Results 161 to 170 of about 3,244 (195)

Automatic robust threshold finding aided by fuzzy information granulation

Proceedings of International Conference on Image Processing, 2002
This paper presents a robust automatic threshold finding method for the human brain MR image segmentation. The method is based on fuzzy information granulation shown by Zadeh (see Abstract of BISC Seminar, 1996). The human brain MR image consists of several parts; the gray matter, white matter, cerebrospinal fluid and so on.
Syoji Kobashi, Naotake Kamiura, Yutaka Hata, Makoto Ishikawa   +3 more
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Optimized fuzzy information granulation based machine learning classification

2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery, 2010
In machine learning classification, the classifier can be described by some rules, and the rules can be expressed by fuzzy granules corresponding to fuzzy concepts. In this paper we will introduce fuzzy information granulation to the process of building fuzzy classifier.
Yang Li, Fusheng Yu
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On Optimal Fuzzy Information Granulation

2002
Information granulation is one of the basic concept of human cognition. L.A. Zadeh defined the subject of the theory of fuzzy information granulation by the following way “The theory of fuzzy information granulation (TFIG) is inspired by the ways in which humans granulate information and reason with it.
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Fuzzy Information Granulation with Multiple Levels of Granularity

2011
Granular computing is a problem solving paradigm based on information granules, which are conceptual entities derived through a granulation process. Solving a complex problem, via a granular computing approach, means splitting the problem into information granules and handling each granule as a whole.
CASTELLANO, GIOVANNA, MENCAR, CORRADO, FANELLI, Anna Maria   +2 more
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Balancing Interpretability and Accuracy by Multi-Level Fuzzy Information Granulation

2006 IEEE International Conference on Fuzzy Systems, 2006
In this paper we present a multi-level approach for extracting well-defined and semantically sound information granules from numerical data. The approach is based on the Double Clustering framework (DC/), which performs two main clustering steps on the data space in order to extract granules qualitatively described in terms of fuzzy sets that meet a ...
Corrado Mencar, Giovanna Castellano, Anna Maria Fanelli   +2 more
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A fast fuzzy support vector machine based on information granulation

Neural Computing and Applications, 2012
In order to improve the efficiency of fuzzy support vector machine training high-dimensional and large-scale dataset, a fast fuzzy support vector machine based on information granulation (FSVM-FIG) is proposed. Firstly, the training set is divided into some granules by fuzzy C-means, including pure granules and mixed granules.
Shifei Ding, Youzhen Han, Junzhao Yu, Yaxiang Gu   +3 more
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Multicriterial optimization of information granules in fuzzy If-Then rules

2018
Investigation of trade-off between characteristics of information granules for construction of fuzzy rule-based model is challenging scientific problem. Main optimization requirement in information granules estimation (antecedent and consequent parts of fuzzy rules) are cardinality which characterizes justifiability (reliability) of information ...
Aliev, R.A., Huseynov, O.H., Adilova, Nigar E.   +2 more
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An application of fuzzy information granulation in the emerging area of online sports

Expert Systems with Applications, 2011
Abstract: One of the major computational challenges that online businesses face today is to make sense of huge amount of information. Granular computing has emerged as an important conceptual and computational paradigm of information processing. As an emerging field of study, it has been suggested that granular computing at philosophical level concerns
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Information granulation and uncertainty measures in interval-valued intuitionistic fuzzy information systems

European Journal of Operational Research, 2013
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Bing Huang, Yu-liang Zhuang, Huaxiong Li
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Research on Identifying Emotion Sentence Based on Fuzzy Information Granulation

2017 13th International Conference on Computational Intelligence and Security (CIS), 2017
We put forward a method based on fuzzy information granulation to solve the problem of identifying the emotional sentence. Firstly, the necessary work is carried out on the microblogging sentence training set, including the word segmentation, stop words and so on. The feature vector is constructed and the weight of the feature is calculated.
Qiong Shen, Bin Gui, Jianlin Zhu
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