This book offers a timely overview of fuzzy and rough set theories and methods. Based on selected contributions presented at the International Symposium on Fuzzy and Rough Sets, ISFUROS 2017, held in Varadero, Cuba, on October 24-26, 2017, the book also covers related approaches, such as hybrid rough-fuzzy sets and hybrid fuzzy-rough sets and granular computing, as well as a number of applications, from big data analytics, to business intelligence, security, robotics, logistics, wireless sensor networks and many more. It is intended as a source of inspiration for PhD students and researchers in the field, fostering not only new ideas but also collaboration between young researchers and institutions and established ones.

Since their very inception, both fuzzy and rough set theories have earned a sound, well-deserved reputation owing to their intrinsic capabilities to model uncertainty coming from the real world. The increasing amount of investigations on both subjects reported every year in the literature vouches for the dynamics of the area and its rapid advancements.

In the last few years the widespread utilization of fuzzy and rough sets as granulation sources has contributed to lay both methodologies in a privileged position within Granular Computing, thus giving rise to a sort a modeling which is far closer to the way human beings perceive their environment – via granulated knowledge.

This volume is a compilation of the best papers presented at the First International Symposium on Fuzzy and Rough Sets (ISFUROS 2006) held in Santa Clara, Cuba. You will therefore find valuable contributions both in the theoretical field as in several application domains such as intelligent control, data analysis, decision making and machine learning, just to name a few. Together, they will catch you up with the huge potential of the aforementioned methodologies.

Along the years, rough set theory has earned a well-deserved reputation as a sound methodology for dealing with imperfect knowledge in a simple though mathematically sound way. This edited volume aims at continue stressing the benefits of applying rough sets in many real-life situations while still keeping an eye on topological aspects of the theory as well as strengthening its linkage with other soft computing paradigms. The volume comprises 11 chapters and is organized into three parts. Part 1 deals with theoretical contributions while Parts 2 and 3 focus on several real world data mining applications. Chapters authored by pioneers were selected on the basis of fundamental ideas/concepts rather than the thoroughness of techniques deployed. Academics, scientists as well as engineers working in the rough set, computational intelligence, soft computing and data mining research area will find the comprehensive coverage of this book invaluable.

This book offers a timely overview of fuzzy and rough set theories and methods. Based on selected contributions presented at the International Symposium on Fuzzy and Rough Sets, ISFUROS 2017, held in Varadero, Cuba, on October 24-26, 2017, the book also covers related approaches, such as hybrid rough-fuzzy sets and hybrid fuzzy-rough sets and granular computing, as well as a number of applications, from big data analytics, to business intelligence, security, robotics, logistics, wireless sensor networks and many more. It is intended as a source of inspiration for PhD students and researchers in the field, fostering not only new ideas but also collaboration between young researchers and institutions and established ones.

Since their very inception, both fuzzy and rough set theories have earned a sound, well-deserved reputation owing to their intrinsic capabilities to model uncertainty coming from the real world. The increasing amount of investigations on both subjects reported every year in the literature vouches for the dynamics of the area and its rapid advancements.

In the last few years the widespread utilization of fuzzy and rough sets as granulation sources has contributed to lay both methodologies in a privileged position within Granular Computing, thus giving rise to a sort a modeling which is far closer to the way human beings perceive their environment – via granulated knowledge.

This volume is a compilation of the best papers presented at the First International Symposium on Fuzzy and Rough Sets (ISFUROS 2006) held in Santa Clara, Cuba. You will therefore find valuable contributions both in the theoretical field as in several application domains such as intelligent control, data analysis, decision making and machine learning, just to name a few. Together, they will catch you up with the huge potential of the aforementioned methodologies.

Along the years, rough set theory has earned a well-deserved reputation as a sound methodology for dealing with imperfect knowledge in a simple though mathematically sound way. This edited volume aims at continue stressing the benefits of applying rough sets in many real-life situations while still keeping an eye on topological aspects of the theory as well as strengthening its linkage with other soft computing paradigms. The volume comprises 11 chapters and is organized into three parts. Part 1 deals with theoretical contributions while Parts 2 and 3 focus on several real world data mining applications. Chapters authored by pioneers were selected on the basis of fundamental ideas/concepts rather than the thoroughness of techniques deployed. Academics, scientists as well as engineers working in the rough set, computational intelligence, soft computing and data mining research area will find the comprehensive coverage of this book invaluable.