Design And Development Of Expert Systems And Neural Networks
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Design and Development of Expert Systems and Neural Networks by L. R. Medsker,Larry Medsker,Jay Liebowitz Pdf
This book gives readers and practitioners the tools they need to develop appropriate applications and systems. It also explores managing and institutionalizing expert system development and usage.
Hybrid Neural Network and Expert Systems by Larry R. Medsker Pdf
Hybrid Neural Network and Expert Systems presents the basics of expert systems and neural networks, and the important characteristics relevant to the integration of these two technologies. Through case studies of actual working systems, the author demonstrates the use of these hybrid systems in practical situations. Guidelines and models are described to help those who want to develop their own hybrid systems. Neural networks and expert systems together represent two major aspects of human intelligence and therefore are appropriate for integration. Neural networks represent the visual, pattern-recognition types of intelligence, while expert systems represent the logical, reasoning processes. Together, these technologies allow applications to be developed that are more powerful than when each technique is used individually. Hybrid Neural Network and Expert Systems provides frameworks for understanding how the combination of neural networks and expert systems can produce useful hybrid systems, and illustrates the issues and opportunities in this dynamic field.
Fuzzy Engineering Expert Systems with Neural Network Applications by Adedeji Bodunde Badiru,John Cheung Pdf
Provides an up-to-date integration of expert systems with fuzzy logic and neural networks. Includes coverage of simulation models not present in other books. Presents cases and examples taken from the authors' experience in research and applying the technology to real-world situations.
Development of Knowledge-Based Systems for Engineering by Carlo Tasso,Edoardo R.de Arantes e Oliveira Pdf
The goal of the volume is twofold: to help engineers to understand the design and development process and the specific techniques utilized for constructing expert systems in engineering and, secondly, to introduce computer specialists to significant applications of knowledge-based techniques in engineering. Among the authors are world famous experts of engineering and knowledge-based systems development.
A Design and Development Method for Artificial Neural Network Projects by Stefan Vogt Pdf
Inhaltsangabe:Abstract: In the 1980s research efforts and successes made artificial neural networks popular. Since the 1990s engineers have been using this foundation for problem solving. But artifiial neural network solutions for "real-world" problems are sometimes hard to find because of the complexity of the domain and because of the vast number of design attributes the engineer has to deal with. This thesis provides a structured overview of attributes in the design process of artificial neural networks and reviews technical process models. Current development methods for artificial neural networks are then reviewed and critiqued. The thesis concludes with a new design and development method for artificial neural networks. Inhaltsverzeichnis:Table of Contents: List of figuresx List of tablesxi Introduction1 1.Design attributes in ANN3 1.1ANN models4 1.1.1Node level7 1.1.2Network level9 1.1.3Training level9 1.2Data and data representation10 1.3Global system design12 1.4Hardware and software implementation13 1.5Characteristics of ANNs15 1.5.1Advantages of ANNs15 1.5.2Limitations and concerns16 2.Technical process models and engineering methods18 2.1Why use an engineering method?18 2.2Evolutionary model of engineering discipline20 2.3Overview of technical process models22 2.3.1Taxonomy of technical process models24 2.3.2Prototyping25 2.3.3Incremental method26 2.3.4Strict contractual approach26 2.3.5Deciding on process models and methods26 2.3.6Examples of process models27 2.3.7Representation of process models27 2.4Quality criteria of process models29 3.Current engineering methods for ANNs30 3.1Why a special method for ANNs?30 3.1.1Are conventional engineering methodologies suitable for ANNs?30 3.2Methods for expert systems31 3.3System identication methods35 3.4Bailey and Thompson37 3.4.1Criticism43 3.5Medsker and Liebowitz44 3.6Jones and Franklin45 3.7Schalko47 3.8Karayiannis and Nicolaos48 3.8.1Criticism49 3.9Nelson and Illingworth50 3.9.1Criticism51 3.10Whittington and Spracklen52 3.10.1Criticism56 3.11Lawrence and Andriola57 3.11.1Criticism58 3.12General criticism of current methodologies58 4.Proposed design and development method60 4.1Development process61 4.1.1Requirement analysis65 4.1.2Specication68 4.1.3Data and domain analysis70 4.1.4Architectural design76 4.1.5Detailed ANN design84 4.1.6ANN implementation92 4.1.7Training93 4.1.8Monitoring training94 4.1.9ANN quality [...]
