Note: Intro -- Phytohortology -- The Scientific Term -- About the Main Authors -- Explanation and Remarks on Publishing -- Brief Introduction to the Book -- FOREWORD -- PREFACE -- The distribution of major botanical gardens in China* -- Abbreviation of Chinese Botanical Garden Names -- CONTENTS -- Chapter 1 Botanical Garden and Botanical Garden Science, PHYTOHORTOLOGY -- 1.1 Professional Concept of a Botanical Garden -- 1.2 Nature and Function of Botanical Gardens -- 1.2.1 Nature -- 1.2.2 Function -- 1.2.3 Feature of Scientific Research in Botanical Gardens -- 1.3 Classification of Botanical Gardens and Their Features -- 1.3.1 Multi-function Integrated Botanical Gardens -- 1.3.2 Botanical Gardens Belonging to University or Research Institute -- 1.3.3 Professional Botanical Gardens -- 1.3.4 Other Types of Botanical Gardens -- References -- Chapter 2 The History of Botanical Gardens -- 2.1 The History of World Botanical Gardens -- 2.1.1 The Beginning of Modern Botanical Gardens -- 2.1.2 Growth of Modern Botanical Gardens -- 2.1.3 The Establishment of International Botanic Gardens Organization Promoted the Development of Botanical Gardens -- 2.2 The history of Chinese Modern Botanical Gardens -- 2.2.1 The Feature of Botanical Garden Development -- 2.2.2 Development of the Quantity of Botanical Gardens -- 2.2.3 Distribution of Botanical Gardens in China -- 2.2.4 The Prospects of Professional Development of Botanical Gardens -- References -- APPENDIX: The Declaration of Gran Canaria -- Chapter 3 Ex-situ Conservation in Botanical Gardens -- 3.1 Essentials of Ex-situ Conservation -- 3.1.1 Status and Reasons for Species Endangerment -- 3.1.2 The Concept of the Integrative Conservation -- 3.1.3 Significance and Function of Ex-situ Conservation -- 3.1.4 The Target Taxa Appropriated to Ex-situ Conservation. , 3.1.5 Ex-situ Conservation in Botanical Garden Provides "Refuge" for Endangered Plants, and a "Transition Point" of Cultivation for Wild Plants -- 3.2 The Status Quo of Ex-situ Conservation in Botanical Gardens and the Convention On Biological Diversity (CBD) -- 3.2.1 The Status Quo of Plant Introduction and Collections in Botanical Gardens -- 3.2.2 The Relationship of Ex-situ Conservation and the Convention on Biological Diversity -- 3.3 The Evaluation of Ex-situ Conservation -- 3.3.1 The Multiple and Comprehensive Evaluation System -- 3.3.2 Establishing the Evaluation Criteria for Collections According to the Character and Assignments of Each Garden -- 3.4 Ex-situ Conservation Technique -- 3.4.1 Basic Scientific Disciplines -- 3.4.2 Minimum Population -- 3.4.3 The Sampling Technique -- 3.4.4 Seed Bank -- 3.5 The Recordkeeping System of Living Plant Collections -- 3.5.1 The Importance of Recordkeeping -- 3.5.2 Traditional Plant Recordkeeping -- 3.5.3 The Development of the Computerization of Plant Recording Systems -- 3.5.4 Analysis on the Issues and Outlooks in the Computerization Process of Plant Records in Botanical Gardens -- 3.6 The Ex-situ Conservation of Medicinal Plants -- 3.6.1 The Complexity of Medicinal Plant Conservation -- 3.6.2 The Urgency of the Medicinal Plant Conservation -- 3.6.3 Ex-situ Conservation Is the Base of Medicinal Plant Cultivation -- 3.7 Urban Biodiversity Conservation -- 3.7.1 The Process of Urbanization Is the Result of Social and Economic Development -- 3.7.2 Urban Development Causes a Serious Loss of Biodiversity -- 3.7.3 The Ecological Environment of Urban Bring About Variation of Plant Species -- 3.7.4 