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On the Power of Fuzzy Markup Language 2013 ed. [Kõva köide]

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  • Formaat: Hardback, 188 pages, kõrgus x laius: 235x155 mm, kaal: 483 g, XX, 188 p., 1 Hardback
  • Sari: Studies in Fuzziness and Soft Computing 296
  • Ilmumisaeg: 14-Dec-2012
  • Kirjastus: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • ISBN-10: 3642354874
  • ISBN-13: 9783642354878
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On the Power of Fuzzy Markup Language 2013 ed.Suurem pilt
  • Formaat: Hardback, 188 pages, kõrgus x laius: 235x155 mm, kaal: 483 g, XX, 188 p., 1 Hardback
  • Sari: Studies in Fuzziness and Soft Computing 296
  • Ilmumisaeg: 14-Dec-2012
  • Kirjastus: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • ISBN-10: 3642354874
  • ISBN-13: 9783642354878
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9783642354878.html
Märksõnad:
This book provides an open-source framework that allows designers to program a fuzzy controller by using the Fuzzy Markup Language approach.

One of the most successful methodology that arose from the worldwide diffusion of Fuzzy Logic is Fuzzy Control. After the first attempts dated in the seventies, this methodology has been widely exploited for controlling many industrial components and systems. At the same time, and very independently from Fuzzy Logic or Fuzzy Control, the birth of the Web has impacted upon almost all aspects of computing discipline. Evolution of Web, Web2.0 and Web 3.0 has been making scenarios of ubiquitous computing much more feasible; consequently information technology has been thoroughly integrated into everyday objects and activities.What happens when Fuzzy Logic meets Web technology? Interesting results might come out, as you will discover in this book. Fuzzy Mark-up Language is a son of this synergistic view, where some technological issues of Web are re-interpreted taking into account the transparent notion of Fuzzy Control, as discussed here. The concept of a Fuzzy Control that is conceived and modeled in terms of a native web wisdom represents another step towards the last picture of Pervasive Web Intelligence.
Part I Fuzzy Markup Language - Fundamentals
On the Need of a Standard Language for Designing Fuzzy Systems
3(14)
Bruno N. Di Stefano
1 Introduction
3(3)
2 The Importance of the Documentation for the Design of Interoperable Programmable Controllers
6(1)
3 A First Attempt for a Fuzzy Language: IEC 61131-7
7(4)
4 Fuzzy Markup Language: A Novel Proposal for a Standard Fuzzy Systems Language
11(3)
5 Conclusion
14(3)
References
14(3)
Fuzzy Markup Language: A XML Based Language for Enabling Full Interoperability in Fuzzy Systems Design
17(16)
Giovanni Acampora
1 Introduction
17(2)
2 Fuzzy Markup Language: The Grammar and Stylesheet Translators
19(8)
2.1 FML Syntax: XML Tags and Attributes
19(5)
2.2 Describing the FML Grammar through XML Schema
24(3)
2.3 FML Synthesis: XSLT Documents
27(1)
3 An Extension of FML: Type 2 FML
27(2)
4 Conclusions
29(4)
References
30(3)
Distributing Fuzzy Reasoning through Fuzzy Markup Language: An Application to Ambient Intelligence
33(18)
Giovanni Acampora
Vincenzo Loia
Autilia Vitiello
1 Introduction
33(2)
2 FML and Its Distributive Features
35(3)
3 FML-Based Mobile Agents
38(4)
3.1 Migration in Multi-agent Systems
38(1)
3.2 A Multi-agent Framework for Distributing FML Programs
39(3)
4 Applying Multi-agent FML to Ambient Intelligence
42(5)
4.1 Learning Mode
43(3)
4.2 Control Model
46(1)
5 Simulation and Experimental Results
47(2)
6 Conclusions
49(2)
References
49(2)
An Enhanced Visual Environment for Designing, Testing and Developing FML-Based Fuzzy Systems
51(22)
Giovanni Acampora
Vincenzo Loia
Autilia Vitiello
1 Introduction
51(2)
2 A Novel Vision of a Fuzzy Controller: FLC Labeled Tree
53(6)
3 Visual FML Tool Functionalities
59(10)
3.1 Fuzzy System Description
61(3)
