Rough Set Theory, introduced by Pawlak in the early 1980s, has become an important part of soft computing within the last 25 years. However, much of the focus has been on the theoretical understanding of Rough Sets, with a survey of Rough Sets and their applications within business and industry much desired. Rough Sets: Selected Methods and Applications in Management and Engineering provides context to Rough Set theory, with each chapter exploring a real-world application of Rough Sets.

Rough Sets is relevant to managers striving to improve their businesses, industry researchers looking to improve the efficiency of their solutions, and university researchers wanting to apply Rough Sets to real-world problems.

The 124 papers were carefully reviewed and selected from 188 submissions. The papers are organized in topical sections as follows: aggregation theory beyond the unit interval; formal concept analysis and uncertainty; fuzzy implication functions; fuzzy mathematical analysis and its applications; generalized sets and operators; information fusion techniques based on aggregation functions, pre-aggregation functions, and their generalizations; interval uncertainty; knowledge acquisition, representation and reasoning; logical structures of opposition and logical syllogisms; mathematical fuzzy logics; theoretical and applied aspects of imprecise probabilities; data science and machine learning; decision making modeling and applications; e-health; fuzzy methods in data mining and knowledge discovery; soft computing and artificia intelligence techniques in image processing; soft methods in statistics and data analysis; uncertainty, heterogeneity, reliability and explainability in AI; weak and cautious supervised learning.

The 124 papers were carefully reviewed and selected from 188 submissions. The papers are organized in topical sections as follows: aggregation theory beyond the unit interval; formal concept analysis and uncertainty; fuzzy implication functions; fuzzy mathematical analysis and its applications; generalized sets and operators; information fusion techniques based on aggregation functions, pre-aggregation functions, and their generalizations; interval uncertainty; knowledge acquisition, representation and reasoning; logical structures of opposition and logical syllogisms; mathematical fuzzy logics; theoretical and applied aspects of imprecise probabilities; data science and machine learning; decision making modeling and applications; e-health; fuzzy methods in data mining and knowledge discovery; soft computing and artificia intelligence techniques in image processing; soft methods in statistics and data analysis; uncertainty, heterogeneity, reliability and explainability in AI; weak and cautious supervised learning.

This two-volume set LNAI 14839-14840 constitutes the refereed proceedings of the International Joint Conference on Rough Sets, IJCRS 2024, held in Halifax, NS, Canada, during May 17–20, 2024.

The 43 full papers included in this book were carefully reviewed and selected from 56 submissions. They are organized in topical sections as follows: 

Part I: Rough Set Models and Foundations; Rule Induction and Machine Learning; Granular Computing; and Rough Set Applications.

Part II: Three-Way Decision and Rough Sets; Three-Way Decision in Data Analytics; Three-Way Decision in Broad Senses; Rental Market Data Mining; and Applications of Deep Learning and Soft Computing.

This two-volume set LNAI 14839-14840 constitutes the refereed proceedings of the International Joint Conference on Rough Sets, IJCRS 2024, held in Halifax, NS, Canada, during May 17–20, 2024.

The 43 full papers included in this book were carefully reviewed and selected from 56 submissions. They are organized in topical sections as follows: 

Part I: Rough Set Models and Foundations; Rule Induction and Machine Learning; Granular Computing; and Rough Set Applications.

part II: Three-Way Decision and Rough Sets; Three-Way Decision in Data Analytics; Three-Way Decision in Broad Senses; Rental Market Data Mining; and Applications of Deep Learning and Soft Computing.

This book constitutes the refereed proceedings of the International Joint Conference on Rough Sets, IJCRS 2016, held in Santiago de Chile, Chile, in October 2016.

The 46 revised full papers presented together with 7 keynotes, tutorials and expert papers were carefully reviewed and selected from 108 submissions. The papers are grouped in topical sections on Rough Sets, Approximation and Granulation; Rough Sets, Non-Determinism and Incompleteness; Rough Sets and Three-way Decisions; Fuzziness and Similarity in Knowledge Representation; Machine Learning and Decision Making; Ranking and Clustering; Derivation and Application of Rules and Trees; Derivation and Application of Feature Subsets.

This book constitutes the proceedings of the 23rd International Symposium on Foundations of Intelligent Systems, ISMIS 2017, held in Warsaw, Poland, in June 2017. The 56 regular and 15 short papers presented in this volume were carefully reviewed and selected from 118 submissions. The papers include both theoretical and practical aspects of machine learning, data mining methods, deep learning, bioinformatics and health informatics, intelligent information systems, knowledge-based systems, mining temporal, spatial and spatio-temporal data, text and Web mining. In addition, four special sessions were organized; namely, Special Session on Big Data Analytics and Stream Data Mining, Special Session on Granular and Soft Clustering for Data Science, Special Session on Knowledge Discovery with Formal Concept Analysis and Related Formalisms, and Special Session devoted to ISMIS 2017 Data Mining Competition on Trading Based on Recommendations, which was launched as a part of the conference.