Urgent Protection Needed for Germplasm Resources in Cities -- 3.7.5 Cities Need More Plant Resources Than Before -- 3.8 The Ex-situ Conservation and the Blue Book. , 3.8.1 Species That Can Be Removed From the Red List -- 3.8.2 Species That Can be Listed in the Blue Book -- 3.9 Improvement of the Ex-situ Conservation Pattern, and Study on the Centers For Ex-situ Plant Conservation -- 3.9.1 Improvement of the Ex-situ Conservation Pattern -- 3.9.2 Exploration of the Centers for Plant Ex-situ Conservation -- References -- APPENDIX I -- APPENDIX II -- Chapter 4 Plant Introduction and Acclimatization in Botanical Gardens -- 4.1 The Definition and Criterion of Plant Introduction and Acclimatization -- 4.2 The Theory of Plant Introduction and Acclimatization and Its Application -- 4.2.1 Climatic Similarity Theory -- 4.2.2 Ecological History Analysis -- 4.2.3 The Original Center of Cultivated Plants -- 4.2.4 Ecological Factor Analysis Method and Plant Introduction Effect Theory -- 4.2.5 The Biodiversity Centers -- 4.3 The Mission of Plant Introduction and Acclimatization of Botanical Gardens -- 4.4 The Plant Introduction of Specific Groups, Families, and Genera -- 4.4.1 The Introduction of Specific Groups -- 4.4.2 The Introduction of Specific Families -- 4.4.3 The Introduction of Specific Genera -- 4.4.4 Geographical Regional Introduction-Chinese Plants Around the World -- 4.5 The Plant Introduction and Exploration of Economic Plants in Botanical Gardens-with Special Reference of Industrial Plant Materials in China -- 4.5.1 Hevea brasiliensis -- 4.5.2 Nicotiana tabacum -- 4.5.3 Lavandula angustifolia -- 4.5.4 Carthamus tinctorius -- 4.5.5 Stevia rebaudiana -- 4.5.6 Toxicodendron vernicifluun -- 4.5.7 Cistus ladaniferus -- 4.6 Some Cases of the Fruit Tree Introduction and Development by Chinese Botanical Gardens -- 4.6.1 Vitis -- 4.6.2 Actinidia -- 4.6.3 Rubus -- 4.6.4 Vaccinium -- 4.6.5 Mangifera indica -- 4.6.6 Others. , 4.7 The Introduction and Acclimatization of Trees and Environmental Plants in Chinese Botanical Gardens -- 4.7.1 Trees -- 4.7.2 Psammophyte -- 4.8 The Introduction and Acclimatization of Medicinal Plants in Chinese Botanical Gardens -- 4.8.1 A Survey of Chinese Botanical Garden in Medicinal Plant Introduction -- 4.8.2 The Key Species Researched in Chinese Botanical Gardens -- 4.8.3 The Stress Cultivation -- 4.9 The Introduction of Ornamental Plants in Chinese Botanical Gardens -- 4.9.1 Paeonia -- 4.9.2 Chimonanthus -- 4.9.3 Victoria -- 4.9.4 Nelumbo and Nymphaea -- 4.10 The Introduction and Acclimatization of Ground Cover Plants and Turf Grass in Chinese Botanical Gardens -- 4.10.1 The Ground Cover Plants -- 4.10.2 Turf Grass -- 4.11 The Introduction of Hedgerow Plants -- 4.12 The Plant Introduction and Acclimatization and Invasive Species -- 4.12.1 The Concept of Invasive Species -- 4.12.2 The Damage Status of Invasive Species -- 4.12.3 The Invasive Species and the Introduction and Acclimatization of Plants -- References -- Chapter 5 The Greenhouse System in Botanical Gardens -- 5.1 The Types and Functions of Botanical Garden Greenhouses -- 5.1.1 The Exhibition Greenhouse -- 5.1.2 Propagation Greenhouse -- 5.1.3 Experimental Greenhouse -- 5.2 The History of the Exhibition Greenhouse in Botanical Gardens.. -- 5.2.1 Early Non-exhibition Greenhouse -- 5.2.2 The Birth of Large-scale Exhibition Greenhouses and Their Three Development Stages -- 5.2.3 The Architectural Art in Large-scale Exhibition Greenhouses -- 5.2.4 The Origin