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FANCFIS: Fast adaptive neuro-complex fuzzy inference system
International Journal of Approximate Reasoning, 2019zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Omolbanin Yazdanbakhsh, Scott Dick
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Adaptive Neuro-Fuzzy Inference System in Agriculture
2020This chapter emphasizes the use of adaptive fuzzy inference system (ANFIS) in agriculture. An overview of the basic concepts of ANFIS is provided at the beginning, where the underlying architecture of ANFIS is also discussed. The introduction is followed by the second section which highlights the diverse applications of ANFIS in agriculture during ...
K. Aditya Shastry, null Sanjay H. A.
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Nonlinear system modeling with dynamic adaptive neuro-fuzzy inference system
2014 IEEE International Symposium on Innovations in Intelligent Systems and Applications (INISTA) Proceedings, 2014This paper introduces the architecture and learning procedure of dynamic adaptive neuro-fuzzy inference system (DANFIS) for nonlinear dynamical system modeling. In our DANIS model, IF part of the rules are comprised of Gaussian type membership functions and THEN part of the rules are differential equations of linear functions.
Sevcan Yilmaz, Yusuf Oysal
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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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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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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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Glaucoma detection using adaptive neuro-fuzzy inference system
Expert Systems With Applications, 2007Abstract Purpose. To develop an automated classifier based on adaptive neuro-fuzzy inference system (ANFIS) to differentiate between normal and glaucomatous eyes from the quantitative assessment of summary data reports of the Stratus optical coherence tomography (OCT) in Taiwan Chinese population. Methods.
Mei-Ling Huang
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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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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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