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Home > Papers > Fuzzy-Mathematics

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	1. Completeness in fuzzy metric spaces based on $I$-filters
	YUE Yue-Li
	Mathematics 23 November 2015
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	Abstract:The aim of this paper is to study completeness in fuzzy metric spaces and $I$-uniform spaces based on $I$-filters. It is shown that the degree to which fuzzy metric space is complete is equal to the degree to which its induced $I$-uniform space is complete, this is to say that the fuzzy metric space is complete if and only if the induced $I$-uniform space is complete.
	TO cite this article:YUE Yue-Li. Completeness in fuzzy metric spaces based on $I$-filters[OL].[23 November 2015] http://en.paper.edu.cn/en_releasepaper/content/4665155


	2. Convergence and completeness in fuzzy metric spaces and fuzzifying uniform spaces
	YUE Yue-Li
	Mathematics 23 November 2015
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	Abstract:The aim of this paper is to study convergence and completeness in fuzzy metric spaces and fuzzifying uniform spaces from a degree point of view. Firstly, the convergence degree theory of sequence in fuzzy metric spaces are given. Secondly, the relationship between compactness, total boundedness and completeness is studied. Thirdly, the corresponding filter convergence theory and completeness degree theory in fuzzifying uniform spaces are investigated. Finally, the relationship between the completeness of fuzzy metric spaces and that of induced fuzzifying uniform spaces is studied.
	TO cite this article:YUE Yue-Li. Convergence and completeness in fuzzy metric spaces and fuzzifying uniform spaces[OL].[23 November 2015] http://en.paper.edu.cn/en_releasepaper/content/4665152

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	3. Three kinds of functional equations with $h-e-$implications
	LIU Hua-Wen
	Mathematics 11 April 2014
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	Abstract:Recently, the author introduced a new class of fuzzyimplications called $h-e-$implications. In this paper, weinvestigate three kinds of functional equations with this class offuzzy implications, i.e., law of importation, contraction law anddistributivity over triangular norms (t-norms) and triangularconorms (t-conorms). For the law of importation, we establishnecessary and sufficient conditions of making it hold. It is shownthat the contraction law does not hold for any $h-e-$implication.For the distributivity of $h-e-$implications over t-norms andt-conorms, we respectively give the necessary and the sufficientconditions. This work will be of certain guiding significance forthe design and analysis of fuzzy systems with every kind ofperformance.
	TO cite this article:LIU Hua-Wen. Three kinds of functional equations with $h-e-$implications[OL].[11 April 2014] http://en.paper.edu.cn/en_releasepaper/content/4593069


	4. A new class of fuzzy implications derived from unary monotonic functions
	LIU Huawen
	Mathematics 17 March 2014
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	Abstract:By using unary monotonic functions on [0,1] which maybe non-continuous, we introduce a new kind of fuzzy implicationscalled $h-e-$implications, and analyze its basic properties, such asleft neutrality, exchange principle, contraposition and thecontinuity, etc. Several known classes of fuzzy implications derivedfrom unary functions are shown to be the particular cases of$h-e-$implications. It is also shown that the family of$h-e-$implications differs from the well known classes of fuzzyimplications, i.e., (S,N)-, R- and QL-implications. The resultsobtained in this paper will be helpful to improve the operatortheory for approximate reasoning. At the same time, they will alsoenlarge the operator space for intelligent systems.
	TO cite this article:LIU Huawen. A new class of fuzzy implications derived from unary monotonic functions[OL].[17 March 2014] http://en.paper.edu.cn/en_releasepaper/content/4590352


	5. A new fuzzy integral for data mining
	Liu Wan-Li,Liu Jin-Bo
	Mathematics 04 March 2011
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	Abstract:Any specified fuzzy integral can be used as an aggregation tool ininformation fusion, so introducing more types of integrals willprovide more choices to deal with various types of objectives and components in real problems. This paper aims in defining and investigating a new type of fuzzy integral, called $(T)$ fuzzyintegral based on the concepts of $mathfrak{T}$-norm and$mathfrak{T}$-conorm. For this integral, the integrand, themeasure and the integration result are all multi-valued. Then, some classical results of the integral are obtained。 Moreover,different integration results can be got based on different kinds ofcomponent of multi-valued measure. Here, we will discuss someproperties and theoremsin case the component of multi-valued measure is generalizedfuzzy measure, fuzzy measure and generalized $T$ measure.
	TO cite this article:Liu Wan-Li,Liu Jin-Bo. A new fuzzy integral for data mining[OL].[ 4 March 2011] http://en.paper.edu.cn/en_releasepaper/content/4414378


