Nadia Nedjah Livres

Data mining consists of attempting to discover novel and useful knowledge from data, trying to find patterns among datasets that can help in intelligent decision making. However, reports of real-world case studies are not generally detailed in the literature, due to the fact that they are usually based on proprietary datasets, making it impossible to publish the results. This kind of situation makes hard to evaluate, in a precise way, the degree of effectiveness of data mining techniques in real-world applications. On the other hand, researchers of this field of expertise usually exploit public-domain datasets. This volume offers a wide spectrum of research work developed for data mining for real-world application. In the following, we give a brief introduction of the chapters that are included in this book.

Automatic Text Categorization and Clustering are becoming more and more important as the amount of text in electronic format grows and the access to it becomes more necessary and widespread. Well known applications are spam filtering and web search, but a large number of everyday uses exist (intelligent web search, data mining, law enforcement, etc.) Currently, researchers are employing many intelligent techniques for text categorization and clustering, ranging from support vector machines and neural networks to Bayesian inference and algebraic methods, such as Latent Semantic Indexing. This volume offers a wide spectrum of research work developed for intelligent text categorization and clustering. In the following, we give a brief introduction of the chapters that are included in this book.

Designing complex programs such as operating systems, compilers, filing systems, data base systems, etc. is an old ever lasting research area. Genetic programming is a relatively new promising and growing research area. Among other uses, it provides efficient tools to deal with hard problems by evolving creative and competitive solutions. Systems Programming is generally strewn with such hard problems. This book is devoted to reporting innovative and significant progress about the contribution of genetic programming in systems programming. The contributions of this book clearly demonstrate that genetic programming is very effective in solving hard and yet-open problems in systems programming. Followed by an introductory chapter, in the remaining contributed chapters, the reader can easily learn about systems where genetic programming can be applied successfully. These include but are not limited to, information security systems, compilers, data mining systems, stock market prediction systems, robots and automatic programming.

Research on applying principles of quantum computing to improve the engineering of intelligent systems has been launched since late 1990s. This emergent research field concentrates on studying on quantum computing that is characterized by certain principles of quantum mechanics such as standing waves, interference, quantum bits, coherence, superposition of states, and concept of interference, combined with computational intelligence or soft computing approaches, such as artificial neural networks, fuzzy systems, evolutionary computing, swarm intelligence and hybrid soft computing methods. This volume offers a wide spectrum of research work developed using soft computing combined with quantum computing systems.

Focusing on advancements in fuzzy system engineering, this book highlights recent breakthroughs in fuzzy logic and soft computing. It explores innovative developments in fuzzy theory and showcases practical applications that leverage this theory to enhance intelligent system engineering. The monograph serves as a comprehensive resource for understanding the evolving landscape of fuzzy logic and its implications for intelligent systems.

Focusing on quantum computation, this book explores the concepts of quantum unitary, binary, and ternary operators, detailing their implications for computation. It examines the architecture of quantum processors and validates their functionality through simulated execution of various quantum instructions. The comprehensive review highlights the intricate relationship between quantum operators and processing capabilities, making it a valuable resource for understanding advanced quantum computing principles.

This book explores the integration of various soft computing techniques, such as Genetic Algorithms, Artificial Neural Networks, and Particle Swarm Optimization, into hardware designs. It emphasizes the use of reconfigurable hardware like FPGAs for efficient implementation, addressing challenges in embedded system design and circuit synthesis.

The design of most modern engineering systems entails the consideration of a good trade-off between the several targets requirements to be satisfied along the system life such as high reliability, low redundancy and low operational costs. These aspects are often in conflict with one another, hence a compromise solution has to be sought. Innovative computing techniques, such as genetic algorithms, swarm intelligence, differential evolution, multi-objective evolutionary optimization, just to name few, are of great help in founding effective and reliable solution for many engineering problems. Each chapter of this book attempts to using an innovative computing technique to elegantly solve a different engineering problem.

Mobile robotic is a recent ? eld that has roots in many engineering and science disciplines such as mechanical, electrical, mechatronics, cognitive and social sciences just to name few. A mobile robot needs e? cient mechanisms of lo- motion, kinematics, sensors data, localization, planning and navigation that enable it to travel throughout its environment. Scientists have been fascinated by conception of mobile robots for many years. Machines have been designed withwheelsandtracksorotherlocomotion devicesand/orlimbs topropelthe unit. When the environment is well ordered these machines can function well. Mobile robots have demonstrated strongly their ability to carry out useful work. Intelligent robots have become the focus of intensive research in the last decade. The ? eld of intelligent mobile robotics involves simulations and re- world implementations of robots which adapt themselves to their partially unknown, unpredictable and sometimes dynamic environments. The design and control of autonomous intelligent mobile robotic systems operatinginunstructuredchangingenvironmentsincludesmanyobjectived- ? culties. There are several studies about the ways in which, robots exhibiting some degree of autonomy, adapt themselves to ? t in their environments. The application and use of bio-inspired techniques such as reinforcement lea- ing, arti? cial neural networks, evolutionary computation, swarm intelligence and fuzzy systems in the design and improvement of robot designs is an em- gentresearchtopic. Researchershaveobtainedrobotsthatdisplayanamazing slew of behaviours and perform a multitude of tasks.

Methods for the artificial evolution of active components, such as programs and hardware, are rapidly developing branches of adaptive computation and adaptive engineering. Evolvable Machines reports innovative and significant progress in automatic and evolutionary methodology applied to machine design. This book presents theoretical as well as practical chapters concentrating on Evolvable Robots, Evolvable Hardware Synthesis, as well as Evolvable Design.