Hedge Algebra Based Type-2 Fuzzy Logic System and its Application to Predict Survival Time of Myeloma Patients

2009 International Conference on Knowledge and Systems Engineering ◽

10.1109/kse.2009.22 ◽

2009 ◽

Author(s):

Phan Anh Phong ◽

Dinh Khac Dong ◽

Tran Dinh Khang

Keyword(s):

Fuzzy Logic ◽

Survival Time ◽

Fuzzy Logic System ◽

Logic System

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A New Interval Type-2 Fuzzy Logic System Under Dynamic Environment: Application to Financial Investment

SSRN Electronic Journal ◽

10.2139/ssrn.3532096 ◽

2020 ◽

Author(s):

Akihiko Takahashi ◽

Soichiro Takahashi

Keyword(s):

Fuzzy Logic ◽

Dynamic Environment ◽

Fuzzy Logic System ◽

Financial Investment ◽

Interval Type ◽

Logic System

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A new interval type-2 fuzzy logic system under dynamic environment: Application to financial investment

Engineering Applications of Artificial Intelligence ◽

10.1016/j.engappai.2021.104154 ◽

2021 ◽

Vol 100 ◽

pp. 104154

Author(s):

Akihiko Takahashi ◽

Soichiro Takahashi

Keyword(s):

Fuzzy Logic ◽

Dynamic Environment ◽

Fuzzy Logic System ◽

Financial Investment ◽

Interval Type ◽

Logic System

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Identification of continuous stirred tank reactor based on PCA-interval type-2 fuzzy logic system method

Procedia Computer Science ◽

10.1016/j.procs.2021.02.053 ◽

2021 ◽

Vol 183 ◽

pp. 230-236

Author(s):

Zhengmei Zhao ◽

Jun Li

Keyword(s):

Fuzzy Logic ◽

Fuzzy Logic System ◽

Stirred Tank ◽

Continuous Stirred Tank Reactor ◽

Tank Reactor ◽

System Method ◽

Continuous Stirred Tank ◽

Interval Type ◽

Logic System

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An attempt to use a type-2 fuzzy logic system to assist with real estate appraisals

2008 1st International Conference on Information Technology ◽

10.1109/inftech.2008.4621620 ◽

2008 ◽

Cited By ~ 2

Author(s):

Michal Sygnowski ◽

Bogdan Trawinski ◽

Aleksander Zgrzywa

Keyword(s):

Fuzzy Logic ◽

Real Estate ◽

Fuzzy Logic System ◽

Logic System

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Diagnosing of Risk State in Subsystems of CNC Turning Center using Interval Type-2 Fuzzy Logic System with Semi Elliptic Membership Functions

International Journal of Fuzzy Systems ◽

10.1007/s40815-021-01172-0 ◽

2021 ◽

Author(s):

K. B. Badri Narayanan ◽

M. Sreekumar

Keyword(s):

Fuzzy Logic ◽

Fuzzy Logic System ◽

Membership Functions ◽

Cnc Turning ◽

Turning Center ◽

Interval Type ◽

Logic System

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Detection and classification of multiple power signal patterns with Volterra series and interval type-2 fuzzy logic system

Protection and Control of Modern Power Systems ◽

10.1186/s41601-017-0039-z ◽

2017 ◽

Vol 2 (1) ◽

Cited By ~ 3

Author(s):

Rahul ◽

Rajiv Kapoor ◽

M. M. Tripathi

Keyword(s):

Fuzzy Logic ◽

Volterra Series ◽

Fuzzy Logic System ◽

Multiple Power ◽

Interval Type ◽

Logic System

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An optimal design for type–2 fuzzy logic system using hybrid of chaos firefly algorithm and genetic algorithm and its application to sea level prediction

Journal of Intelligent & Fuzzy Systems ◽

10.3233/ifs-131101 ◽

2014 ◽

Vol 27 (3) ◽

pp. 1335-1346 ◽

Cited By ~ 12

Author(s):

Nguyen Cong Long ◽

Phayung Meesad

Keyword(s):

Genetic Algorithm ◽

Fuzzy Logic ◽

Optimal Design ◽

Sea Level ◽

Firefly Algorithm ◽

Fuzzy Logic System ◽

Logic System

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Interval type-2 fuzzy logic system for the double tank water level control system

2017 9th International Conference on Modelling, Identification and Control (ICMIC) ◽

10.1109/icmic.2017.8321608 ◽

2017 ◽

Author(s):

Wen Zhang ◽

Ruisheng Sun

Keyword(s):

Fuzzy Logic ◽

Control System ◽

Water Level ◽

Fuzzy Logic System ◽

Level Control ◽

Level Control System ◽

Interval Type ◽

Tank Water ◽

Logic System

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Fault Detection Method based on Auto-associative Kernel Regression and Interval Type-2 Fuzzy Logic System for Multivariate Process

2021 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) ◽

10.1109/fuzz45933.2021.9494486 ◽

2021 ◽

Author(s):

Seunghwan Jung ◽

Minseok Kim ◽

Joungguen Kim ◽

Sungshin Kim

Keyword(s):

Fuzzy Logic ◽

Fault Detection ◽

Detection Method ◽

Kernel Regression ◽

Fuzzy Logic System ◽

Multivariate Process ◽

Interval Type ◽

Logic System

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Learning Rules for Type-2 Fuzzy Logic System in the Control of DeNOx Filter

Artificial Intelligence and Soft Computing - Lecture Notes in Computer Science ◽

10.1007/978-3-319-19324-3_17 ◽

2015 ◽

pp. 184-194

Author(s):

Marcin Kacprowicz ◽

Adam Niewiadomski ◽

Krzysztof Renkas

Keyword(s):

Fuzzy Logic ◽

Fuzzy Logic System ◽

Learning Rules ◽

Logic System

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