Fuzzy Logic And Neural Networks PDF Download
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| Author | : Masao Mukaidono |
| Publisher | : World Scientific |
| Total Pages | : 117 |
| Release | : 2001 |
| Genre | : Computers |
| ISBN | : 9810245343 |
Download Fuzzy Logic for Beginners Book in PDF, ePub and Kindle
There are many uncertainties in the real world. Fuzzy theory treats a kind of uncertainty called fuzziness, where it shows that the boundary of yes or no is ambiguous and appears in the meaning of words or is included in the subjunctives or recognition of human beings. Fuzzy theory is essential and is applicable to many systems -- from consumer products like washing machines or refrigerators to big systems like trains or subways. Recently, fuzzy theory has been a strong tool for combining new theories (called soft computing) such as genetic algorithms or neural networks to get knowledge from real data. This introductory book enables the reader to understand easily what fuzziness is and how one can apply fuzzy theory to real problems -- which explains why it was a best-seller in Japan.
| Author | : József Dombi |
| Publisher | : Springer Nature |
| Total Pages | : 186 |
| Release | : 2021-04-28 |
| Genre | : Technology & Engineering |
| ISBN | : 3030722805 |
Download Explainable Neural Networks Based on Fuzzy Logic and Multi-criteria Decision Tools Book in PDF, ePub and Kindle
The research presented in this book shows how combining deep neural networks with a special class of fuzzy logical rules and multi-criteria decision tools can make deep neural networks more interpretable – and even, in many cases, more efficient. Fuzzy logic together with multi-criteria decision-making tools provides very powerful tools for modeling human thinking. Based on their common theoretical basis, we propose a consistent framework for modeling human thinking by using the tools of all three fields: fuzzy logic, multi-criteria decision-making, and deep learning to help reduce the black-box nature of neural models; a challenge that is of vital importance to the whole research community.
| Author | : Bart Kosko |
| Publisher | : |
| Total Pages | : 488 |
| Release | : 1992 |
| Genre | : Computers |
| ISBN | : |
Download Neural Networks and Fuzzy Systems Book in PDF, ePub and Kindle
Written by one of the foremost experts in the field of neural networks, this is the first book to combine the theories and applications or neural networks and fuzzy systems. The book is divided into three sections: Neural Network Theory, Neural Network Applications, and Fuzzy Theory and Applications. It describes how neural networks can be used in applications such as: signal and image processing, function estimation, robotics and control, analog VLSI and optical hardware design; and concludes with a presentation of the new geometric theory of fuzzy sets, systems, and associative memories.
| Author | : Hayagriva V. Rao |
| Publisher | : |
| Total Pages | : 551 |
| Release | : 1996 |
| Genre | : C++ (Computer program language) |
| ISBN | : 9788170296942 |
Download C++ Neural Networks and Fuzzy Logic Book in PDF, ePub and Kindle
| Author | : S. RAJASEKARAN |
| Publisher | : PHI Learning Pvt. Ltd. |
| Total Pages | : 459 |
| Release | : 2003-01-01 |
| Genre | : Computers |
| ISBN | : 8120321863 |
Download NEURAL NETWORKS, FUZZY LOGIC AND GENETIC ALGORITHM Book in PDF, ePub and Kindle
This book provides comprehensive introduction to a consortium of technologies underlying soft computing, an evolving branch of computational intelligence. The constituent technologies discussed comprise neural networks, fuzzy logic, genetic algorithms, and a number of hybrid systems which include classes such as neuro-fuzzy, fuzzy-genetic, and neuro-genetic systems. The hybridization of the technologies is demonstrated on architectures such as Fuzzy-Back-propagation Networks (NN-FL), Simplified Fuzzy ARTMAP (NN-FL), and Fuzzy Associative Memories. The book also gives an exhaustive discussion of FL-GA hybridization. Every architecture has been discussed in detail through illustrative examples and applications. The algorithms have been presented in pseudo-code with a step-by-step illustration of the same in problems. The applications, demonstrative of the potential of the architectures, have been chosen from diverse disciplines of science and engineering. This book with a wealth of information that is clearly presented and illustrated by many examples and applications is designed for use as a text for courses in soft computing at both the senior undergraduate and first-year post-graduate engineering levels. It should also be of interest to researchers and technologists desirous of applying soft computing technologies to their respective fields of work.
