Die Autoren behandeln umfassend zentrale Themen der Informatik von Künstlichen Neuronalen Netzen, über Evolutionäre Algorithmen bis hin zu Fuzzy-Systemen und Bayes-Netzen. Denn: Der Anwendungsbereich ´´Computational Intelligence´´ erlangt durch viele erfolgreiche industrielle Produkte immer mehr an Bedeutung. Dieses Buch behandelt die zentralen Techniken dieses Gebiets und bettet sie in ein didaktisches Konzept ein, welches sich gezielt an Studierende und Lehrende der Informatik wendet. Für die vorliegende 2. Auflage des Buches wurden alle Themenbereiche überarbeitet, aktualisiert und zum Teil erweitert. Zusatzmaterialen wie Aufgaben, Lösungen und Foliensätze für Vorlesungen sowie Beispiele aus der industriellen Anwendung betonen den praktischen Charakter des Buches.
This introduction to computational geometry focuses on algorithms. Motivation is provided from the application areas as all techniques are related to particular applications in robotics, graphics, CAD/CAM, and geographic information systems. Modern insights in computational geometry are used to provide solutions that are both efficient and easy to understand and implement.
This book constitutes the proceedings of the 10th International Conference on Computational Logistics, ICCL 2019, held in Barranquilla, Colombia, in September/October 2019. The 27 papers included in this book were carefully reviewed and selected from 49 submissions. They were organized in topical sections named: freight transportation and urban logistics; maritime and port logistics; vehicle routing problems; network design and distribution problems; and selected topics in decision support systems and ICT tools.
This introduction to polynomial rings, Gröbner bases and applications bridges the gap in the literature between theory and actual computation. It details numerous applications, covering fields as disparate as algebraic geometry and financial markets. To aid in a full understanding of these applications, more than 40 tutorials illustrate how the theory can be used. The book also includes many exercises, both theoretical and practical. This is a book about Gröbner bases and their applications. It contains 3 chapters, 20 sections, 44 tutorials, 165 exercises, and numerous further amusements. It is going to help you bridge the gap between theoretical computer algebra and actual computation. We hope you will have as much fun reading it as the authors had writing it! From the reviews: ´´This is one of the most refreshing mathematical books I have ever held in my hands. This is academic teaching at its best; if I had not seen it, I would not have believed that it could be done so well.´´ (Hans Stetter, IMN - Internationale Mathematische Nachrichten 2003) ´´Every paragraph of the book shows how much the authors have enjoyed translating into printed matter the outcome of a long, large, deep and personal relation with computationally oriented commutative algebra. And the result is a non-standard, elementary and self-contained introduction to the theory of Gröbner bases and its applications.´´ (Laureano González-Vega and Tomás Recio, ACM SIGSAM Bulletin 2004) ´´The style of this book merits a comment. Each section begins with a quotation and an overview in which ´´Italian imagination overtakes German rigor´´. These introductions and the following main bodies of each section are well written, engaging and often amusing. The book is a pleasure to read.´´ (John Little, Mathematical Reviews 2001)
Robert Kowalski demonstrates how ordinary people in their everyday life can profit from the advances of computational logic that have been developed for artificial intelligence. This book is an eye-opening read for any student who employs practical thinking, problem solving and communication skills.
An authoritative guide to computer simulation grounded in a multi-disciplinary approach for solving complex problems Simulation and Computational Red Teaming for Problem Solving offers a review of computer simulation that is grounded in a multi-disciplinary approach. The authors present the theoretical foundations of simulation and modeling paradigms from the perspective of an analyst. The book provides the fundamental background information needed for designing and developing consistent and useful simulations. In addition to this basic information, the authors explore several advanced topics. The book´s advanced topics demonstrate how modern artificial intelligence and computational intelligence concepts and techniques can be combined with various simulation paradigms for solving complex and critical problems. Authors examine the concept of Computational Red Teaming to reveal how the combined fundamentals and advanced techniques are used successfully for solving and testing complex real-world problems. This important book: Demonstrates how computer simulation and Computational Red Teaming support each other for solving complex problems Describes the main approaches to modeling real-world phenomena and embedding these models into computer simulations Explores how a number of advanced artificial intelligence and computational intelligence concepts are used in conjunction with the fundamental aspects of simulation Written for researchers and students in the computational modelling and data analysis fields, Simulation and Computational Red Teaming for Problem Solving covers the foundation and the standard elements of the process of building a simulation and explores the simulation topic with a modern research approach.
This book reflects more than three decades of research on Cellular Automata (CA), and nearly a decade of work on the application of CA to model biological strings, which forms the foundation of ´A New Kind of Computational Biology´ pioneered by the start-up, CARLBio. After a brief introduction on Cellular Automata (CA) theory and functional biology, it reports on the modeling of basic biological strings with CA, starting with the basic nucleotides leading to codon and anti-codon CA models. It derives a more involved CA model of DNA, RNA, the entire translation process for amino acid formation and the evolution of protein to its unique structure and function. In subsequent chapters the interaction of Proteins with other bio-molecules is also modeled. The only prior knowledge assumed necessary is an undergraduate knowledge of computer programming and biology. The book adopts a hands-on, ´´do-it-yourself´´ approach to enable readers to apply the method provided to derive the CA rules and comprehend how these are related to the physical ´rules´ observed in biology. In a single framework, the authors have presented two branches of science - Computation and Biology. Instead of rigorous molecular dynamics modeling, which the authors describe as a Bottoms-Up model, or relying on the Top-Down new age Artificial Intelligence (AI) and Machine Language (ML) that depends on extensive availability of quality data, this book takes the best from both the Top-Down and Bottoms-up approaches and establishes how the behavior of complex molecules is represented in CA. The CA rules are derived from the basic knowledge of molecular interaction and construction observed in biological world but mapped to a few subset of known results to derive and predict results. This book is useful for students, researchers and industry practitioners who want to explore modeling and simulation of the physical world complex systems from a different perspective. It raises the inevitable the question - ´Are life and the universe nothing but a collection of continuous systems processing information´.
This book presents advanced and practical techniques for performance optimization for highly parallel processing. Featuring various parallelization techniques in material science, it is a valuable resource for anyone developing software codes for computational sciences such as physics, chemistry, biology, earth sciences, space science, weather, disaster prevention and manufacturing, as well as for anyone using those software codes. Chapter 1 outlines supercomputers and includes a brief explanation of the history of hardware. Chapter 2 presents procedures for performance evaluation, while Chapter 3 describes the set of tuned applications in materials science, nanoscience and nanotechnology, earth science and engineering on the K computer. Introducing the order-N method, based on density functional theory (DFT) calculation, Chapter 4 explains how to extend the applicability of DFT to large-scale systems by reducing the computational complexity. Chapter 5 discusses acceleration and parallelization in classical molecular dynamics simulations, and lastly, Chapter 6 explains techniques for large-scale quantum chemical calculations, including the order-N method. This is the second of the two volumes that grew out of a series of lectures in the K computer project in Japan. The first volume addresses more basic techniques, and this second volume focuses on advanced and concrete techniques.