Category: Uncategorized

Generalized intuitionistic fuzzy geometric aggregation operator and its application to multi-criteria group decision making

Abstract  In general, for multi-criteria group decision making problem, there exist inter-dependent or interactive phenomena among criteria
or preference of experts, so that it is not suitable for us to aggregate them by conventional aggrega…

Abstract  

In general, for multi-criteria group decision making problem, there exist inter-dependent or interactive phenomena among criteria
or preference of experts, so that it is not suitable for us to aggregate them by conventional aggregation operators based
on additive measures. In this paper, based on fuzzy measures a generalized intuitionistic fuzzy geometric aggregation operator
is investigated for multiple criteria group decision making. First, some operational laws on intuitionistic fuzzy values are
introduced. Then, a generalized intuitionistic fuzzy ordered geometric averaging (GIFOGA) operator is proposed. Moreover,
some of its properties are given in detail. It is shown that GIFOGA operator can be represented by special t-norms and t-conorms
and is a generalization of intuitionistic fuzzy ordered weighted geometric averaging operator. Further, an approach to multiple
criteria group decision making with intuitionistic fuzzy information is developed where what criteria and preference of experts
often have inter-dependent or interactive phenomena among criteria or preference of experts is taken into account. Finally,
a practical example is provided to illustrate the developed approaches.

  • Content Type Journal Article
  • Pages 1-10
  • DOI 10.1007/s00500-010-0554-6
  • Authors
    • Chunqiao Tan, Central South University School of Business Changsha 410083 China

Petri nets for modelling metabolic pathways: a survey

Abstract  In the last 15 years, several research efforts have been directed towards the representation and the analysis of metabolic
pathways by using Petri nets. The goal of this paper is twofold. First, we discuss how the knowledge about m…

Abstract  

In the last 15 years, several research efforts have been directed towards the representation and the analysis of metabolic
pathways by using Petri nets. The goal of this paper is twofold. First, we discuss how the knowledge about metabolic pathways
can be represented with Petri nets. We point out the main problems that arise in the construction of a Petri net model of
a metabolic pathway and we outline some solutions proposed in the literature. Second, we present a comprehensive review of
recent research on this topic, in order to assess the maturity of the field and the availability of a methodology for modelling
a metabolic pathway by a corresponding Petri net.

  • Content Type Journal Article
  • DOI 10.1007/s11047-010-9180-6
  • Authors
    • Paolo Baldan, Dipartimento di Matematica Pura e Applicata, Università di Padova, via Trieste 63, 35121 Padova, Italy
    • Nicoletta Cocco, Dipartimento di Informatica, Università Ca’ Foscari di Venezia, via Torino 155, 30172 Venezia Mestre, Italy
    • Andrea Marin, Dipartimento di Informatica, Università Ca’ Foscari di Venezia, via Torino 155, 30172 Venezia Mestre, Italy
    • Marta Simeoni, Dipartimento di Informatica, Università Ca’ Foscari di Venezia, via Torino 155, 30172 Venezia Mestre, Italy

Image annotation by incorporating word correlations into multi-class SVM

Abstract  Image annotation systems aim at automatically annotating images with semantic keywords. Machine learning approaches are often
used to develop these systems. In this paper, we propose an image annotation approach by incorporating wo…

Abstract  

Image annotation systems aim at automatically annotating images with semantic keywords. Machine learning approaches are often
used to develop these systems. In this paper, we propose an image annotation approach by incorporating word correlations into
multi-class support vector machine (SVM). At first, each image is segmented into five fixed-size blocks instead of time-consuming
object segmentation. Every keyword from training images is manually assigned to the corresponding block and word correlations
are computed by a co-occurrence matrix. Then, MPEG-7 visual descriptors are applied to these blocks to represent visual features
and the minimal-redundancy-maximum-relevance (mRMR) method is used to reduce the feature dimension. A block-feature-based
multi-class SVM classifier is trained for 80 semantic concepts. At last, the probabilistic outputs from SVM and the word correlations
are integrated to obtain the final annotation keywords. The experiments on Corel 5000 dataset demonstrate our approach is
effective and efficient.

  • Content Type Journal Article
  • Pages 1-11
  • DOI 10.1007/s00500-010-0558-2
  • Authors
    • Lei Zhang, Shandong University School of Computer Science and Technology Jinan China
    • Jun Ma, Shandong University School of Computer Science and Technology Jinan China

Variable precision rough set model over two universes and its properties

Abstract  The extension of rough set model is an important research direction in the rough set theory. In this paper, based on the rough
set model over two universes, we firstly propose the variable precision rough set model (VPRS-model) ove…

Abstract  

The extension of rough set model is an important research direction in the rough set theory. In this paper, based on the rough
set model over two universes, we firstly propose the variable precision rough set model (VPRS-model) over two universes using
the inclsion degree. Meantime, the concepts of the reverse lower and upper approximation operators are presented. Afterwards,
the properties of the approximation operators are studied. Finally, the approximation operators with two parameters are introduced
as a generalization of the VPRS-model over two universes, and the related conclusions are discussed.