3.2 Systems Verification
64(3)
3.3 Systems Tuning
67(1)
3.4 Systems Synthesis
68(1)
4 Conclusions
69(4)
References
69(4)
Part II Fuzzy Markup Language - Applications
Apply Fuzzy Markup Language to ASAP Assessment System
73(22)
Chang-Shing Lee
Mei-Hui Wang
Pi-Hsia Hung
Yi-Ling Kuo
Hui-Min Wang
Bort-Hung Lin
1 Introduction
74(1)
2 Item Fuzzy Ontology and Fuzzy Markup Language
75(2)
2.1 Item Fuzzy Ontology
75(1)
2.2 Fuzzy Markup Language
76(1)
3 CMMI-Based ASAP Assessment System
77(6)
3.1 Introduction to CMMI
78(1)
3.2 Introduction to ASAP
79(1)
3.3 Structure of CMMI-Based ASAP Assessment System
80(1)
3.4 Subsystem Function Descriptions
81(2)
4 FML-Based Semantic Inference Mechanism
83(6)
4.1 Structure of FML-Based Semantic Inference Mechanism
83(1)
4.2 Natural Language Processing Mechanism
84(1)
4.3 Fuzzy Reasoning Mechanism
85(3)
4.4 Semantic Summary Mechanism
88(1)
5 Simulation Results
89(2)
6 Conclusion
91(4)
References
92(3)
Apply Fuzzy Markup Language to Knowledge Representation for Game of Computer Go
95(18)
Chang-Shing Lee
Mei-Hui Wang
Yu-Jen Chen
Shi-Jim Yen
1 Introduction
95(2)
2 Knowledge Representation for Game of Computer Go
97(4)
2.1 Game Record Ontology
97(1)
2.2 Go Board Ontology
98(3)
3 FML-Based Decision Support Agent
101(5)
3.1 Structure of FML-Based Decision Support Agent
101(1)
3.2 Fuzzy Decision Support System
101(2)
3.3 Territory Partition Mechanism
103(1)
3.4 Fuzzy Inference Mechanism
103(2)
3.5 Alarm Presentation Mechanism
105(1)
4 Experimental Results
106(5)
5 Conclusions
111(2)
References
111(2)
Fuzzy Markup Language for Malware Behavioral Analysis
113(20)
Hsien-De Huang
Giovanni Acampora
Vincenzo Loia
Chang-Shing Lee
Hani Hagras
Mei-Hui Wang
Hung-Yu Kao
Jee-Gong Chang
1 Introduction
114(1)
2 Basic Concepts: Improving TWMAN through FML and OWL
115(4)
2.1 Ontology Web Language (OWL) for Modeling Malwares Domain
115(2)
2.2 Fuzzy Markup Language (FML) as Inference Engine for Malwares Analysis
117(1)
2.3 Taiwan Malware Analysis Net (TWMAN)
118(1)
3 An FML-Based Fuzzy Ontological Model for TWMAN
119(6)
3.1 Integrating OWL and FML for Analyzing Malware Behaviors
120(2)
3.2 Fuzzy Inference Mechanism
122(3)
4 Experimental Results
125(1)
5 Conclusions
126(7)
References
131(2)
Applying FML-Based Fuzzy Ontology to University Assessment
133(16)
Mei-Hui Wang
Chang-Shing Lee
Hani Hagras
Ming-Kai Su
Yu-Yang Tseng
Hui-Min Wang
Yuan-Liang Wang
Che-Hung Liu
1 Introduction
134(1)
2 Structure of University Goal Ontology
135(4)
3 FML-Based University Assessment System
139(2)
3.1 Fuzzy Markup Language
139(1)
3.2 Knowledge Base of University Assessment System
139(1)
3.3 Rule Base of University Assessment System
140(1)
4 Simulation Results
141(5)
5 Conclusions
146(3)
References
147(2)
A Type-2 FML-Based Fuzzy Ontology for Dietary Assessment
149(20)
Mei-Hui Wang
Chang-Shing Lee
Zhi-Wei Chen
Hani Hagras
Su-E Kuo
Hui-Ching Kuo
Hui-Hua Cheng
1 Introduction
149(2)
2 Definition of Fuzzy Ontology
151(5)
2.1 Fuzzy Ontology [ 12]
151(2)
2.2 Type-2 Fuzzy Set
153(3)
2.3 Type-2 Fuzzy Diet Ontology
156(1)
3 Type-2 FML-Based Dietary Assessment System
156(5)
3.1 Structure of the Proposed System
157(1)
3.2 Food Nutrition Facts
158(1)
3.3 Type-2 Fuzzy Inference Mechanism
159(2)
4 Experiments and Results
161(5)
5 Conclusions
166(3)
References
167(2)
A Type-2 FML-Based Meeting Scheduling Support System
169(16)
Chang-Shing Lee
Mei-Hui Wang
Ming-Kai Su
Min-Hsiang Wu
Hani Hagras
1 Introduction
169(2)
2 Type-2 FML-Based Personal Ontology
171(4)
2.1 Type-2 Fuzzy Set
171(1)
2.2 Type-2 FML-Based Personal Ontology
172(1)
2.3 Type-2 FML-Based Meeting Scheduling Ontology
173(2)
3 FML-Based Meeting Scheduling System
175(6)
3.1 Type-2 FML-Based Meeting Scheduling System
175(1)
3.2 Knowledge Base for Type-2 FML-Based Meeting Scheduling System
176(4)
3.3 Fuzzy Inference Mechanism
180(1)
3.4 Sentence Extraction Mechanism
181(1)
4 Experiments and Results
181(3)
5 Conclusions
184(1)
References 185(2)
Author Index 187