Evolving Intelligent Systems

<p>From theory to techniques, the first all-in-one resource for EIS</p> <p>There is a clear demand in advanced process industries, defense, and Internet and communication (VoIP) applications for intelligent yet adaptive/evolving systems. Evolving Intelligent Systems is the first self- contained volume that covers this newly established concept in its entirety, from a systematic methodology to case studies to industrial applications. Featuring chapters written by leading world experts, it addresses the progress, trends, and major achievements in this emerging research field, with a strong emphasis on the balance between novel theoretical results and solutions and practical real-life applications.</p> <ul> <li> <p>Explains the following fundamental approaches for developing evolving intelligent systems (EIS):</p> </li> <li style=”list-style: none”> <ul> <li>the Hierarchical Prioritized Structure</li> <li> <p>the Participatory Learning Paradigm</p> </li> <li> <p>the Evolving Takagi-Sugeno fuzzy systems (eTS+)</p> </li> <li> <p>the evolving clustering algorithm that stems from the well-known Gustafson-Kessel offline clustering algorithm</p> </li> </ul> </li> <li> <p>Emphasizes the importance and increased interest in online processing of data streams</p> </li> <li> <p>Outlines the general strategy of using the fuzzy dynamic clustering as a foundation for evolvable information granulation</p> </li> <li> <p>Presents a methodology for developing robust and interpretable evolving fuzzy rule-based systems</p> </li> <li> <p>Introduces an integrated approach to incremental (real-time) feature extraction and classification</p> </li> <li> <p>Proposes a study on the stability of evolving neuro-fuzzy recurrent networks</p> </li> <li> <p>Details methodologies for evolving clustering and classification</p> </li> <li> <p>Reveals different applications of EIS to address real problems in areas of:</p> </li> <li style=”list-style: none”> <ul> <li> <p>evolving inferential sensors in chemical and petrochemical industry</p> </li> <li> <p>learning and recognition in robotics</p> </li> </ul> </li> <li> <p>Features downloadable software resources</p> </li> </ul> <p>Evolving Intelligent Systems is the one-stop reference guide for both theoretical and practical issues for computer scientists, engineers, researchers, applied mathematicians, machine learning and data mining experts, graduate students, and professionals.</p>