) the fundamentals of knowledge-based systems, (ii) formal inference, and reasoning about models of a changing and partially known world, (iii) uncertainty and probabilistic methods, (iv) the expression of knowledge in rule-based systems, (v) evolving representations of knowledge as a system interacts with the environment, (vi) applying connectionist learning algorithms to improve on knowledge acquired from experts, (vii) reasoning with cases organized in indexed hierarchies, (viii) the process of acquiring and inductively learning knowledge, (ix) extraction of knowledge nuggets from very large data sets, and (x) interactions between multiple specialized reasoners with specialized knowledge bases. Each chapter takes the reader on a journey from elementary concepts to topics of active research, providing a concise description of several topics within and related to the field of expert systems, with pointers to practical applications and other relevant literature. Frontiers of Expert Systems: Reasoning with Limited Knowledge is suitable as a secondary text for a graduate-level course, and as a reference for researchers and practitioners in industry.
Database and Expert Systems Applications by Kim V. Andersen,John Debenham,Roland Wagner Pdf
DEXA 2005, the 16th International Conference on Database and Expert Systems Applications, was held at the Copenhagen Business School, Copenhagen, Denmark, from August 22 to 26, 2005. The success of the DEXA series has partly been due to the way in which it has kept abreast of recent developments by spawning specialized workshops and conferences each with its own proceedings. In 2005 the DEXA programme was co-located with the 7th International Conference on Data Warehousing and Knowledge Discovery [DaWaK 2005], the 6th International Conference on Electronic Commerce and Web Technologies [EC-Web 2005], the 4th International Conference on Electronic Government [EGOV 2005], the 2nd International Conference on Trust, Privacy, and Security in Digital Business [TrustBus 2005], the 2nd International Conference on Industrial Applications of Holonic and Multi-agent Systems [HoloMAS 2005], as well as 19 specialized workshops. These proceedings are the result of a considerable amount of hard work. Beginning with the preparation of submitted papers, the papers went through the reviewing process. This process was supported by online discussion between the reviewers to determine the final conference program. The authors of accepted papers revised their manuscripts to produce this fine collection. DEXA 2005 received 390 submissions, and from those the Program Committee selected the 92 papers in these proceedings. This year the reviewing process generated more than 1000 referee reports. The hard work of the authors, the referees and the Program Committee is gratefully acknowledged.
Database and Expert Systems Applications by Gabriele Kotsis,A Min Tjoa,Ismail Khalil,Lukas Fischer,Bernhard Moser,Atif Mashkoor,Johannes Sametinger,Anna Fensel,Jorge Martinez-Gil Pdf
This volume constitutes the refereed proceedings of the three workshops held at the 31st International Conference on Database and Expert Systems Applications, DEXA 2020, held in September 2020: The 11th International Workshop on Biological Knowledge Discovery from Data, BIOKDD 2020, the 4th International Workshop on Cyber-Security and Functional Safety in Cyber-Physical Systems, IWCFS 2020, the 2nd International Workshop on Machine Learning and Knowledge Graphs, MLKgraphs2019. Due to the COVID-19 pandemic the conference and workshops were held virtually. The 10 papers were thoroughly reviewed and selected from 15 submissions, and discuss a range of topics including: knowledge discovery, biological data, cyber security, cyber-physical system, machine learning, knowledge graphs, information retriever, data base, and artificial intelligence.