	6. (T) Fuzzy Integral of Multi-dimensional Function
	Liu Wanli,Zhang Qiuzhao
	Mathematics 17 April 2010
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	Abstract:Firstly, based on the T fuzzy measure and (T)fuzzy integral of one-dimensional function, this paper defines multi-dimensional simple function using generalized T-norm and S-norm and obtains a theorem on the representation form of a common multi-dimensional measurable function. Then it intro-duces two operational symbols T and S, presents the definitions of T fuzzy integrals for themulti-dimensional simple function and a commonmulti-dimensional measurable function and discusses some properties which are similartoone-dimensional case.I ndex Terms—multi-dimensional function; simplefunction; T fuzzy integral.
	TO cite this article:Liu Wanli,Zhang Qiuzhao. (T) Fuzzy Integral of Multi-dimensional Function[OL].[17 April 2010] http://en.paper.edu.cn/en_releasepaper/content/42031


	7. License plate Recognition Model Based on Neural Networks
	LiuYan
	Mathematics 05 December 2008
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	Abstract:License Plate Recognition Intelligent Transportation System is an important part of a wide range of applications and a better prospect in the near future license plate recognition system will be in the public security, communications, high-speed, and other departments are widely used. In this paper, neural network since the license plate number on the Lenovo models for pattern recognition, this model has a fast algorithm to identify high-precision, high anti-noise performance advantages. I believe this model has a certain practical value.
	TO cite this article:LiuYan. License plate Recognition Model Based on Neural Networks[OL].[ 5 December 2008] http://en.paper.edu.cn/en_releasepaper/content/26341


	8. Based on fuzzy math students eligible for scholarship assessment
	Liu Xiaoxu
	Mathematics 24 November 2008
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	Abstract:Based on the language of pattern recognition is wider context of applications in the mode of modern management science, such as the choice of personnel, project evaluation, the evaluation of the business, and so on, the model will be able to use natural language statements. According to the human language to describe the model for the establishment of an appropriate mathematical model, so as to solve real-life production, is of great significance. This article is for colleges and universities scholarship eligibility assessment, establishing the fuzzy language model. This language model, according to the students of outstanding quality, and may be eligible to receive scholarships to describe the language discussed the assessment of students eligible for scholarships. Accreditation for colleges and universities to provide a scientific and fair method of assessing the scholarship, was in line with the conclusions of the actual situation.
	TO cite this article:Liu Xiaoxu. Based on fuzzy math students eligible for scholarship assessment[OL].[24 November 2008] http://en.paper.edu.cn/en_releasepaper/content/26000


	9. A new definition of locally convex L-topological vector spaces
	Hua-peng Zhang,Jin-xuan Fang
	Mathematics 17 March 2008
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	Abstract:In this paper, a new definition of locally convex L-topological vector spaces is given. The relationship between this new definition and the previous definition of locally convex L-topological vector spaces given by Yan and Fang [L-fuzzy locally convex topological vector spaces, J. Fuzzy Math. 7 (3) (1999) 765-772] is investigated. Moreover, the concept of generalized L-fuzzy semi-norm is introduced. By using a family of generalized L-fuzzy semi-norms, a characterization of the new locally convex L-topological vector spaces is presented.
	TO cite this article:Hua-peng Zhang,Jin-xuan Fang. A new definition of locally convex L-topological vector spaces[OL].[17 March 2008] http://en.paper.edu.cn/en_releasepaper/content/19377


	10. On I(L)-topological vector spaces generated by a co-tower of L-topological vector spaces
	Hua-peng Zhang,Jin-xuan Fang
	Mathematics 17 March 2008
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	Abstract:In this paper, a characterization for an I(L)-topological space to be generated by a given co-tower of L-topological spaces is obtained. Moreover, the relationship between some properties of an I(L)-topological vector space generated by a co-tower of L-topological vector spaces and that of the given co-tower of L-topological vector spaces is investigated.
	TO cite this article:Hua-peng Zhang,Jin-xuan Fang. On I(L)-topological vector spaces generated by a co-tower of L-topological vector spaces[OL].[17 March 2008] http://en.paper.edu.cn/en_releasepaper/content/19350

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