About the Name of Greenhouse -- 5.3 Examples of Greenhouse Systems in Botanical Gardens -- 5.3.1 Greenhouse Series in RBG Kew -- 5.3.2 The Eden Project -- 5.4 A Great Variety of Greenhouse Plants -- 5.4.1 Types of Display -- 5.4.2 The Plants Displayed in Exhibition Greenhouses -- 5.5 Ancillary Facilities -- 5.5.1 The Sun-shelters. , 5.5.2 The Preparation of Soil in Greenhouse and Soil Disinfection Equipment -- 5.5.3 The Reservoir -- References -- Chapter 6 Education in Botanical Gardens -- 6.1 Aim, Significance, and Role of Education in Botanical Gardens -- 6.2 Objects of Botanical Gardens Education -- 6.2.1 Children and Students -- 6.2.2 Adults -- 6.2.3 People with Special Needs -- 6.3 Educational Approaches and Forms in Botanical Gardens -- 6.3.1 Ordinary Information for Visitors -- 6.3.2 Scientific Guide -- 6.3.3 Plant Labels -- 6.3.4 Popular Science Exhibition and Flower Show -- 6.3.5 Summer (Winter) Camp -- 6.3.6 Popular Science Lectures and Training Courses -- 6.3.7 Popular Science Competition -- 6.3.8 Education Gallery, Propaganda Window and Cordial Labels -- 6.3.9 Popular Science Reading Materials and Press -- 6.3.10 Setting up Advisory Mailbox and Hotline -- 6.3.11 Establishing Cooperative Relationships with Schools -- 6.3.12 International Cooperation and Exchanges -- 6.4 Education Facilities in Botanical Gardens -- 6.4.1 Hardware -- 6.4.2 Software -- 6.5 Association: Friends of Botanical Gardens -- References -- Chapter 7 Landscape Planning, Design and Architecture in Botanical Gardens -- 7.1 Basic Principles for Landscape Architecture in a Botanical Garden -- 7.1.1 Adapting to the Characteristics of Botanical Gardens -- 7.1.2 Reflecting the Nature of Botanical Gardens -- 7.1.3 Fully Utilizing Native Natural Resources -- 7.2 Selecting Location for Botanical Gardens -- 7.2.1 Selecting Geographical Locations -- 7.2.2 Selecting Site -- 7.3 Layout of a Botanical Garden -- 7.3.1 Adjusting Topography and Regulating Water Systems -- 7.3.2 Functional Areas and Roads -- 7.3.3 Landscape Structures -- 7.3.4 Arrangement of Plant Groups -- 7.4 Exhibit the Plant Diversity, Landscape Architecture and Planning in Specific and Topic Gardens. , 7.4.1 Scientific Research Foundation of Specific and Topic Garden Development.

Note: Description based on publisher supplied metadata and other sources

Note: Title -- Preface -- Organization -- Table of Contents -- Part I: Rough Sets and Its Generalizations -- A Characterization of Rough Separability -- Introduction -- Rough Sets and Indiscernibility Relations -- Rough Separability and Pseudometric Spaces -- Pseudometrics Determined by Families of Sets -- Equivalence of Pseudometric Spaces -- Conclusions -- References -- Data-Driven Valued Tolerance Relation -- Introduction -- Valued Tolerance Relation -- Data-Driven Valued Tolerance Relation -- Calculation of Tolerance Degree -- Auto-selection of Threshold -- Experiment Results -- Conclusions -- References -- Optimistic Multi-Granulation Fuzzy Rough Set Model Based on Triangular Norm -- Introduction -- The Rough Set Based on Triangular Norm -- Optimistic Multi-Granulation Fuzzy Rough Set Based on Triangular Norm -- Conclusions -- References -- Rough Set Model Based on Hybrid Tolerance Relation -- Introduction -- Preliminaries -- Strong and Weak Indiscernibility Relations -- Incomplete Information System and Tolerance Relations -- Weak Tolerance Relations -- Hybrid Tolerance Relation and Decision Rule -- Hybrid Tolerance Relation -- Decision Rule -- Conclusions -- References -- Scalable Improved Quick Reduct: Sample Based -- Introduction -- Overview of IQRA and IQRA_IG Algorithms -- Proposed SGIQRA_IG Algorithm -- Experiments and Results -- Analysis of Results -- Conclusion -- References -- Soft Rough Sets Based on Similarity Measures -- Introduction -- Preliminaries -- Analysis of Soft Rough Approximations -- Soft Fuzzy Rough Sets Based on Similarity Measures -- Concluding Remarks -- References -- Theory of Truth Degrees in Three Valued Formed System RSL -- Introduction -- Basic of Rough Set and Formed System RSL -- The Theory of Truth Degree -- Similarity Degree and a Pseudo-metric among Formulas -- Conclusion -- References. , Upper Approximation Reduction Based on Intuitionistic Fuzzy T Equivalence Information Systems -- Introduction -- Intuitionistic Fuzzy Rough Sets and Intuitionistic Fuzzy T Equivalence Information Systems -- Upper Approximation Reduction in IF T Equivalence Information Systems with Decision -- An Illustrated Example -- Conclusions -- References -- Part II: Rough Sets in Data and Knowledge Processing -- A Fuzzy-Rough Sets Based Compact Rule Induction Method for Classifying Hybrid Data -- Introduction -- Preliminary Notion of Rough Sets Based Rule Induction Method -- Fuzzy Rough Sets Based Compact Rule Learner -- Experiments and Discussion -- Conclusion -- References -- A New Intuitionistic Fuzzy Rough Set Approach for Decision Support -- Introduction -- Preliminaries -- Dominance-Based Rough Set Approach -- Intuitionistic Fuzzy Theory -- Uncertain Rule Induction -- Believe Factor -- Measurements -- Believable Rule Induction -- Illustrative Example -- Decision Table and Rough Approximations -- Believable Rule Induction -- Verification of Sorting Capability -- Conclusion -- References -- A New Rule Induction Method from a Decision Table Using a Statistical Test -- Introduction -- Model of Data Generation -- Proposal of Rule Estimation Method by Statistical Test -- Algorithm for Rule Induction -- Experimental Studies -- Conclusions -- References -- A Rough Neurocomputing Approach for Illumination Invariant Face Recognition System -- Introduction -- Rough Set Theory (RST) -- Proposed RNRS Architecture -- Design of ADNN -- Approximation Neuron -- Decider Neuron -- Architecture of ADNN -- Experimental Results -- Conclusion -- References -- An Approximation Decision Entropy Based Decision Tree Algorithm and Its Application in Intrusion Detection -- Introduction -- Preliminaries -- Approximation Decision Entropy -- Decision Tree Algorithm DTADE. , Experimental Results -- Conclusion -- References -- Application of Rough Set Theory to Prediction of Antimicrobial Activity of Bis-quaternary Ammonium Chlorides -- Introduction -- Material and Methods -- Material -- Discovery of Decision Rules Using DRSA -- Attribute Relevance -- Results and Discussion -- References -- Classification and Decision Based on Parallel Reducts and F-Rough Sets -- Introduction -- F-Rough Sets and Parallel Reducts -- Three Types of Classification(Decision) Based on Parallel Reducts and F-Rough Sets -- Specific Decision Subsystem -- Decision Subsystem Selected Randomly -- Deciding by a Majority Vote -- Conclusion -- References -- Evidential Clustering or Rough Clustering: The Choice Is Yours -- Introduction -- Similarities between ECM and RKM -- Strengths of ECM -- Strengths of RKM -- Conclusion -- References -- Heuristic for Attribute Selection Using Belief Discernibility Matrix -- Introduction -- Rough Set Theory -- Belief Function Theory -- Heuristic for Attribute Selection Method Using Belief Discernibility Matrix -- Uncertain Decision Table -- Feature Selection with Johnson´s Heuristic Algorithm -- Belief Discernibility Matrix -- Belief Rough Set Classifier -- Experimental Results -- Conclusion and Future Work -- References -- Incremental Rules Induction Based on Rule Layers -- Introduction -- Rough Sets and Probabilistic Rules -- Rough Set Theory -- Probabilistic Rules -- Problems in Incremental Rule Induction -- Theory for Incremental Learning -- Both: Negative -- R: Positive -- d: Positive -- d: Positive -- Updates of Accuracy and Coverage -- An Algorithm for Incremental Learning -- Algorithm -- Experimental Results -- Conclusion -- References -- Optimization of Inhibitory Decision Rules Relative to Length and Coverage -- Introduction -- Nonredundant Decision Rules -- Directed Acyclic Graph (T). , Procedures of Optimization Relative to Length and Coverage -- Experimental Results -- Conclusions -- References -- Parallelized Computing of Attribute Core Based on Rough Set Theory and MapReduce -- Introduction -- Parallel Algorithm for Computing Attribute Core Based on Rough Set and MapReduce -- Experiments and Discussion -- Case Study -- Comparative Experiments for Efficiency of the Proposed Algorithm -- Conclusion -- References -- Semi-supervised Vehicle Recognition: An Approximate Region Constrained Approach -- Introduction -- Semi-supervised Learning Based on Approximate Region Constraints (SsL-ARC) -- SsL-ARC Algorithm Framework -- Approximate Region Constraints -- Experiments -- Conclusions -- References -- Part III: Knowledge Technology -- A Color Image Segmentation Algorithm by Integrating Watershed with Region Merging -- Introduction -- Watershed Algorithm -- Merger of the Image Regions -- Distance Metric between Graph Regions -- Merger Algorithm of the Image Regions -- Experimental Results and Analysis -- Conclusion -- References -- A Mixed Strategy Multi-Objective Coevolutionary Algorithm Based on Single-Point Mutation and Particle Swarm Optimization -- Introduction -- Multi-Objective Optimization Problems -- Multi-Objective Coordination Operator Evolutionary Programming Based on Single Point and PSO Operator -- Mixed Strategy -- Maintenance of External Archive -- Algorithm Description -- The Experimental Results -- Experiment Setting -- Results and Analysis -- Summary -- References -- A Novel Distributed Machine Learning Method for Classification: Parallel Covering Algorithm -- Introduction -- Covering Algorithm Overview -- Learn Procedure -- Classification -- Parallel Covering Algorithm -- Experiments and Analysis -- Uniprocessor Environment -- Multi-core Parallel Computing Environment -- Conclusion -- References. , A Spatial Clustering Method for Points-with-Directions -- Introduction -- Related Work -- Points-with-Directions Clustering -- Problem Definition -- Spatial Clustering Method for Points-with-Directions -- The Limitations of PDC -- PDC+ -- Experimental Evaluation -- Conclusions and Future Work -- References -- An Argumentation Framework for Non-monotonic Reasoning in Description Logic -- Introduction -- The Description Logic ALC -- Defeasible ALC -- Inductive Terminologies -- Conclusion and Future Work -- References -- Analysis of Symmetry Properties for Bayesian Confirmation Measures -- Introduction -- Preliminaries -- Property of Bayesian Confirmation -- Properties of Symmetry -- A New Set of Symmetry