Books in the Intelligent Systems Reference Library series

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

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 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.

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.

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

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.

Surprisingly information systems are quite different fromconventional (energy, material-intensive) artificial systems, and ratherresemble biological systems (information-intensive systems).

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 book presents recently developed intelligent techniques with applications and theory in the area of quality management. The book consists of classical quality management topics dealing with intelligent techniques for solving the complex quality management problems.

The topic of this monograph falls within the, so-called, biologically motivated computing paradigm, in which biology provides the source of models and inspiration towards the development of computational intelligence and machine learning systems.

This book introduces a paradigm of reverse hypothesis machines (RHM), focusing on knowledge innovation and machine learning. The book is useful as a reference book for machine learning researchers and professionals as well as machine intelligence enthusiasts.

This book presents innovative and high-quality research on the implementation of conceptual frameworks, strategies, techniques, methodologies, informatics platforms and models for developing advanced knowledge-based systems and their application in different fields, including Agriculture, Education, Automotive, Electrical Industry, Business Services, Food Manufacturing, Energy Services, Medicine and others.Knowledge-based technologies employ artificial intelligence methods to heuristically address problems that cannot be solved by means of formal techniques. These technologies draw on standard and novel approaches from various disciplines within Computer Science, including Knowledge Engineering, Natural Language Processing, Decision Support Systems, Artificial Intelligence, Databases, Software Engineering, etc. As a combination of different fields of Artificial Intelligence, the area of Knowledge-Based Systems applies knowledge representation, case-based reasoning, neural networks, Semantic Web and TICs used in different domains. The book offers a valuable resource for PhD students, Master¿s and undergraduate students of Information Technology (IT)-related degrees such as Computer Science, Information Systems and Electronic Engineering.

This book presents a study of the use of optimization algorithms in complex image processing problems.

This book introduces computational proximity (CP) as an algorithmic approach to finding nonempty sets of points that are either close to each other or far apart. In CP, two types of near sets are considered, namely, spatially near sets and descriptivelynear sets.

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.

The book focuses on a set of cutting-edge research techniques, highlighting the potential of soft computing tools in the analysis of economic and financial phenomena and in providing support for the decision-making process.

This book illustrates recent bio-inspired efficient algorithms for solving NP-hard problems. Discusses theoretical bio-inspired concepts and models, in particular for agents, ants and virtual robots, variations of the Traveling Salesman Problem and more.

This book applies the free, downloadable SAGE software program to numerous of examples and solved as well as unsolved problems in linear algebra and differential geometry, offering plenty of SAGE applications at each stage of the exposition.

In a stimulating exploration of the role played by philosophy, logic, and science in the study of engineering, this book aims to rekindle creativity and innovation among budding engineers by advocating the rich benefits of a broader conceptual framework.

This book presents recent advances in Knowledge discovery in databases (KDD) with a focus on the areas of market basket database, time-stamped databases and multiple related databases.

Time series analysis and modelling represent a large study field, implying the approach from the perspective of the time and frequency, with applications in different domains.

This is the first book on experience-based knowledge representation and knowledge management using the unique Decisional DNA (DDNA) technology.

This book presents innovative and high-quality research on the implementation of conceptual frameworks, strategies, techniques, methodologies, informatics platforms and models for developing advanced knowledge-based systems and their application in different fields, including Agriculture, Education, Automotive, Electrical Industry, Business Services, Food Manufacturing, Energy Services, Medicine and others.Knowledge-based technologies employ artificial intelligence methods to heuristically address problems that cannot be solved by means of formal techniques. These technologies draw on standard and novel approaches from various disciplines within Computer Science, including Knowledge Engineering, Natural Language Processing, Decision Support Systems, Artificial Intelligence, Databases, Software Engineering, etc. As a combination of different fields of Artificial Intelligence, the area of Knowledge-Based Systems applies knowledge representation, case-based reasoning, neural networks, Semantic Web and TICs used in different domains. The book offers a valuable resource for PhD students, Master's and undergraduate students of Information Technology (IT)-related degrees such as Computer Science, Information Systems and Electronic Engineering.

This monograph presents new developments in multi-level decision-making theory, technique and method in both modeling and solution issues. It especially presents how a decision support system can support managers in reaching a solution to a multi-level decision problem in practice.