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We describe in this book, new methods for analysis and design of hybrid intelligent systems using soft computing techniques. Soft Computing SC consists of several computing paradigms, including fuzzy logic, neural networks, and genetic algorithms, which can be used to produce powerful hybrid intelligent systems for solving problems in pattern recognition, time series prediction, intelligent control, robotics and automation.

Hybrid int- ligent systems that combine several SC techniques are needed due to the complexity and high dimensionality of real-world problems. Hybrid int- ligent systems can have different architectures, which have an impact on the efficiency and accuracy of these systems, for this reason it is very - portant to optimize architecture design. The architectures can combine, in different ways, neural networks, fuzzy logic and genetic algorithms, to achieve the ultimate goal of pattern recognition, time series prediction, - telligent control, or other application areas.

This book is intended to be a major reference for scientists and en- neers interested in applying new computational and mathematical tools to design hybrid intelligent systems.

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This book can also be used as a textbook or major reference for graduate courses like the following: soft computing, intelligent pattern recognition, computer vision, applied artificial intel- gence, and similar ones. We consider that this book can also be used to get novel ideas for new lines of research, or to continue the lines of research proposed by the authors of the book. With the proliferation of computers a variety of modeling paradigms emerged under computational intelligence and soft computing. An advancing technology is currently fragmented due, as well, to the need to cope with different types of data in different application domains.

TSO Reliability Management: a probabilistic approach for better balance between reliability & costs

This research monograph proposes a unified, cross-fertilizing approach for knowledge-representation and modeling based on lattice theory. The emphasis is on clustering, classification, and regression applications. It is shown how rigorous analysis and design can be pursued in soft computing using conventional hard computing methods. Moreover, non-Turing computation can be pursued.

The material here is multi-disciplinary based on our on-going research published in major scientific journals and conferences.

Imprecise Probability Group: Publications

Experimental results by various algorithms are demonstrated extensively. Relevant work by other authors is also presented both extensively and comparatively. Advances in Web Intelligence and Data Mining. Today, in the middle of the?

Annotated list of publications

Consequently, more e? The new Web-related research directions include intelligent methods usually associated with the? The book presents state-of-the-art developments in the? However, the development of fuzzy set theory at the theoretical level, and its successful appli- tions to science and technology have often run in isolation.

Only a little part of the theoretical apparatus was effectively used in past applications. The most prominent ones, namely fuzzy rule-based modeling and control engineering, were directly - spired from a seminal paper by Lot? Zadeh in , suggesting how to use expert knowledge for synthetizing control laws, and from the?

Later in the eighties, when spectacular applications were bl- soming in Japan, fuzzy rule-based systems were systematized and simpli? Thus fuzzy systems signi? Even if this area was quite successful, it is patent that the role, in the success of fuzzy logic, of new fuzzy set-related concepts developed quite at the same time in themathematicalnicheofthefuzzyset communitywaslimited. Similar ebooks. But How Do It Know? Clark Scott.

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  7. This book thoroughly explains how computers work. It starts by fully examining a NAND gate, then goes on to build every piece and part of a small, fully operational computer. The necessity and use of codes is presented in parallel with the apprioriate pieces of hardware. The book can be easily understood by anyone whether they have a technical background or not. It could be used as a textbook. Marc Dorio. Add to Wishlist. USD Sign in to Purchase Instantly.

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    Temporarily Out of Stock Online Please check back later for updated availability. Overview Mechatronic design processes have become shorter and more parallelized, induced by growing time-to-market pressure. Product Details Table of Contents. Table of Contents Introduction. Average Review.

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    Write a Review. This work introduces new uncertainty-preserving dependability methods for early design stages. These include the propagation of uncertainty through dependability models, the activation of data from similar components for analyses and the integration of uncertain dependability predictions into an optimization framework. It is shown that Dempster-Shafer theory can be an alternative to probability theory in early design stage dependability predictions.

    Expert estimates can be represented, input uncertainty is propagated through the system and prediction uncertainty can be measured and interpreted. The resulting coherent methodology can be applied to represent the uncertainty in dependability models. JavaScript is currently disabled, this site works much better if you enable JavaScript in your browser. Computer Science Theoretical Computer Science. Studies in Computational Intelligence Free Preview.