  • Content Type Journal Article
  • Pages 1-11
  • DOI 10.1007/s00500-010-0562-6
  • Authors
    • Yonghong Shen, Tianshui Normal University School of Mathematics and Statistics Tianshui 741001 People’s Republic of China
    • Faxing Wang, Tongda College of Nanjing University of Posts and Telecommunications Nanjing 210046 People’s Republic of China

On aggregation in multiset-based self-assembly of graphs

Abstract  We continue the formal study of multiset-based self-assembly. The process of self-assembly of graphs, where iteratively new
nodes are attached to a given graph, is guided by rules operating on nodes labelled by multisets. In this w…

Abstract  

We continue the formal study of multiset-based self-assembly. The process of self-assembly of graphs, where iteratively new
nodes are attached to a given graph, is guided by rules operating on nodes labelled by multisets. In this way, the multisets
and rules model connection points (such as “sticky ends”) and complementarity/affinity between connection points, respectively.
We identify three natural ways (individual, free, and collective) to attach (aggregate) new nodes to the graph, and study
the generative power of the corresponding self-assembly systems. For example, it turns out that individual aggregation can
be simulated by free or collective aggregation. However, we demonstrate that, for a fixed set of connection points, collective
aggregation is rather restrictive. We also give a number of results that are independent of the way that aggregation is performed.

  • Content Type Journal Article
  • Pages 1-22
  • DOI 10.1007/s11047-010-9183-3
  • Authors
    • Francesco Bernardini, Leiden University Leiden Institute of Advanced Computer Science Leiden The Netherlands
    • Robert Brijder, Leiden University Leiden Institute of Advanced Computer Science Leiden The Netherlands
    • Matteo Cavaliere, Centre for Computational and Systems Biology (CoSBi) The Microsoft Research-University of Trento Trento Italy
    • Giuditta Franco, University of Verona Department of Computer Science Strada Le Grazie 15 37134 Verona Italy
    • Hendrik Jan Hoogeboom, Leiden University Leiden Institute of Advanced Computer Science Leiden The Netherlands
    • Grzegorz Rozenberg, Leiden University Leiden Institute of Advanced Computer Science Leiden The Netherlands

A modified hybrid method of spatial credibilistic clustering and particle swarm optimization

Abstract  Hybrid methods of spatial credibilistic clustering and particle swarm optimization (SCCPSO) (Wen et al. in Int J Fuzzy Syst
10:174–184, 2008) are validated to be effective, and produce better results than other common method…

Abstract  

Hybrid methods of spatial credibilistic clustering and particle swarm optimization (SCCPSO) (Wen et al. in Int J Fuzzy Syst
10:174–184, 2008) are validated to be effective, and produce better results than other common methods. In this paper, SCCPSO is further investigated
and a modified SCCPSO is put forward by discussing the membership functions and presenting a pre-selection method based on
proving an evaluation criterion on the clustering results. The analysis of computational complexity demonstrates the feasibility
of the modified SCCPSO. Experiments verify the discussion on the membership functions, the correctness of the evaluation criterion,
as well as the effectiveness of the pre-selection method and the modified SCCPSO.

  • Content Type Journal Article
  • Pages 1-11
  • DOI 10.1007/s00500-010-0553-7
  • Authors
    • Peihan Wen, Tsinghua University Department of Industrial Engineering Beijing 100084 China
    • Jian Zhou, Tsinghua University Department of Industrial Engineering Beijing 100084 China
    • Li Zheng, Tsinghua University Department of Industrial Engineering Beijing 100084 China

Entropy-type classification maximum likelihood algorithms for mixture models

Abstract  Mixtures of distributions are popularly used as probability models for analyzing grouped data. Classification maximum likelihood
(CML) is an important maximum likelihood approach to clustering with mixture models. Yang et al. exten…

Abstract  

Mixtures of distributions are popularly used as probability models for analyzing grouped data. Classification maximum likelihood
(CML) is an important maximum likelihood approach to clustering with mixture models. Yang et al. extended CML to fuzzy CML.
Although fuzzy CML presents better results than CML, it is always affected by the fuzziness index parameter. In this paper,
we consider fuzzy CML with an entropy-regularization term to create an entropy-type CML algorithm. The proposed entropy-type
CML is a parameter-free algorithm for mixture models. Some numerical and real-data comparisons show that the proposed method
provides better results than some existing methods.

