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An adaptive neuro fuzzy inference system for prediction of anxiety of students
2016 Eighth International Conference on Advanced Computational Intelligence (ICACI), 2016In this paper authors propose design methodology and application of Adaptive Neuro-Fuzzy Inference System (ANFIS) in prediction of anxiety of students using hybrid learning algorithm to improve the prediction based on the conventional model using questioner.
Satwanti Devi +2 more
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Improved adaptive neuro-fuzzy inference system
Neural Computing and Applications, 2011This paper introduces a new type of Adaptive Neuro-fuzzy System, denoted as IANFIS (Improved Adaptive Neuro-fuszzy Inference System). The new structure is realized by the insertion of the error of training of ANFIS in the third layer of this system. The recurrence of the error of training will increase the capability of convergence and the robustness ...
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Adaptive Neuro-Fuzzy Inference System for Classification of Texts
2018In this work, we applied Adaptive Neuro-Fuzzy Inference System to three different classification problems: (1) sentence-level subjectivity detection, (2) sentiment analysis of texts, and (3) detecting user intention in natural language call routing system.
Kamil R. Aida-zade +3 more
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Self-adaptive neuro-fuzzy inference systems for classification applications
IEEE Transactions on Fuzzy Systems, 2002This paper presents a self-adaptive neuro-fuzzy inference system (SANFIS) that is capable of self-adapting and self-organizing its internal structure to acquire a parsimonious rule-base for interpreting the embedded knowledge of a system from the given training data set.
Jeen-Shing Wang, C. S. George Lee
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Seizure prediction using adaptive neuro-fuzzy inference system
2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2013In this study, we present a neuro-fuzzy approach of seizure prediction from invasive Electroencephalogram (EEG) by applying adaptive neuro-fuzzy inference system (ANFIS). Three nonlinear seizure predictive features were extracted from a patient's data obtained from the European Epilepsy Database, one of the most comprehensive EEG database for epilepsy ...
Ahmed Fazle Rabbi +2 more
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Adaptive neuro fuzzy inference system for vessel position forecasting
2017 International Conference on Engineering, Technology and Innovation (ICE/ITMC), 2017In this work, we present a novel approach for short-term vessel movement predictions in real world maritime conditions, based on an Adaptive Neuro Fuzzy Inference System. The proposed system uses real world vessel position recordings, reported by the Automatic Identification System and is capable of highly accurate future vessel position forecasting ...
Elias K. Xidias, Dimitrios Zissis
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Adaptive Neuro-Fuzzy Inference System for Controlling a Steam Valve
2019 IEEE 9th International Conference on System Engineering and Technology (ICSET), 2019Controlling a steam valve can be considered as a sensitive subject. It can restrict the allowance of steam through a specific controllable valve or gate. Steam valves are utilized in many steam systems such as electrical generation stations, ironing systems and heating systems.
Moatasem Yaseen Al-Ridha +2 more
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Adaptive Neuro-Fuzzy Inference System For Analysis of Doppler Signals
2006 International Conference of the IEEE Engineering in Medicine and Biology Society, 2006In this study, a new approach based on adaptive neuro-fuzzy inference system (ANFIS) was presented for detection of ophthalmic artery stenosis. Decision making was performed in two stages: feature extraction using the wavelet transform (WT) and the ANFIS trained with the backpropagation gradient descent method in combination with the least squares ...
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An adaptive neuro-fuzzy inference system for bridge risk assessment
Expert Systems with Applications, 2008Bridge risks are often evaluated periodically so that the bridges with high risks can be maintained timely. This paper develops an adaptive neuro-fuzzy system (ANFIS) using 506 bridge maintenance projects for bridge risk assessment, which can help Highways Agency to determine the maintenance priority ranking of bridge structures more systematically ...
Ying-Ming Wang 0001, Taha M. S. Elhag
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Analog VLSI implementation of adaptive neuro-fuzzy inference systems
ICECS 2000. 7th IEEE International Conference on Electronics, Circuits and Systems (Cat. No.00EX445), 2002This paper presents an analog VLSI implementation of adaptive neuro-fuzzy inference systems (ANFIS). Stochastic perturbative techniques, which are more VLSI friendly than standard learning techniques such as back-propagation, are used for on-chip learning. The system is tested by the task of predicting the Mackey-Glass chaotic time series.
Ahmed Sultan, Mohamed El-Sayed
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