sparse fuzzy rule-bases
TSK Inference with Sparse Rule Bases
... uses fuzzy logic and fuzzy set theory to map inputs to ...typical fuzzy inference system consists of mainly two parts, a rule base (or knowledge base) and an inference ...Mamdani fuzzy ...
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Curvature-Based Sparse Rule Base Generation for Fuzzy Rule Interpolation
... Fuzzy rule base generation has been intensively studied in the ...Data-driven rule base generation was proposed to minimise the involvement of human ex- ...dense rule bases that are ...
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Rough-fuzzy rule interpolation
... Fuzzy rule interpolation forms an important approach for performing inference with sys- tems comprising sparse rule ...rules, fuzzy rule interpolation may still derive a use- ful ...
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Fuzzy rule interpolation and extrapolation techniques: Criteria and evaluation guidelines
... analyzes Fuzzy Rule In- terpolation and extrapolation Techniques ...of fuzzy rule interpolation, we treat them both as approximation techniques designed to be applied where sparse or ...
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An Extended Takagi-Sugeno-Kang Inference System (TSK+) with Fuzzy Interpolation and Its Rule Base Generation
... A rule base covering the entire input domain is required for the conventional Mamdani inference and Takagi–Sugeno–Kang (TSK) ...inference. Fuzzy interpola- tion enhances conventional fuzzy ...
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Curvature-based sparse rule base generation for fuzzy rule interpolation
... fuzzy rule base is usually generated in two ...a fuzzy rule base is traditionally built upon human expertise, which greatly limits the system modelling as experts may not always be ...
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Quaternion Neuro-Fuzzy Learning Algorithm for Fuzzy Rule Generation
... tuning fuzzy rules and its parameters by back propagation learning algorithm of neural networks ...each fuzzy inference rule under the simplified fuzzy inference method, can generate ...
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Compositional Rule of Inference and Adaptive Fuzzy Rule Based Scheme with Applications
... analysis fuzzy inference scheme dominates over classical two-valued ...a fuzzy inference scheme, linguistic variables are used in observation and effect parts to get a ...Adaptive fuzzy rule ...
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Genetic fuzzy rule-based system using MOGUL learning methodology for energy consumption forecasting
... Genetic fuzzy rule- based systems Under the iterative rule Learning approach (MOGUL) to forecast energy ...Neural Fuzzy Interface System (HyFIS) and Wang and Mendel’s Fuzzy Rule ...
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Fuzzy Association Rule by Classification Technique
... the fuzzy association rule then it is difficult to find the minimum frequency because of distinct fuzzy values of data ...put fuzzy values to different classes and the no of classes act as ...
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Adaptive Neuro-Fuzzy Systems
... linguistic fuzzy rules, which is common to all neuro-fuzzy ...a fuzzy model can become limited with too many fuzzy ...the fuzzy rule ...
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IMPROVED CLUSTER HEAD SELECTION USING FUZZY LOGIC IN WIRELESS SENSOR NETWORKS
... perform. Fuzzy Logic offers several unique features that make it a particularly good alternative for many control ...of fuzzy logic control consists of a fuzzifier, fuzzy rules, fuzzy ...
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RЀNYI ENTROPY FOR MIXTURE MODEL OF ULTIVARIATE SKEW NORMAL CAUCHY DISTRIBUTIONS
... a rule no 8, rules {P8 P10 P13 P18} have support ...association rule theory by Agrawal [1], it is mean: if the students have a good skill in writing, Active Learning, Social Perceptiveness, they must be ...
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Software Quality Prediction using Fuzzy Rule based System
... a fuzzy rule based system and an ordinary multiple ...applying fuzzy logic is smaller than MMRE applying multiple regression; while the value of Pred ...applying fuzzy logic is higher than ...
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Generalized Adaptive Fuzzy Rule Interpolation
... to fuzzy rule interpo- lation that works based on two neighbouring rules flanking an observation, adaptive fuzzy rule interpolation is able to restore system consistency when contradictory ...
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Islanding Detection In Distributed Generation By Using Fuzzy Rule Based
... a fuzzy rule-based classifier using features for islanding detection in distributed ...the fuzzy are developed and the corresponding rule base is formulated for islanding ...the fuzzy ...
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Download Download PDF
... simplified fuzzy control algorithm (SFCA) which they developed, in a purely fuzzy logic setting, could make the rule-based paradigm to possess the computational efficiency and trainable capability ...
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Comparative Analysis Of Fuzzy Association Rule Mining Algorithms
... the fuzzy rules learning algorithm after developed in ...for fuzzy rule ...control rule learning (regression ...complete rule in the each iteration ...
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NODE RECOVERY IN WIRELESS SENSOR NETWORK USING GENETIC ALGORITHM AND FUZZY LOGIC
... Abstract: Wireless Sensor Network (WSN) is an emerging technology for data transfer through a number of sensor nodes. The goal of the sensor node is to collect the data at regular intervals and transfer data to the ...
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Development Of Control System For Solar Plant Using Genetic Fuzzy PID Techniques
... optimal fuzzy Proportional Integral-Derivative (PID) controller for a solar power ...The fuzzy PID controller is a discrete-time version of the conventional PID controller, which preserves the same linear ...
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