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Picture inference system: a new fuzzy inference system on picture fuzzy set

Applied Intelligence, 2016
In this paper, we propose a novel fuzzy inference system on picture fuzzy set called picture inference system (PIS) to enhance inference performance of the traditional fuzzy inference system. In PIS, the positive, neutral and negative degrees of the picture fuzzy set are computed using the membership graph that is the combination of three Gaussian ...
Le Hoang Son   +2 more
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Z-Adaptive Fuzzy Inference Systems

2021 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2021
Z-numbers consist of two components, restriction and restriction reliability, to cover both possibilistic and probabilistic uncertainties. So far, the components of Z-numbers are merely determined by expert knowledge and lack automated learning/training.
Fatemeh Rezaee-Ahmadi   +2 more
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Fuzzy Inference System

2019
Liver fibrosis is the natural wound-healing response to parenchymal injury in chronic liver diseases. It may eventually results in liver Cirrhosis (F4) and its various complications (F0–F1, F2, F3). The assessment of liver fibrosis staging is essential for people suffering from chronic liver diseases.
Joey Sing Yee Tan, Amandeep S. Sidhu
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Fuzzy Inference Network with Mamdani Fuzzy Inference System

2018
In the modern era, the amount of data generated is increasing at an exponential rate. The generated data has both numeric as well as linguistic form. Learning or extracting relevant information from these types of data is a major challenge for researchers.
Nishchal K. Verma   +3 more
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Movie Recommendation System Based on Fuzzy Inference System and Adaptive Neuro Fuzzy Inference System

International Journal of Fuzzy System Applications, 2015
One of most prominent features that social networks or e-commerce sites now provide is recommendation of items. However, the recommendation task is challenging as high degree of accuracy is required. This paper analyzes the improvement in recommendation of movies using Fuzzy Inference System (FIS) and Adaptive Neuro Fuzzy Inference System (ANFIS).
Md Mahfuzur Rahman Siddiquee   +2 more
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On Liu’s Inference Rules for Fuzzy Inference Systems

2010
Liu’s inference is a process of deriving consequences from fuzzy knowledge or evidence via the tool of conditional credibility. Using membership functions, this paper derives some expressions of Liu’s inference rule for fuzzy systems. This paper also gives some new inference rules with multiple antecedents and with multiple if-then rules.
Xin Gao, Dan A. Ralescu, Yuan Gao 0021
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A Fuzzy Inference System for Meta-Evaluation

Seventh International Conference on Intelligent Systems Design and Applications (ISDA 2007), 2007
This paper presents a new methodology for meta-evaluation that makes use of fuzzy sets and fuzzy logic concepts. It comprehends a data collection instrument and a hierarchical fuzzy inference system. The advantages of the proposed system are: (i) the instrument, which allows intermediate answers; (ii) the inference process ability to adapt to specific ...
Ana Carolina Letichevsky   +2 more
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A fuzzy inference system for sleep staging

2011 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2011), 2011
In this paper, a fuzzy inference system for sleep staging was developed. Nine input variables including temporal and spectrum analyses of the EEG, EOG, and EMG signals were extracted and normalization was applied to these variables to reduce the effect of individual variability.
Sheng-Fu Liang   +4 more
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Autotuning of Fuzzy Inference System with RL

2007 American Control Conference, 2007
Reinforcement learning refers to a class of learning tasks and algorithms in which the learning system learns an associative mapping by maximizing a scalar evaluation function by interacting with environment. Fuzzy actor critic learning (FACL) is a reinforcement learning method based on dynamic programming principle.
Natarajan Pappa, S. Rama Krishnan
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Fuzzy inference system for osteoporosis detection

2016 IEEE Global Humanitarian Technology Conference (GHTC), 2016
The goal of this paper is to propose a fuzzy inference framework for diagnosis of osteoporosis disease in the field of medical imaging. The idea behind such a framework is to assist the physician to detect, control and treat various forms of osteoporosis in better way.
Reshmalakshmi Chandrasekharan   +1 more
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