fuzzy inference rule
Design of Host based Intrusion Detection System using Fuzzy Inference Rule
... For testing phase, a test data from the testing data is given to the Mamdami fuzzy inference system. It compares the input variable with the membership functions on the premises part to obtain the ...
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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 ...
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An Application of Fuzzy Inference System Composed of Double-Input Rule Modules to Control Problems
... 1) Obstacle avoidance: From (operation) data given by an examinee to avoid obstacle, fuzzy inference rule for each model is constructed. As shown in Fig.3, the distance d and the angle θ between ...
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Application of the Fuzzy Inference System Method to Predict the Number of Weaving Fabric Production
... From the calculation data of the production of Mlaki Wanarejan Utara Pemalang woven fabric according to Tsukamoto's method in March 2017 using Weka's rule obtained 343 woven fabrics in meters, while using the ...
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Design of PID, Fuzzy PD/PID and Single Input Fuzzy Logic Controller for Higher Order System
... input fuzzy controller, 3,5,7,9 or 11 membership functions for each input are mostly used ...two fuzzy membership functions are used for the two inputs error e and derivative of error(ė) as shown in ...
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Generating Classification Rules from Training Samples
... using fuzzy membership ...a rule base and classified samples from the training ...using fuzzy membership functions is a valid approach to generate a rule set that can be used develop a FIS for ...
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Rainfall-runoff modelling of a watershed
... In this study an adaptive neuro-fuzzy inference system was used for rainfall-runoff modelling for the Nagwan watershed in the Hazaribagh District of Jharkhand, India. Different combinations of rainfall and ...
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Online Full Text
... Abstract—Efficient methods for detecting oil production abnormalities have been active research area in recent years. This paper presents an hybrid approach towards the detection of oil production abnormalities using ...
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An Optimal Fuzzy Logic Guidance Law using Particle Swarm Optimization
... based fuzzy MFs optimizing method is also introduced to a fixed point control problem, ...automatic fuzzy MFs optimizing, most of them are in the area of TS type of fuzzy ...of fuzzy ...
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ASSOCIATION RULE MINING BASED VIDEO CLASSIFIER WITH LATE ACCEPTANCE HILL CLIMBING APPROACH
... network, fuzzy system model, measure theory, mathematics morphology and many other ...uninorm fuzzy logic UL , which is Multiplicative additive intuitionistic linear logic MAILL extended with the ...
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A Fuzzy Logic Based Trading System
... of fuzzy systems with neural networks and/or genetic algorithms appear to be popular in real-world ...of fuzzy and probabilistic systems have also been ...probabilistic fuzzy model [10], in which ...
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ABSTRACT:- A review paper on the various VLSI architectures of fuzzy logic based processors and
... of fuzzy logic, as it is he who has given the concept around four decades ...the fuzzy logic has been used in numerous applications and in every domain of science and ...The fuzzy logic has been ...
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Crowdsourcing Inference Rule Evaluation
... semantic inference annotation (Snow et ...for inference rules that takes advantage of ...of rule applications and avoids annotator training ...
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An efficient parallel algorithm for haplotype inference based on rule based approach and consensus methods.
... Haplotype Inference based on Consensus Method proposed by Orzack and Gusfield in [Orzack ...Clark’s Inference rule, on the number of accurately inferred genotypes, and secondly to explore better ways ...
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Survey of fuzzy inference model and impact on QOS parameters using adaptive neuro fuzzy inference system in MANET
... proposed Fuzzy logic control method to improve the performance and reliability of the multicast routing protocols in ...nodes. Fuzzy logic is proposed to distinguish the strong and weak nodes in the ...
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Fuzzy inference systems implemented on neural architectures for motor fault detection and diagnosis
... Different NN structures have proven to be successful in solving the motor fault detection/diagnosis problem [1], [15], [23]–[25]. Following the techniques developed for general process fault detection/diagnosis [5]–[8], ...
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Rule Based Temporal Inference
... Time-wise knowledge is relevant in knowledge graphs as the majority facts are true in some time period, for instance, (Barack Obama, president of, USA, 2009, 2017). Consequently, temporal information extraction and ...
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Minimum Scoring Rule Inference
... scoring rule that is strictly local in the above sense (Bernardo, ...scoring rule is a linear combination of the log score and what they term a key local scoring rule, which they have ...scoring ...
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Evaluation of Enterprise Performance Based on FLI-GA Model
... is fuzzy logic inference method (Rustum, Omar & Emad, ...2009). Fuzzy logic inference method can reflect the expert’s correct judgment, so as to avoid difficulties of giving weights ...
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Image Enhancement using Hybrid Fuzzy Inference System (IEHFS)
... hybrid Fuzzy inference system is applied by taking a movable window over the image of 5 x 5 size, where the pixels around the center pixel are named according to the direction to identify ...the ...
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