Rough Set Theory, introduced by Pawlak in the early 1980s, has become an important part of soft computing within the last 25 years. However, much of the focus has been on the theoretical understanding of Rough Sets, with a survey of Rough Sets and their applications within business and industry much desired. Rough Sets: Selected Methods and Applications in Management and Engineering provides context to Rough Set theory, with each chapter exploring a real-world application of Rough Sets.

Rough Sets is relevant to managers striving to improve their businesses, industry researchers looking to improve the efficiency of their solutions, and university researchers wanting to apply Rough Sets to real-world problems.

The 124 papers were carefully reviewed and selected from 188 submissions. The papers are organized in topical sections as follows: aggregation theory beyond the unit interval; formal concept analysis and uncertainty; fuzzy implication functions; fuzzy mathematical analysis and its applications; generalized sets and operators; information fusion techniques based on aggregation functions, pre-aggregation functions, and their generalizations; interval uncertainty; knowledge acquisition, representation and reasoning; logical structures of opposition and logical syllogisms; mathematical fuzzy logics; theoretical and applied aspects of imprecise probabilities; data science and machine learning; decision making modeling and applications; e-health; fuzzy methods in data mining and knowledge discovery; soft computing and artificia intelligence techniques in image processing; soft methods in statistics and data analysis; uncertainty, heterogeneity, reliability and explainability in AI; weak and cautious supervised learning.

The 124 papers were carefully reviewed and selected from 188 submissions. The papers are organized in topical sections as follows: aggregation theory beyond the unit interval; formal concept analysis and uncertainty; fuzzy implication functions; fuzzy mathematical analysis and its applications; generalized sets and operators; information fusion techniques based on aggregation functions, pre-aggregation functions, and their generalizations; interval uncertainty; knowledge acquisition, representation and reasoning; logical structures of opposition and logical syllogisms; mathematical fuzzy logics; theoretical and applied aspects of imprecise probabilities; data science and machine learning; decision making modeling and applications; e-health; fuzzy methods in data mining and knowledge discovery; soft computing and artificia intelligence techniques in image processing; soft methods in statistics and data analysis; uncertainty, heterogeneity, reliability and explainability in AI; weak and cautious supervised learning.

This two-volume set LNAI 14839-14840 constitutes the refereed proceedings of the International Joint Conference on Rough Sets, IJCRS 2024, held in Halifax, NS, Canada, during May 17–20, 2024.

The 43 full papers included in this book were carefully reviewed and selected from 56 submissions. They are organized in topical sections as follows: 

Part I: Rough Set Models and Foundations; Rule Induction and Machine Learning; Granular Computing; and Rough Set Applications.

Part II: Three-Way Decision and Rough Sets; Three-Way Decision in Data Analytics; Three-Way Decision in Broad Senses; Rental Market Data Mining; and Applications of Deep Learning and Soft Computing.

This two-volume set LNAI 14839-14840 constitutes the refereed proceedings of the International Joint Conference on Rough Sets, IJCRS 2024, held in Halifax, NS, Canada, during May 17–20, 2024.

The 43 full papers included in this book were carefully reviewed and selected from 56 submissions. They are organized in topical sections as follows: 

Part I: Rough Set Models and Foundations; Rule Induction and Machine Learning; Granular Computing; and Rough Set Applications.

part II: Three-Way Decision and Rough Sets; Three-Way Decision in Data Analytics; Three-Way Decision in Broad Senses; Rental Market Data Mining; and Applications of Deep Learning and Soft Computing.

This book constitutes the refereed proceedings of the International Joint Conference on Rough Sets, IJCRS 2016, held in Santiago de Chile, Chile, in October 2016.

The 46 revised full papers presented together with 7 keynotes, tutorials and expert papers were carefully reviewed and selected from 108 submissions. The papers are grouped in topical sections on Rough Sets, Approximation and Granulation; Rough Sets, Non-Determinism and Incompleteness; Rough Sets and Three-way Decisions; Fuzziness and Similarity in Knowledge Representation; Machine Learning and Decision Making; Ranking and Clustering; Derivation and Application of Rules and Trees; Derivation and Application of Feature Subsets.

This book constitutes the proceedings of the 23rd International Symposium on Foundations of Intelligent Systems, ISMIS 2017, held in Warsaw, Poland, in June 2017. The 56 regular and 15 short papers presented in this volume were carefully reviewed and selected from 118 submissions. The papers include both theoretical and practical aspects of machine learning, data mining methods, deep learning, bioinformatics and health informatics, intelligent information systems, knowledge-based systems, mining temporal, spatial and spatio-temporal data, text and Web mining. In addition, four special sessions were organized; namely, Special Session on Big Data Analytics and Stream Data Mining, Special Session on Granular and Soft Clustering for Data Science, Special Session on Knowledge Discovery with Formal Concept Analysis and Related Formalisms, and Special Session devoted to ISMIS 2017 Data Mining Competition on Trading Based on Recommendations, which was launched as a part of the conference.