Properties -- Conclusions -- References -- Applying Verbal Decision Analysis in Selecting Specific Practices of CMMI -- Introduction -- Verbal Decision Analysis: Overview and Application -- Conclusions, Future Works and Acknowledgment -- References -- Belief Networks in Classification of Laryngopathies Based on Speech Spectrum Analysis -- Introduction -- Laryngopathy Data -- Theoretical Foundations of BeliefSEEKER -- Experiments -- Conclusions -- References -- Comparing Similarity of Concepts Identified by Temporal Patterns of Terms in Biomedical Research Documents -- Introduction -- A Method for Analyzing Distances on Taxonomy and Temporal Patterns of Term Usage -- Obtaining Temporal Patterns of Data-Driven Indexes Related to Term Usages -- Defining Similarity of Terms on a Structured Taxonomy -- Analyzing Similarity of Terms in Temporal Patterns of Medical Research Documents -- Analysis of Disease over Time -- Obtaining Temporal Patterns of Medical Terms about Migraine Drug Therapy Studies -- Similarity of the Terms in Obtained Temporal Patterns on MeSH -- Conclusion -- References. , Extracting Incidental and Global Knowledge through Compact Pattern Trees in Distributed Environment.

Note: Intro -- Preface -- Organization -- Contents -- Rough Sets: The Experts Speak -- Decision-Oriented Rough Set Methods -- 1 Introduction -- 2 Decision-Oriented Rough Set Models and Methods -- 3 Concluding Remarks and Future Perspectives -- References -- On Generalized Decision Functions: Reducts, Networks and Ensembles -- 1 Introduction -- 2 Generalized Decision Functions -- 3 Simplified Conditional Independence -- 4 Generalized Decision Measures -- 5 Embedded Decision Reducts -- 6 Ensembles of Complementary Reducts -- 7 Attribute Decomposition Problem -- 8 Heuristics and Boolean Representation -- 9 Conclusions and Future Directions -- References -- Formalization of Medical Diagnostic Rules -- 1 Introduction -- 2 Background: Medical Diagnostic Process -- 2.1 RHINOS -- 2.2 Focusing Mechanism -- 3 Basics of Rule Definitions -- 3.1 Rough Sets -- 3.2 Classification Accuracy and Coverage -- 3.3 Probabilistic Rules -- 4 Formalization of Medical Diagnostic Rules -- 4.1 Deterministic Model -- 4.2 Probabilistic Model -- 5 New Rule Induction Model -- 6 Discussion: What Has Not Been Achieved? -- 7 Conclusion -- References -- Multi-granularity Intelligent Information Processing -- 1 Introduction -- 2 Multi-granularity Rough Set Theory -- 3 Multi-granularity Computing with Words -- 4 Multi-granularity Fuzzy Quotient Space Theory -- 5 Multi-granularity Cloud Model -- 6 Multi-granularity Clustering Based on Density Peaks -- 7 Conclusion -- References -- Granular Structures Induced by Interval Sets and Rough Sets -- 1 Introduction -- 2 Interval Sets -- 2.1 Interval Sets and Interval-Set Algebras -- 2.2 Inclusion Relations in Interval Sets -- 2.3 Granular Structure in Interval Sets -- 3 The Granular Structure Based on Order Relation in Interval Sets -- 3.1 Preference -- 3.2 Interval Set Comparisons. , 4 Granular Structures in Interval Sets from Set-Theoretic Perspectives -- 4.1 Granular Structure for (I(2U),w) -- 4.2 Granular Structure for (I(2U),w+) -- 4.3 Granular Structure for (I(2U),p) -- 4.4 Granular Structure for (I(2U),c) -- 5 Connections of Rough Sets and Interval Sets -- 6 Conclusions -- References -- Generalized Rough Sets -- Empirical Risk Minimization for Variable Consistency Dominance-Based Rough Set Approach -- 1 Introduction -- 2 Variable Consistency