inference system
An Application of Fuzzy Inference System Composed of Double-Input Rule Modules to Control Problems
... M ANY studies on self-tuning fuzzy systems[1], [2] have been made. The aim of these studies is to construct automatically fuzzy reasoning rules from input and output data based on the steepest descend method. Obvious ...
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Adaptive Neuro-Fuzzy Inference System Approach for the Automatic Screening of Diabetic Retinopathy in Fundus Images
... fuzzy inference system to track the given input/output data (Jang et ...logic system to distinguish between normal and abnormal eyes (Huang et ...Fuzzy Inference Systems is used in the ...
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Open Modelagem de um adaptive neuro fuzzy inference system para análise de risco em projetos.
... Neuro-fuzzy Inference System (ANFIS), which is capable of aggregating the mathematical treatment capacity of conceptual models with a hybrid learning ...
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A FUZZY INFERENCE SYSTEM FOR ASSESSMENT OF THE SEVERITY OF THE PEPTIC ULCERS
... fuzzy inference system is a rule-based system that uses fuzzy logic, rather than Boolean logic, to reason about ...an inference engine that applies a fuzzy reasoning mechanism to obtain a ...
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Adaptive Neuro-Fuzzy Inference System Applied QSAR with Quantum Chemical Descriptors for Predicting Radical Scavenging Activities of Carotenoids.
... Linear regression method is usually applied to develop QSAR models in several studies [13,15–17,26]; however, the interaction effect between independent variables and nonlinear relationships could not be interpreted ...
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Momentum Analysis based Stock Market Prediction using Adaptive Neuro-Fuzzy Inference System (ANFIS)
... Fuzzy Inference System (ANFIS) introduced by ...fuzzy inference system used in ANFIS and it is composed of four functional ...the inference into a crisp ...
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An improved fuzzy inference system for voltage/VAR control
... HIS paper describes a new architecture for a DMS module aiming at Voltage/Var regulation in networks with a diversity of possible control devices. This architecture is based on the articulation of cascading fuzzy ...
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APPLICATION OF ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM IN INTEREST RATES EFFECTS ON STOCK RETURNS
... In the current study we examine the effects of interest rate changes on common stock returns of Greek banking sector. We examine the Generalized Autoregressive Heteroskedasticity (GARCH) process and an Adaptive ...
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PHONETIC CLASSIFICATION BY ADAPTIVE NETWORK BASED FUZZY INFERENCE SYSTEM AND SUBTRACTIVE CLUSTERING
... on speech recognition. The primary tasks of fuzzy modeling are structure identification and parameter optimization, the former determines the numbers of membership functions and fuzzy if-then rules while the latter ...
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USING AN INTEGRATED FUZZY INFERENCE SYSTEM AND ARTIFICIAL NEURAL NETWORK TO FORECAST DAILY DISCHARGE
... (7) With the classification results from the previous procedure, the forecast outflow discharge was found by fuzzy inference. The model was named Gauss. Fuzzy inference w[r] ...
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FUZZY INFERENCE SYSTEM BASED POWER FACTOR CORRECTION OF THREE PHASE DIODE RECTIFIER USING FIELD PROGRAMABLE GATE ARRAY
... The fuzzy logic controller based simulation diagram of three phase diode rectifier with bi directional switch is shown in Fig.. The input current waveform and THD of[r] ...
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Shop Inference System Using Location Data and Bayesian Network
... I N recent years, real world user status and behaviour have been a focus of attention in marketing and product recommendations [1][2]. User status, inferred from the loca- tion data of mobile and smart phones equipped ...
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Resolution reasoning by RDF Clausal Form Logic
... of inference, managing and finding interrelations between knowledge objects than that an approach based on OWL ...Richard’s inference system of the Clausal Form Logic (CFL) based on the formal ...
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Approximation Capabilities of Interpretable Fuzzy Inference Systems
... become popular [7], [12]. However, there are little studies on effective learning methods of fuzzy inference systems satisfying with interpretability and accuracy. It is desired to develop effective fuzzy systems ...
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Combination of Neural Networks and Fuzzy Clustering Algorithm to Evalution Training Simulation-Based Training
... At first, a fuzzy inference system based on the existing database defined using Takagi-Sugeno-Kang. Using FCM, fuzzy set of rules for modeling the behavior of the database is extracted. The number of fuzzy ...
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Classification techniques on computerized systems to predict and/or to detect Apnea: A systematic review
... Recognition System; ANN, Artificial Neural Network; ANFIS, Adap- tive Neuro-Fuzzy Inference System; AUC, Area Under receiver operating characteris- tic Curve; BHC, Binary Hierarchical Classification; ...
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MODELAGEM E PROGNOSE DO PREÇO DE CARVÃO USANDO UM SISTEMA NEURO-FUZZY.
... the inference system the Takagi-Sugeno model (JANG, 1995) was ...The system used for the ANFIS-2 architecture, with two inputs (P-1 e P-2) and nine rules (R1 a R9), can be represented as (HEDDAM et ...
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Sistema genético difuso para a predição da frequência respiratória de pintinhos sujeitos a desafios térmicos
... Fuzzy Inference System and a Genetic Fuzzy Rule Based ...Fuzzy Inference System was structured based on two input variables: duration of thermal exposure (in days) and dry bulb temperature ...
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J. Braz. Chem. Soc. vol.22 número8
... Food contaminations by migration of low molecular weight additives into foodstuffs can result from direct contact between packaging materials and food. The amount of migration is related to the structural properties of ...
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Data-driven inference for the spatial scan statistic
... usual inference test of the spatial scan statistic, incorporating additional information about the size of the most likely cluster ...modified inference question: what is the probability that the null ...
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