Fuzzy Inference Systems (FIS
Fuzzy Inference System for Productivity and Fertility of Soil
... area. Fuzzy logic makes conversion of imprecise information to precise one, consists of capability to design rational decisions containing imperfect ...in Fuzzy systems[1]. Fuzzy ...
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Modelling of sanitary hot water energy consumption using adaptive neuro-fuzzy inference systems
... Neuro-Fuzzy Inference System (ANFIS) [10] learning method, which is a hybrid of Fuzzy Inference Systems (FIS) and back propagated Artificial Neural Networks (ANN), has been ...
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Long-term prediction of discharges in Manwan Hydropower using adaptive-network-based fuzzy inference systems models
... of fuzzy inference involves membership functions, fuzzy logic operators, and if-then ...rules. Fuzzy inference systems (FIS) have been successfully applied in fields such ...
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A Comparison between Fuzzy Inference Systems for Prediction (with Application to Prices of Fund in Egypt)
... the Fuzzy logic techniques, including Mamdani , Sugeno fuzzy inference system models and Adaptive Neuro-Fuzzy Inference System (ANFIS) .... Fuzzy inference systems ...
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Reliability Estimation of Services Oriented Systems Using Adaptive Neuro Fuzzy Inference System
... neuro fuzzy approach for estimating the reliability of service oriented ...proposed FIS and other traditional ...the fuzzy logic toolbox can be used to find the reliability of such system on the ...
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A Comparison of Mamdani and Sugeno Fuzzy Inference Systems for Traffic Flow Prediction
... of FIS, namely Mamdani [13] and Sugeno FISs [14] are widely accepted and applied to many real-world ...the inference result before defuzzification is a fuzzy set ...
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Prediction of Perceptual Quality for Mobile Video Using Fuzzy Inference Systems
... [32]. FIS includes four stages: fuzzifier, rule base, inference engine, and ...defuzzifier. FIS is powered with learned membership functions and a set of fuzzy inference ...
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Localization of Indoor Areas Using Wi-Fi Signals, Type-2 Fuzzy Inference Systems and Data Mining
... In this case there are three clusters of the input data to generate the Mamdani type 2 FIS. In addition, there is the Test option in this example application to obtain three new fresh values of the same APs ...
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A comparison of different fuzzy inference systems for prediction of catch per unit effort (CPUE) of fish
... Mamdani- Fuzzy Inference System (FIS), Sugeno -FIS and Sugeno-Adaptive Neuro- Fuzzy Inference System (ANFIS) model for the prediction of CPUE of ...of fuzzy ...
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An experiment of predicting Total Electron Content (TEC) by fuzzy inference systems
... The training patterns and the FIS parameters are kept fixed afterwards for 5, 10 and 15 min predictions. We make predictions at every 30 s successively following the training data. However, we use the predicted ...
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Metaheuristic tuning of type-II fuzzy inference systems for data mining
... At first phase, the training to FIS was provided using 10- fold cross validation (10-fold CV) method. In a 10 fold CV, a dataset is equally divided into 10 sets and from the portioned sets, one set is chosen for ...
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Multi-agent System for Documents Retrieval and Evaluation Using Fuzzy Inference Systems
... Mamdani-type fuzzy inference system(as already shown in Figure ...Mamdani-type fuzzy inference system, the range of Sugeno- type output is between 0 and ...this FIS, so two linguistic ...
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Robust FIS Implementation of a Fuzzy based DSTATCOM in VCM for Power Quality Enhancement
... Distribution Systems are often suffered by several power quality ...robust Fuzzy Logic, which is an extension of a multi-value ...of fuzzy-logic DSTATCOM functionality is implemented using ...
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Optimization of Hybrid Power Systems Performance Based on Adaptive Neuro-Fuzzy Inference System
... The main role of ANFIS technique is to get the optimum parameters of MFs that lead to generate the appropriate FIS model for the control system. Usually, the adapted parameters lead to change the shape of MFs. ...
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USING FUZZY INFERENCE SYSTEMS TO OPTIMIZE HIGHWAY ALIGNMENTS
... The fuzzy inference process involves all the elements of Membership Functions, Logical Operations, and If-Then ...type FIS rules (Mamdani and Assilian, 1975). Fuzzy inference ...
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REMOTE REAL-TIME INDOOR DEVICE TRACKING BASED ON FUZZY INFERENCE SYSTEM (FIS)
... positioning systems to infer the locations of devices demonstrates their suitability for indoor environments, where conventional methods prove unreliable (Rizos, Roberts, Barnes, & Gambale, ...
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Fuzzy integral for rule aggregation in fuzzy inference systems
... an FIS, which is responsible for combining the output of different rules and deriving a final comprehensive ...Mamdani-Assilian FIS typically uses FS aggrega- tion strategies such as maximum and summation ...
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On the Capability of a Fuzzy Inference System with Improved Interpretability
... In this paper, we will propose a fuzzy inference system with interpretability. Firstly, it is proved that the proposed model is a universal approximator of continuous functions. Further, the capability of ...
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Development of Fuzzy Inference Scheme for LC Oscillator Design
... behaviour. Fuzzy logic is used in system control and analysis design, because it shortens the time for engineering development and sometimes, in the case of highly complex systems, is the economical way to ...
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Symmetric I* Restriction Method of Fuzzy Inference
... of fuzzy logic, fuzzy inference plays a vital role in the fields of fuzzy control, artificial intelligence, affective computing, image processing and so ...of fuzzy inference are ...
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