This six-volume set presents cutting-edge advances and applications of expert systems. Because expert systems combine the expertise of engineers, computer scientists, and computer programmers, each group will benefit from buying this important reference work. An "expert system" is a knowledge-based computer system that emulates the decision-making ability of a human expert. The primary role of the expert system is to perform appropriate functions under the close supervision of the human, whose work is supported by that expert system. In the reverse, this same expert system can monitor and double check the human in the performance of a task. Human-computer interaction in our highly complex world requires the development of a wide array of expert systems. Expert systems techniques and applications are presented for a diverse array of topics including Experimental design and decision support The integration of machine learning with knowledge acquisition for the design of expert systems Process planning in design and manufacturing systems and process control applications Knowledge discovery in large-scale knowledge bases Robotic systems Geograhphic information systems Image analysis, recognition and interpretation Cellular automata methods for pattern recognition Real-time fault tolerant control systems CAD-based vision systems in pattern matching processes Financial systems Agricultural applications Medical diagnosis
Design and Implementation of Intelligent Manufacturing Systems by Mohammed Jamshidi,Hamid R. Parsaei Pdf
The introduction of artificial intelligence, neural networks, and fuzzy logic into industry has given a new perspective to manufacturing processes in the U.S. and abroad. To help readers keep pace, this book addresses topics of intelligent manufacturing from a variety of theoretical, empirical, design, and implementation perspectives.
Artificial Intelligence by Michael Negnevitsky Pdf
Keeping the maths to a minimum, Negnevitsky explains the principles of AI, demonstrates how systems are built, what they are useful for and how to choose the right tool for the job.
Research and Development in Expert Systems VII by British Computer Society. Specialist Group on Expert Systems. Technical Conference Pdf
This volume contains the refereed and invited papers presented at Expert Systems 90, the tenth annual conference of the British Computer Society's Specialist Group on Expert Systems, held in London in September 1990. The theme of the conference,"Business Benefits of Expert Systems," is particularly pertinent, as expert systems mature and begin to be applied in a much wider range of settings. This year three issues in particular were examined: cybernetics, databases, and programming languages. They reflect the ubiquity of expert systems and show how these methods are helping to expand other areas of technology. This is the seventh volume in the conference series, "Research and Development in Expert Systems," and is essential reading for those working in expert systems and artificial intelligence who wish to keep up to date with developments and opportunities in these important fields.
Safety and environmental issues in rock engineering, volume 2 by L.M. Ribeiro E Sousa,N.F. Grossmann Pdf
State-of-the-art in science; engineering aspects of rock mechanics in the areas of safety ; environmental protection. Discusses various aspects concerning modelling in safety analysis, stability of underground structures, and the contribution of incident and accident cases to the progress of rock engineering activities. The influence of the environment is also considered, namely in heat ; mass transport, contaminant migration, and underground storage of waste; products.
Expert Systems for Human, Materials and Automation by Petrică Vizureanu Pdf
The ability to create intelligent machines has intrigued humans since ancient times, and today with the advent of the computer and 50 years of research into AI programming techniques, the dream of smart machines is becoming a reality. The concept of human-computer interfaces has been undergoing changes over the years. In carrying out the most important tasks is the lack of formalized application methods, mathematical models and advanced computer support. The evolution of biological systems to adapt to their environment has fascinated and challenged scientists to increase their level of understanding of the functional characteristics of such systems. This book has 19 chapters and explain that the expert systems are products of the artificial intelligence, branch of computer science that seeks to develop intelligent programs for human, materials and automation.
Intelligent Systems by Crina Grosan,Ajith Abraham Pdf
Computational intelligence is a well-established paradigm, where new theories with a sound biological understanding have been evolving. The current experimental systems have many of the characteristics of biological computers (brains in other words) and are beginning to be built to perform a variety of tasks that are difficult or impossible to do with conventional computers. As evident, the ultimate achievement in this field would be to mimic or exceed human cognitive capabilities including reasoning, recognition, creativity, emotions, understanding, learning and so on. This book comprising of 17 chapters offers a step-by-step introduction (in a chronological order) to the various modern computational intelligence tools used in practical problem solving. Staring with different search techniques including informed and uninformed search, heuristic search, minmax, alpha-beta pruning methods, evolutionary algorithms and swarm intelligent techniques; the authors illustrate the design of knowledge-based systems and advanced expert systems, which incorporate uncertainty and fuzziness. Machine learning algorithms including decision trees and artificial neural networks are presented and finally the fundamentals of hybrid intelligent systems are also depicted. Academics, scientists as well as engineers engaged in research, development and application of computational intelligence techniques, machine learning and data mining would find the comprehensive coverage of this book invaluable.