Dominance-Based Rough Set Approach -- 3 Empirical Risk Minimization -- 4 Concluding Remarks -- References -- Rough Set Approximations in Multi-scale Interval Information Systems -- 1 Introduction -- 2 Interval Information Systems -- 2.1 Information Systems -- 2.2 Interval Information Systems -- 3 Multi-scale Interval Information Systems -- 3.1 Multi-scale Information Systems -- 3.2 Multi-scale Interval Information Systems -- 4 Rough Set Approximations -- 5 Conclusion -- References -- A New Subsystem-Based Definition of Generalized Rough Set Model -- 1 Introduction -- 2 Preliminaries -- 3 A New Subsystem-Based Definition of Generalized Rough Set Model -- 4 Conclusion -- References -- A Comparison of Two Types of Covering-Based Rough Sets Through the Complement of Coverings -- 1 Introduction -- 2 Preliminaries -- 3 Relationships Between FL, FH and SL, SH Through the Complement of Coverings -- 3.1 Complementary Neighborhood -- 3.2 The Complement of a Covering and Relationships between the Two Types of Covering-Based Rough Sets -- 3.3 Conditions Under Which FH and SH Are Identical -- 4 Extension of a Covering -- 5 Matroidal Approach and the Exact Sets -- 6 Conclusions -- References -- On the Nearness Measures of Near Sets -- 1 Introduction -- 2 Preliminaries -- 3 Nearness Measures -- 4 Strong Nearness Relations -- 5 Concluding Remarks -- References. , Topological Properties for Approximation Operators in Covering Based Rough Sets -- 1 Introduction -- 2 Preliminaries -- 2.1 Pawlak's Rough Set Approximations -- 2.2 Closures -- 2.3 Covering Based Rough Sets -- 2.4 Other Framework of Lower and Upper Approximations -- 2.5 New Framework of Approximation Operators -- 3 Topological Characterization of Upper Approximations -- 4 Algebraic and Topological Properties -- 5 Conclusions -- References -- Rough Sets and Graphs -- Preclusivity and Simple Graphs -- 1 Introduction -- 2 Preliminary Notions -- 2.1 Graphs -- 2.2 Preclusivity Spaces -- 2.3 Formal Concept Analysis -- 3 Simple Graphs as Preclusivity Spaces -- 3.1 Two Basic Cases -- 4 The Cube of Opposition Generated by the Preclusive Relation -- 5 Conclusion -- References -- Preclusivity and Simple Graphs: The n--cycle and n--path Cases -- 1 Introduction -- 2 Preliminary Notions -- 2.1 Graphs -- 2.2 Preclusivity Spaces -- 2.3 Simple Graphs as Preclusivity Spaces -- 3 The Case of Cn -- 4 The Case of Pn -- 5 Conclusion -- References -- Connectedness of Graph and Matroid by Covering-Based Rough Sets -- 1 Introduction -- 2 Basic Definitions -- 2.1 Rough Set -- 2.2 Matroid -- 2.3 Graph -- 3 Covering Induced by Graph -- 4 The Connectedness of Matroid Induced by Covering -- 5 Conclusions -- References -- Controllability in Directed Complex Networks: Granular Computing Perspective -- 1 Introduction -- 2 Definitions -- 2.1 Controllability of Complex Networks Based on the Linear System -- 2.2 Granular Computing -- 3 The Techniques to Enhance Controllability of Directed Complex Networks Based on GrC -- 4 Examples -- 5 Conclusions and Future Work -- References -- Rough and Fuzzy Hybridization -- Dynamic Maintenance of Rough Fuzzy Approximations with the Variation of Objects and Attributes -- 1 Introduction -- 2 Preliminaries. , 3 Matrix Representation of the Lower and Upper Approximations in the FDS -- 4 Dynamically Maintenance of Approximations in the FDS Under the Variation of Attributes and Objects -- 5 An Illustrative Example -- 6 Conclusions -- References -- Semi-Supervised Fuzzy-Rough Feature Selection -- 1 Introduction -- 2 Rough and Fuzzy-Rough Set Theory -- 3 Semi-Supervised Fuzzy-Rough Feature Selection -- 4 Experimental Evaluation -- 4.1 Experimental Setup -- 4.2 Results -- 5 Conclusion -- References -- Modified Generalised Fuzzy Petri Nets for Rule-Based Systems -- 1 Introduction -- 2 Preliminaries -- 2.1 Triangular Norms -- 2.2 Fuzzy Implications -- 3 Generalised Fuzzy Petri Nets -- 4 Modified Generalised Fuzzy Petri Nets -- 5 Example -- 6 Concluding Remarks -- References -- Fuzzy Rough Decision Trees for Multi-label Classification -- 1 Introduction -- 2 Related Works -- 2.1 Multi-label Decision Trees -- 2.2 Multi-label Feature Evaluation with Fuzzy Rough Sets -- 3 Multi-label Fuzzy Rough Decision Trees -- 4 Experiments -- 4.1 A Toy Example -- 4.2 Numerical Experiments -- 4.3 Experiment Results -- 5 Conclusions -- References -- Axiomatic Characterizations of Reflexive and T-Transitive I-Intuitionistic Fuzzy Rough Approximation Operators -- 1 Introduction -- 2 Preliminaries -- 2.1 Intuitionistic Fuzzy Logical Operators -- 2.2 Intuitionistic Fuzzy Sets -- 3 Constructive Definitions of I-Intuitionistic Fuzzy Rough Approximation Operators -- 4 Axioms of I-Intuitionistic Fuzzy Rough Approximation Operators -- 5 Conclusion -- References -- Granular Computing -- Knowledge Supported Refinements for Rough Granular Computing: A Case of Life Insurance Industry -- Abstract -- 1 Introduction -- 2 Preliminary -- 2.1 Rough Set Approach (RSA) and Extended Applications -- 2.2 DEMATEL-Based ANP (DANP) Method -- 3 Research Approach. , 3.1 Dominance-Based Rough Set Approach (DRSA) -- 3.2 DEMATEL-Based ANP Method (DANP) -- 3.3 Suggested Steps for the Proposed Approach -- 4 Empirical Case of Life Insurance Industry in Taiwan -- 4.1 Data -- 4.2 Knowledge-Supported Refinements of Approximation Spaces -- 5 Conclusion and Remarks -- References -- Building Granular Systems - from Concepts to Applications -- 1 Introduction -- 2 Information Granulation -- 3 Models of Granules -- 4 Models of Computing with Granules -- 5 Evaluation of Granular Systems -- 6 Conclusions -- References -- The Rough Granular Approach to Classifier Synthesis by Means of SVM -- 1 Introduction -- 1.1 Motivation -- 1.2 Methodology -- 1.3 Granulation in Rough Mereology -- 1.4 Support Vector Machine Classifier -- 2 Optimized Concept Dependent -Granulation -- 3 Experimental Session -- 3.1 Results of Experiments -- 4 Conclusions -- References -- Data Mining and Machine Learning -- The Boosting and Bootstrap Ensemble for Classifiers Based on Weak Rough Inclusions -- 1 Introduction -- 1.1 Theoretical Background of Our Classifiers -- 2 8_v1.1-8_v1.5 Classifiers -- 3 Classifiers Stabilisation Methods -- 3.1 Bootstrap Ensembles -- 3.2 Boosting Based on Arcing -- 3.3 Boosting Based on Ada-Boost with Monte Carlo Split -- 4 Experimental Session -- 4.1 The Results of Experiments -- 5 Conclusions -- References -- Extraction of Off-Line Handwritten Characters Based on a Soft K-Segments for Principal Curves -- 1 Introduction -- 2 A Soft K-segments Algorithm for Principal Curves -- 2.1 Principal Curves -- 2.2 A Soft K-segments Algorithm for Principal Curves -- 3 Structural Extraction of Off-Line Handwritten Characters Based on a Soft K-segments Principal Curves -- 4 Conclusions -- References -- A Knowledge Acquisition Model Based on Formal Concept Analysis in Complex Information Systems -- 1 Introduction -- 2 Basic Notions of FCA. , 3 Classification Analysis in Domain of Attribute Based On GrC.