Interaktive Fuzzy Optimierung

Das vorliegende Lehrbuch ist eine Einführung in die globale Optimierung, die mathematische Sachverhalte einerseits stringent behandelt, sie aber andererseits auch sehr ausführlich motiviert und mit 80 Abbildungen illustriert. Das Buch richtet sich daher nicht nur an Mathematiker, sondern auch an Natur-, Ingenieur- und Wirtschaftswissenschaftler, die mathematisch fundierte Verfahren in ihrem Gebiet verstehen und anwenden möchten.

Innovation, Wachstum und Optimierung sind normative Grundlagen des Designs, der Technologie, der Wirtschaft, der Gesellschaft und der Kultur. Unter dem Vorzeichen der Digitalisierung zeichnen sich neue ›Optima‹ ab, in denen Menschen zum Bestandteil entgrenzter Netzwerkstrukturen werden. Die in Würzburg entstandenen Aufsätze des vorliegenden Bandes gehen ambivalenten Aspekten dieser Entwicklung mit wissenschaftlichen und gestalterischen Methoden nach. Der Gastbeitrag geht der Frage nach, was dialektisches Denken in Diskurs und Praxis der Gestaltung bedeutet.
Die Herausgeber

Become an expert in Fuzzy Logic and Control Systems using Python in a Professional way.

This book provides an extensive set of tools for applying fuzzy mathematics and graph theory to real-life problems. Balancing the basics and latest developments in fuzzy graph theory, this book starts with existing fundamental theories such as connectivity, isomorphism, products of fuzzy graphs, and different types of paths and arcs in fuzzy graphs to focus on advanced concepts such as planarity in fuzzy graphs, fuzzy competition graphs, fuzzy threshold graphs, fuzzy tolerance graphs, fuzzy trees, coloring in fuzzy graphs, bipolar fuzzy graphs, intuitionistic fuzzy graphs, m-polar fuzzy graphs, applications of fuzzy graphs, and more.

This book provides readers with a systematic and unified framework for identification and adaptive control of Takagi–Sugeno (T–S) fuzzy systems. Its design techniques help readers applying these powerful tools to solve challenging nonlinear control problems. The book embodies a systematic study of fuzzy system identification and control problems, using T–S fuzzy system tools for both function approximation and feedback control of nonlinear systems. Alongside this framework, the book also:

This book presents the necessary and essential backgrounds of fuzzy set theory and linear programming, particularly a broad range of common Fuzzy Linear Programming (FLP) models and related, convenient solution techniques. These models and methods belong to three common classes of fuzzy linear programming, namely: (i) FLP problems in which all coefficients are fuzzy numbers, (ii) FLP problems in which the right-hand-side vectors and the decision variables are fuzzy numbers, and (iii) FLP problems in which the cost coefficients, the right-hand-side vectors and the decision variables are fuzzy numbers.

This book presents a mathematically-based introduction into the fascinating topic of Fuzzy Sets and Fuzzy Logic and might be used as textbook at both undergraduate and graduate levels and also as reference guide for mathematician, scientists or engineers who would like to get an insight into Fuzzy Logic.

After developing fuzzy set theory, many contributors focused their research on the extension of fuzzy sets and their computational methodologies, strengthening modern science and technology. In some real-life phenomena, the conventional methods and traditional fuzzy sets cannot be explained, whereas the extension of fuzzy sets and effective new computing methods can explain it adequately.