This book focuses on the ways in which resiliency can foster the transformation of cities. There is a growing need for our cities to be transformed into "smart" cities; in this regard, tremendous efforts are called for in order to face the environmental challenges that play a major role in the creation or transformation of cities and environments. This book covers a broad range of applications and approaches that are "smart" and "resilient," which, when combined, offer much more flexibility concerning the future of our cities. Consequently, this simple combination, which is producing sweeping changes around the globe, has attracted considerable attention from scholars and decision-makers alike.

In the second half of the past century, the fuzzy theory for solving engineering problems with uncertainties has grown enormously. The ability to perform control tasks in unknown environments is one of the most important characteristics of any intelligent control system. In addition, fuzzy logic provides an inference structure that enables the human reasoning capabilities to be applied to artificial knowledge-based systems. This book presents a few examples of fuzzy logic applications in electrical, chemical, computer and textile engineering with a simple and readable approach.

Recently, the fuzzy logic-based technique has received attention world-wide and has been becoming an emerging area with significant application possibilities. Fuzzy control theory is a combination of the fuzzy theory and the control system theory. It is a practical alternative for a variety of challenging control applications since it provides methods for designing non-linear controllers by the use of heuristic information. Fuzzy logic problems deal with situations that may have several reasonable solutions. The objective is to find the best of these possible solutions. Control systems based on the fuzzy logic theory can become more functional and flexible in comparison with conventional control systems. This book presents modern scientific knowledge in fuzzy logic control theory.