The book outlines selected projects conducted under the supervision of the author. Moreover, it discusses significant relations between Interactive Granular Computing (IGrC) and numerous dynamically developing scientific domains worldwide, along with features characteristic of the author's approach to IGrC. The results presented are a continuation and elaboration of various aspects of Wisdom Technology, initiated and developed in cooperation with Professor Andrzej Skowron.
Based on the empirical findings from these projects, the author explores the following areas: (a) understanding the causes of the theory and practice gap problem (TPGP) in complex systems engineering (CSE);
(b) generalizing computing models of complex adaptive systems (CAS) (in particular, natural computing models) by constructing an interactive granular computing (IGrC) model of networks of interrelated interacting complex granules (c-granules), belonging to a single agent and/or to a group of agents;
(c) developing methodologies based on the IGrC model to minimize the negative consequences of the TPGP.
The book introduces approaches to the above issues, using the proposed IGrC model. In particular, the IGrC model refers to the key mechanisms used to control the processes related to the implementation of CSE projects.
One of the main aims was to develop a mechanism of IGrC control over computations that model a project's implementation processes to maximize the chances of its success, while at the same time minimizing the emerging risks. In this regard, the IGrC control is usually performed by means of properly selected and enforced (among project participants) project principles. These principles constitute examples of c-granules, expressed by complex vague concepts (represented by c-granules too). The c-granules evolve with time (in particular, the meaning of the concepts is also subject of change). This methodology is illustrated using project principles applied by the author during the implementation of the POLTAX, AlgoTradix, Merix, and Excavio projects outlined in the book.
Автор: Yiyu Yao; Qinghua Hu; Hong Yu; Jerzy W. Grzymala-B Название: Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing ISBN: 331925782X ISBN-13(EAN): 9783319257822 Издательство: Springer Рейтинг: Цена: 8944.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Cyberspace is a ubiquitous realm interconnecting every aspect of modern society, enabled by broadband networks and wireless signals around us, existing within local area networks in our schools, hospitals and businesses, and within the massive grids that power most countries. Securing cyberspace to ensure the continuation of growing economies and to protect a nations way of life is a major concern for governments around the globe.This book contains papers presented at the NATO Advanced Research Workshop ARW entitled Best Practices and Innovative Approaches to Develop Cyber Security and Resiliency Policy Framework, held in Ohrid,
Автор: Witold Pedrycz; Shyi-Ming Chen Название: Granular Computing and Decision-Making ISBN: 3319364901 ISBN-13(EAN): 9783319364902 Издательство: Springer Рейтинг: Цена: 18284.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Granularity Helps Explain Seemingly Irrational Features of Human Decision Making.- A Comprehensive Granular Model for Decision Making with Complex Data.-Granularity in Economic Decision Making: An Interdisciplinary Review.- Decision Makers' Opinions Changing Attitude-Driven Consensus Model under Linguistic Environment and Its Application in Dynamic MAGDM.- Using Computing with Words for Managing Non-Cooperative Behaviors in Large Scale Group Decision Making.- A Type-2 Fuzzy Logic Approach for Multi-Criteria Group Decision Making.- Multi-Criteria Influence Diagrams - A Tool for the Sequential Group Risk Assessment.-Consensus Modeling under Fuzziness - A Dynamic Approach with Random Iterative Steps.- Decision Making - Interactive and Interactive Approaches.- Collaborative Decision Making by Ensemble Rule Based Classification Systems.- A GDM Method Based on Granular Computing for Academic Library Management.- Spatial-taxon Information Granules as Used in Iterative Fuzzy-Decision-Making for Image Segmentation.- Group Decision Making in Fuzzy Environment - An Iterative Procedure Based on Group Dynamics.- Fuzzy Optimization in Decision Making of Air Quality Management.- Group Decision Making in Fuzzy Environment - An Iterative Procedure Based on Group Dynamics.- Fuzzy Optimization in Decision Making of Air Quality Management.
Автор: Rafael Bello; Rafael Falc?n; Witold Pedrycz Название: Granular Computing: At the Junction of Rough Sets and Fuzzy Sets ISBN: 3642095682 ISBN-13(EAN): 9783642095689 Издательство: Springer Рейтинг: Цена: 30606.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 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.
Описание: The techniquesused and combined in the proposed method are modular neural networks (MNNs)with a Granular Computing (GrC) approach, thus resulting in a new concept ofMNNs;
Автор: Lech Polkowski; Piotr Artiemjew Название: Granular Computing in Decision Approximation ISBN: 3319128795 ISBN-13(EAN): 9783319128795 Издательство: Springer Рейтинг: Цена: 22203.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A striking feature of granular classifiers obtained by this approach is that preserving the accuracy of them on original data, they reduce substantially the size of the granulated data set as well as the set of granular decision rules.
Автор: Piotr Ho?ko Название: Granular-Relational Data Mining ISBN: 3319527509 ISBN-13(EAN): 9783319527505 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Preface.- Chapter 1: Introduction.- Part I: Generalized Related Set Based Approach.- Chapter 2: Information System for Relational Data.- Chapter 3: Properties of Granular-Relational Data Mining Framework.- Chapter 4: Association Discovery and Classification Rule Mining.- Chapter 5: Rough-Granular Computing.- Part II: Description Language Based Approach.- Chapter 6: Compound Information Systems.- Chapter 7: From Granular-Data Mining Framework to its Relational Version.- Chapter 8: Relation-Based Granules.- Chapter 9: Compound Approximation Spaces.- Conclusions.- References.- Index.
Автор: Tsau Young Lin; Yiyu Y. Yao; Lotfi A. Zadeh Название: Data Mining, Rough Sets and Granular Computing ISBN: 3790825085 ISBN-13(EAN): 9783790825084 Издательство: Springer Рейтинг: Цена: 27251.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In essence, data mining deals with summarization of information which is resident in large data sets, while granular computing plays a key role in the summarization process by draw- ing together points (objects) which are related through similarity, proximity or functionality.
Автор: Dominik Slezak; Marcin Szczuka; Ivo Duentsch; Yiyu Название: Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing ISBN: 3540286535 ISBN-13(EAN): 9783540286530 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Part of a two volume set, this title includes information related to rough set approximations, rough-algebraic foundations, feature selection and reduction, rough-probabilistic approaches, rough-fuzzy hybridization, fuzzy methods in data analysis, evolutionary computing, machine learning, probabilistic network models, granular computing, and more.
Автор: Dominik Slezak; JingTao Yao; James F. Peters; Wojc Название: Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing ISBN: 3540286608 ISBN-13(EAN): 9783540286608 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Contains papers from the proceedings of the 10th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, RSFDGrC 2005, held in Regina, Canada in August/September 2005 in 2 volumes.
Автор: Han Liu; Mihaela Cocea Название: Granular Computing Based Machine Learning ISBN: 331970057X ISBN-13(EAN): 9783319700571 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Introduction, - Traditional Machine Learning, - Semi-supervised Learning through Machine Based Labelling, - Nature Inspired Semi-heuristic Learning, - Fuzzy Classification through Generative Multi-task Learning, - Multi-granularity Semi-random Data Partitioning, - Multi-granularity Rule Learning, - Case Studies, - Con
Автор: Lech Polkowski; Piotr Artiemjew Название: Granular Computing in Decision Approximation ISBN: 3319366211 ISBN-13(EAN): 9783319366210 Издательство: Springer Рейтинг: Цена: 18284.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A striking feature of granular classifiers obtained by this approach is that preserving the accuracy of them on original data, they reduce substantially the size of the granulated data set as well as the set of granular decision rules.
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