We introduce a new algorithm for mining the fuzzy association rules by removing redundant fuzzy association (RFA) rules. Firstly, we analyze some properties of fuzzy association rules and give the definition of RFA rules. ...
Ramezani Fahimeh; Lu Jie(Springer-Verlag Berlin / Heidelberg, 2011)
There are many fuzzy ranking algorithms available to solve multi-attribute decision making (MADM) problems. Some are more suitable than others for particular decision problems. This paper proposes a new method for choosing ...
Xiao Bing; Gao Xinbo; Tao Dacheng; Li Xuelong(Elsevier Science Bv, 2009)
Face recognition by sketches in photos remains a challenging task. Unlike the existing sketch-photo recognition methods, which convert a photo into sketch and then perform the sketch-photo recognition through sketch-sketch ...
Wang Huaqing; He Xiangjian; Wu Qiang; Hintz Thomas(The Institute of Electrical and Electronic Engineers Inc (IEEE), 2006)
In this paper, we propose a Fractal Image Compression
method on a virtual hexagonal image structure by adopting
Fisher’s basic method on the traditional square image
structure. The modification on the definition of range ...
We introduce the concepts of interior, boundary, subspace, connected space, first- and second-countable spaces, and establish some of their properties in fuzzifying topology.
We point out a new approach for fuzzy topology with fuzzy logic, and discuss the neighborhood structure of a point and the convergence of nets and filters in this new framework.
Wang Huaqing; Wu Qiang; He Xiangjian; Hintz Thomas(The Institute of Electrical and Electronic Engineers Inc (IEEE), 2006)
Spiral Architecture based fractal image compression is
proposed in this paper. Perceptually, a new definition of
range block and domain block is presented on such
enhanced image structure. Compared with the common
square ...
Lu Jie; Wu Fengjie; Zhang Guangquan(National University of Singapore, 2003)
Many business decisions can be modeled as multiple
objective linear programming (MOLP) problems. When
formulating a MOLP problem, objective functions and
constraints involve many parameters which possible
values are ...
Lu Liangfu; Zhang Jiawan; Huang Mao; Fu Lei(Elsevier Ltd, 2010)
With the rapid growth of networked data communications in size and complexity, network administrators today are facing more challenges to protect their networked computers and devices from all kinds of attacks. This paper ...
Liu Gm; Li Jinyan; Wong L(Springer London Ltd, 2008)
A complete set of frequent itemsets can get undesirably large due to redundancy when the minimum support threshold is low or when the database is dense. Several concise representations have been previously proposed to ...
A new Differential Evolution (DE) that incorporates fuzzy control and k-nearest neighbors algorithm to determine the terminating condition is proposed. A technique called Iteration Windows is introduced to govern the number ...
A new fuzzy modeling based on fuzzy linear fractional transformations model is introduced. This new representation is shown to be a flexible tool for handling complicated nonlinear models. Particularly, the new fuzzy model ...
Zhang Guoli; Lu Hai Yan; Zhang Guangquan(IEEE, 2010)
This paper proposes a new parallel search algorithm using an evolutionary algorithm and quasi-simplex techniques (EAQST) for non-linear constrained function optimization. EAQST produces the offspring in parallel by using ...
Concha Oscar; Sanchez-Montanes Manuel(Springer Berlin / Heidelberg, 2007)
Standard machine learning techniques assume that the statistical structure of the training and test datasets are the same (i.e. same attribute distribution p(x), and same class distribution p(c|x)). However, in real ...
In this paper, we discuss the problem of feature selection and the importance of using mutual information in evaluating the discrimination ability of feature subsets between class labels. Because of the difficulties ...
Lu Hai Yan; Zhang Guoli(Macquarie Scientific Publishing, 2004)
This paper proposes a new parallel search algorithm
using evolutionary programming and quasi-simplex technique
(EPQS). EPQS produces the offspring from three ways in
parallel: 1) Using the Gaussian mutation, 2) Using ...
This paper presents a new particle swarm optimization (PSO) algorithm for tuning parameters (weights) of neural networks. The new PSO algorithm is called fuzzy logic-based particle swarm optimization with cross-mutated ...