Bücher der Reihe Intelligent Systems Reference Library

The results presented here (including the assessment of a new tool - inhibitory trees) offer valuable tools for researchers in the areas of data mining, knowledge discovery, and machine learning, especially those whose work involves decision tables with many-valued decisions.

Experimental data analysis is at the core of scientific inquiry, and computers have taken this function to a new level. This volume is an interactive guide to complex modern analytical processes from non-linear curve fitting to clustering and machine learning.

This book initially reviews the major feature representation and extraction methods and effective learning and recognition approaches, which have broad applications in the context of intelligent image search and video retrieval.

This book presents neuromorphic cognitive systems from a learning and memory-centered perspective.

Last, Chapter 7 presents simulation methodologies for modeling maritime traffic. The intended readership of the book spans both an academic audience and professionals in the areas of Operational Research, Transportation Science, and Maritime Science interested in applying IT methodologies in their areas of expertise.

This book offers the first comprehensive overview of artificial intelligence (AI) technologies in decision support systems for diagnosis based on medical images, presenting cutting-edge insights from thirteen leading research groups around the world.

This book explores reasoning with rough sets by developing a granularity-based framework. It begins with a brief description of the rough set theory, then examines selected relations between rough set theory and non-classical logics including modal logic.

When discussing classification, support vector machines are known to be a capable and efficient technique to learn and predict with high accuracy within a quick time frame.

This volume presents recent research in cyber security and reports how organizations can gain competitive advantages by applying the different security techniques in real-world scenarios.

The book expresses the conviction that the art of creating tools - Greek techne - changes its character together with the change of civilization epochs and co-determines such changes.

Special emphasis is given to intelligent tutoring systems as a particular class of e-learning systems, which support and improve the learning and teaching of domain-specific knowledge. A new approach to perform effective personalization based on Semantic web technologies achieved in a tutoring system is presented.

This book introduces readers to the current trends in using deep learners and deep learner descriptors for medical applications.

This book combines the advantages of high-dimensional data visualization and machine learning in the context of identifying complex n-D data patterns.

This book illustrates the rapid pace of development in intelligent assistive technology in recent years, and highlights some salient examples of using modern IT&C technologies to provide devices, systems and application software for persons with certain motor or cognitive disabilities.

Data preprocessing includes the data reduction techniques, which aim at reducing the complexity of the data, detecting or removing irrelevant and noisy elements from the data.This book is intended to review the tasks that fill the gap between the data acquisition from the source and the data mining process.

This book presents machine learning and type-2 fuzzy sets for the prediction of time-series with a particular focus on business forecasting applications.

This book provides a comprehensive overview of deep learning (DL) in medical and healthcare applications, including the fundamentals and current advances in medical image analysis, state-of-the-art DL methods for medical image analysis and real-world, deep learning-based clinical computer-aided diagnosis systems.Deep learning (DL) is one of the key techniques of artificial intelligence (AI) and today plays an important role in numerous academic and industrial areas. DL involves using a neural network with many layers (deep structure) between input and output, and its main advantage of is that it can automatically learn data-driven, highly representative and hierarchical features and perform feature extraction and classification on one network. DL can be used to model or simulate an intelligent system or process using annotated training data.Recently, DL has become widely used in medical applications, such as anatomic modelling, tumour detection, disease classification, computer-aided diagnosis and surgical planning. This book is intended for computer science and engineering students and researchers, medical professionals and anyone interested using DL techniques.

This book focuses on various aspects of research on ageing, including in relation to assistive technology; Products, services and environments have been changing in response to the changing population.Presenting international design research to demonstrate the thinking and ideas shaping design, this book is a valuable resource for designers;

This book attempts to improve algorithms by novel theories and complex data analysis in different scopes including object detection, remote sensing, data transmission, data fusion, gesture recognition, and edical image processing and analysis. The book is directed to the Ph.D.

This book attempts to improve algorithms by novel theories and complex data analysis in different scopes including object detection, remote sensing, data transmission, data fusion, gesture recognition, and medical image processing and analysis. The book is directed to the Ph.D.

A special emphasis is devoted to approximation and adaptivity issues as well as to the integration of heterogeneous data sources. The book will prove useful as a reference book for senior undergraduate or graduate courses on advanced data management issues, which have a special focus on query processing and data integration.

Presents a sample of the advances in information hiding techniques and their applications. This title includes: image data hiding scheme based on vector quantization and image graph coloring; the copyright protection system for Android platform; and, reversible data hiding ICA-based image and video watermarking.

Some of the key principles formulated in the middle ages were done by Johannes Kepler (Problem of the wine barrels), Johan Bernoulli (brachystochrone problem), Leonhard Euler (Calculus of Variations), Lagrange (Principle multipliers), that were formulated primarily in the ancient world and are of a geometric nature.

This research volume presents a sample of recent contributions related to the issue of quality-assessment for Web Based information in the context of information access, retrieval, and filtering systems.The advent of the Web and the uncontrolled process of documents' generation have raised the problem of declining quality assessment to information on the Web, by considering both the nature of documents (texts, images, video, sounds, and so on), the genre of documents ( news, geographic information, ontologies, medical records, products records, and so on), the reputation of information sources and sites, and, last but not least the actions performed on documents (content indexing, retrieval and ranking, collaborative filtering, and so on).The volume constitutes a compendium of both heterogeneous approaches and sample applications focusing specific aspects of the quality assessment for Web-based information for researchers, PhD students and practitioners carrying out their research activity in the field of Web information retrieval and filtering, Web information mining, information quality representation and management.

This book is about the formulations, theoretical investigations, and practical applications of new stochastic models for fundamental concepts and operations of the discipline of risk management.

This handbook presents some of the most recent topics in neural information processing, covering both theoretical concepts and practical applications. The contributions include: Deep architectures Recurrent, recursive, and graph neural networks Cellular neural networks Bayesian networks Approximation capabilities of neural networks Semi-supervised learning Statistical relational learning  Kernel methods for structured data  Multiple classifier systems  Self organisation and modal learning  Applications to content-based image retrieval, text mining in large document collections, and bioinformatics  This book is thought particularly for graduate students, researchers and practitioners, willing to deepen their knowledge on more advanced connectionist models and related learning paradigms.

This detailed survey of the ontology modelling application Knowledge Seeker demonstrates how it can improve the efficiency of traditional information systems, increase the accuracy of text classification, and enhance the capabilities of search engines.

The International Council on Systems Engineering (INCOSE) defines Systems Engineering as an interdisciplinary approach and means to enable the realization of successful systems. Researchers are using intelligence-based techniques to support the practices of systems engineering in an innovative way.