| Author | : Stamatios V. Kartalopoulos |
| Publisher | : Wiley-IEEE Press |
| Total Pages | : 240 |
| Release | : 1996 |
| Genre | : Computers |
| ISBN | : |
Download Understanding Neural Networks and Fuzzy Logic Book in PDF, ePub and Kindle
Understand the fundamentals of the emerging field of fuzzy neural networks, their applications and the most used paradigms with this carefully organized state-of-the-art textbook. Previously tested at a number of noteworthy conference tutorials, the simple numerical examples presented in this book provide excellent tools for progressive learning. UNDERSTANDING NEURAL NETWORKS AND FUZZY LOGIC offers a simple presentation and bottom-up approach that is ideal for working professional engineers, undergraduates, medical/biology majors, and anyone with a nonspecialist background. Sponsored by: IEEE Neural Networks Council
| Author | : Erdal Kayacan |
| Publisher | : Butterworth-Heinemann |
| Total Pages | : 266 |
| Release | : 2015-10-07 |
| Genre | : Mathematics |
| ISBN | : 0128027037 |
Download Fuzzy Neural Networks for Real Time Control Applications Book in PDF, ePub and Kindle
AN INDISPENSABLE RESOURCE FOR ALL THOSE WHO DESIGN AND IMPLEMENT TYPE-1 AND TYPE-2 FUZZY NEURAL NETWORKS IN REAL TIME SYSTEMS Delve into the type-2 fuzzy logic systems and become engrossed in the parameter update algorithms for type-1 and type-2 fuzzy neural networks and their stability analysis with this book! Not only does this book stand apart from others in its focus but also in its application-based presentation style. Prepared in a way that can be easily understood by those who are experienced and inexperienced in this field. Readers can benefit from the computer source codes for both identification and control purposes which are given at the end of the book. A clear and an in-depth examination has been made of all the necessary mathematical foundations, type-1 and type-2 fuzzy neural network structures and their learning algorithms as well as their stability analysis. You will find that each chapter is devoted to a different learning algorithm for the tuning of type-1 and type-2 fuzzy neural networks; some of which are: • Gradient descent • Levenberg-Marquardt • Extended Kalman filter In addition to the aforementioned conventional learning methods above, number of novel sliding mode control theory-based learning algorithms, which are simpler and have closed forms, and their stability analysis have been proposed. Furthermore, hybrid methods consisting of particle swarm optimization and sliding mode control theory-based algorithms have also been introduced. The potential readers of this book are expected to be the undergraduate and graduate students, engineers, mathematicians and computer scientists. Not only can this book be used as a reference source for a scientist who is interested in fuzzy neural networks and their real-time implementations but also as a course book of fuzzy neural networks or artificial intelligence in master or doctorate university studies. We hope that this book will serve its main purpose successfully. Parameter update algorithms for type-1 and type-2 fuzzy neural networks and their stability analysis Contains algorithms that are applicable to real time systems Introduces fast and simple adaptation rules for type-1 and type-2 fuzzy neural networks Number of case studies both in identification and control Provides MATLAB® codes for some algorithms in the book
| Author | : Chi-hau Chen |
| Publisher | : McGraw-Hill Companies |
| Total Pages | : 862 |
| Release | : 1996 |
| Genre | : Computers |
| ISBN | : |
Download Fuzzy Logic and Neural Network Handbook Book in PDF, ePub and Kindle
A practical reference that presents concise and comprehensive reports on the major activities in fuzzy logic and neural networks, with emphasis on the applications and systems of interest to computer engineers. Each of the 31 chapters focuses on the most important activity of a specific topic, and the chapters are organized into three parts: principles and algorithms; applications; and architectures and systems. The applications for fuzzy logic include home appliance design and manufacturing process; those for neural networks include radar, sonar, and speech signal processing, remote sensing, and electrical power systems. Annotation copyright by Book News, Inc., Portland, OR
| Author | : Mo-yuen Chow |
| Publisher | : World Scientific |
| Total Pages | : 155 |
| Release | : 1997-11-26 |
| Genre | : Computers |
| ISBN | : 9814496936 |
Download Methodologies Of Using Neural Network And Fuzzy Logic Technologies For Motor Incipient Fault Detection Book in PDF, ePub and Kindle
Motor monitoring, incipient fault detection, and diagnosis are important and difficult topics in the engineering field. These topics deal with motors ranging from small DC motors used in intensive care units to the huge motors used in nuclear power plants. With proper machine monitoring and fault detection schemes, improved safety and reliability can be achieved for different engineering system operations. The importance of incipient fault detection can be found in the cost saving which can be obtained by detecting potential machine failures before they occur. Non-invasive, inexpensive, and reliable fault detection techniques are often preferred by many engineers. A large number of techniques, such as expert system approaches and vibration analysis, have been developed for motor fault detection purposes. Those techniques have achieved a certain degree of success. However, due to the complexity and importance of the systems, there is a need to further improve existing fault detection techniques.A major key to the success in fault detection is the ability to use appropriate technology to effectively fuse the relevant information to provide accurate and reliable results. The advance in technology will provide opportunities for improving existing fault detection schemes. With the maturing technology of artificial neural network and fuzzy logic, the motor fault detection problem can be solved using an innovative approach based on measurements that are easily accessible, without the need for rigorous mathematical models. This approach can identify and aggregate the relevant information for accurate and reliable motor fault detection. This book will introduce the neccessary concepts of neural network and fuzzy logic, describe the advantages and challenges of using these technologies to solve motor fault detection problems, and discuss several design considerations and methodologies in applying these techniques to motor incipient fault detection.
| Author | : Nikola K. Kasabov |
| Publisher | : Marcel Alencar |
| Total Pages | : 581 |
| Release | : 1996 |
| Genre | : Artificial intelligence |
| ISBN | : 0262112124 |
Download Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering Book in PDF, ePub and Kindle
Combines the study of neural networks and fuzzy systems with symbolic artificial intelligence (AI) methods to build comprehensive AI systems. Describes major AI problems (pattern recognition, speech recognition, prediction, decision-making, game-playing) and provides illustrative examples. Includes applications in engineering, business and finance.
