Jeng-Shyang Pan

Michal Wozniak

André C.P.L.F. de Carvalho

Marios M. Polycarpou

Héctor Quintian

This volume constitutes the proceedings of the 8th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2013, held in Salamanca, Spain, in September 2013. The 68 papers published in this volume were carefully reviewed and selected from 218 submissions. They are organized in topical sessions on Agents and Multi Agents Systems; HAIS Applications; Classification and Cluster Analysis; Data Mining and Knowledge Discovery; Video and Image Analysis; Bio-inspired Models and Evolutionary Computation; Learning Algorithms; Systems, MAN, and Cybernetics; Hybrid Intelligent Systems for Data Mining and Applications; Metaheuristics for Combinatorial Optimization and Modelling Complex Systems.

8th International Conference, HAIS 2013, Salamanca, Spain, September 11-13, 2013. Proceedings

Hybrid Artificial Intelligent Systems

Cesare Alippi

Georgios Ellinas

Christos Panayiotou

This two volume set LNCS 5768 and LNCS 5769 constitutes the refereed proceedings of the 19th International Conference on Artificial Neural Networks, ICANN 2009, held in Limassol, Cyprus, in September 2009. The 200 revised full papers presented were carefully reviewed and selected from more than 300 submissions. The first volume is divided in topical sections on learning algorithms; computational neuroscience; hardware implementations and embedded systems; self organization; intelligent control and adaptive systems; neural and hybrid architectures; support vector machine; and recurrent neural network.

19th International Conference, Limassol, Cyprus, September 14-17, 2009, Proceedings

Artificial Neural Networks – ICANN 2009

Vasso Reppa

Christos G. Panayiotou

Recent advances in information and communication technologies, embedded systems and sensor networks have generated significant research activity in the development of so-called cyber-physical systems. An example of a large network of cyber-physical systems is a smart city with intelligent infrastructures for supporting the environment, energy and water distribution, transportation, telecommunication, health care, home automation, and so on. From a systems point of view, safety, reliability and fault tolerance become key challenges in designing cyber-physical systems. One of the major issues is detecting and correcting faults in the sensors that form a critical part of these networks and systems. For example, if two sensors should provide similar information, how do you know which one is at fault should their readings suddenly greatly differ? Sensor Fault Diagnosis addresses all the issues in sensor fault detection and isolation. It provides a clear tutorial on the challenges and models that can be used to address them. It describes, in detail, the requirements for modeling the systems, designing the architecture, detecting faults, isolating those faults, and presents learning techniques for enhancing performance. This monograph will appeal to all researchers and students working on large sensor networks and systems.

Sensor Fault Diagnosis

Elias Kyriakides

This book constitutes revised selected papers from the 9th International Conference on Critical Information Infrastructures Security, CRITIS 2014, held in Limassol, Cyprus, in October 2014. The 20 full and 19 short papers presented in this volume were carefully reviewed and selected from 74 submissions. They are organized in topical sections named: cyber-physical systems and sensor networks; security of water systems; power and energy system security; security and recovery policies, cyber security; and security tools and protocols.

9th International Conference, CRITIS 2014, Limassol, Cyprus, October 13-15, 2014, Revised Selected Papers

Critical Information Infrastructures Security

This volume is part of the two-volume proceedings of the 19th International Conf- ence on Artificial Neural Networks (ICANN 2009), which was held in Cyprus during September 14–17, 2009. The ICANN conference is an annual meeting sp- sored by the European Neural Network Society (ENNS), in cooperation with the - ternational Neural Network Society (INNS) and the Japanese Neural Network Society (JNNS). ICANN 2009 was technically sponsored by the IEEE Computational Intel- gence Society. This series of conferences has been held annually since 1991 in various European countries and covers the field of neurocomputing, learning systems and related areas. Artificial neural networks provide an information-processing structure inspired by biological nervous systems. They consist of a large number of highly interconnected processing elements, with the capability of learning by example. The field of artificial neural networks has evolved significantly in the last two decades, with active partici- tion from diverse fields, such as engineering, computer science, mathematics, artificial intelligence, system theory, biology, operations research, and neuroscience. Artificial neural networks have been widely applied for pattern recognition, control, optimization, image processing, classification, signal processing, etc.

19th International Conference, Limassol, Cyprus, September 14-17, 2009, Proceedings, Part I

Jay A. Farrell

A highly accessible and unified approach to the design and analysisof intelligent control systems Adaptive Approximation Based Control is a tool every controldesigner should have in his or her control toolbox. Mixing approximation theory, parameter estimation, and feedbackcontrol, this book presents a unified approach designed to enablereaders to apply adaptive approximation based control to existingsystems, and, more importantly, to gain enough intuition andunderstanding to manipulate and combine it with other control toolsfor applications that have not been encountered before. The authors provide readers with a thought-provoking framework forrigorously considering such questions as: * What properties should the function approximator have? * Are certain families of approximators superior to others? * Can the stability and the convergence of the approximatorparameters be guaranteed? * Can control systems be designed to be robust in the face ofnoise, disturbances, and unmodeled effects? * Can this approach handle significant changes in the dynamics dueto such disruptions as system failure? * What types of nonlinear dynamic systems are amenable to thisapproach? * What are the limitations of adaptive approximation basedcontrol? Combining theoretical formulation and design techniques withextensive use of simulation examples, this book is a stimulatingtext for researchers and graduate students and a valuable resourcefor practicing engineers.

Unifying Neural, Fuzzy and Traditional Adaptive Approximation Approaches

Adaptive Approximation Based Control

Jun Wang

Gary G. Yen

The two-volume set LNCS 7367 and 7368 constitutes the refereed proceedings of the 9th International Symposium on Neural Networks, ISNN 2012, held in Shenyang, China, in July 2012. The 147 revised full papers presented were carefully reviewed and selected from numerous submissions. The contributions are structured in topical sections on mathematical modeling; neurodynamics; cognitive neuroscience; learning algorithms; optimization; pattern recognition; vision; image processing; information processing; neurocontrol; and novel applications.

Marios M. Polycarpou

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