  • Content Type Journal Article
  • Pages 1-9
  • DOI 10.1007/s00500-010-0560-8
  • Authors
    • Chien-Yo Lai, Chung Yuan Christian University Department of Applied Mathematics Chung-Li 32023 Taiwan
    • Miin-Shen Yang, Chung Yuan Christian University Department of Applied Mathematics Chung-Li 32023 Taiwan

A cost-efficient and versatile sanitizing algorithm by using a greedy approach

Abstract  In a very large database, there exists sensitive information that must be protected against unauthorized accesses. The confidentiality
protection of the information has been a long-term goal pursued by the database security researc…

Abstract  

In a very large database, there exists sensitive information that must be protected against unauthorized accesses. The confidentiality
protection of the information has been a long-term goal pursued by the database security research community and the government
statistical agencies. In this paper, we proposed greedy methods for hiding sensitive rules. The experimental results showed
the effectiveness of our approaches in terms of undesired side effects avoided in the rule hiding process. The results also
revealed that in most cases, all the sensitive rules are hidden without generating spurious rules. First, the good scalability
of our approach in terms of database sizes was achieved by using an efficient data structure, FCET, to store only maximal
frequent itemsets instead of storing all frequent itemsets. Furthermore, we also proposed a new framework for enforcing the
privacy in mining association rules. In the framework, we combined the techniques of efficiently hiding sensitive rules with
the transaction retrieval engine based on the FCET index tree. For hiding sensitive rules, the proposed greedy approach includes
a greedy approximation algorithm and a greedy exhausted algorithm to sanitize the database. In particular, we presented four
strategies in the sanitizing procedure and four strategies in the exposed procedure, respectively, for hiding a group of association
rules characterized as sensitive or artificial rules. In addition, the exposed procedure would expose missing rules during
the processing so that the number of missing rules could be lowered as much as possible.

  • Content Type Journal Article
  • Pages 1-14
  • DOI 10.1007/s00500-010-0549-3
  • Authors
    • Chieh-Ming Wu, National Yunlin University of Science and Technology Graduate School of Engineering Science and Technology 123 University Road, Section 3, Touliu Yunlin 640 Taiwan, ROC
    • Yin-Fu Huang, National Yunlin University of Science and Technology Department of Computer Science and Information Engineering 123 University Road, Section 3, Touliu Yunlin 640 Taiwan, ROC

Stabilization of nonlinear time-delay systems with input saturation via anti-windup fuzzy design

Abstract  This investigation considers stability analysis and control design for nonlinear time-delay systems subject to input saturation.
An anti-windup fuzzy control approach, based on fuzzy modeling of nonlinear systems, is developed to d…

Abstract  

This investigation considers stability analysis and control design for nonlinear time-delay systems subject to input saturation.
An anti-windup fuzzy control approach, based on fuzzy modeling of nonlinear systems, is developed to deal with the problems
of stabilization of the closed-loop system and enlargement of the domain of attraction. To facilitate the designing work,
the nonlinearity of saturation is first characterized by sector conditions, which provide a basis for analysis and synthesis
of the anti-windup fuzzy control scheme. Then, the Lyapunov–Krasovskii delay-independent and delay-dependent functional approaches
are applied to establish sufficient conditions that ensure convergence of all admissible initial states within the domain
of attraction. These conditions are formulated as a convex optimization problem with constraints provided by a set of linear
matrix inequalities. Finally, numeric examples are given to validate the proposed method.

  • Content Type Journal Article
  • Pages 1-12
  • DOI 10.1007/s00500-010-0555-5
  • Authors
    • Chen-Sheng Ting, National Formosa University Department of Electrical Engineering Yunlin 632 Taiwan, ROC
    • Chuan-Sheng Liu, National Formosa University Department of Aeronautical Engineering Yunlin 632 Taiwan, ROC

SIGEVOlution Volume 4 Issue 3

The new issue of SIGEVOlution is now available for you to download from: http://www.sigevolution.org The issue features: Issues in Applying Computational Intelligence by Arthur Kordon JavaXCSF by Patrick O. Stalph & Martin V. Butz Dissertation Corner New issues of journals … Continue reading →

Portland, Oregon

The new issue of SIGEVOlution is now available for you to download from:
http://www.sigevolution.org

The issue features:

  • Issues in Applying Computational Intelligence by Arthur Kordon
  • JavaXCSF by Patrick O. Stalph & Martin V. Butz
  • Dissertation Corner
  • New issues of journals
  • Calls & calendar

The newsletter is intended to be viewed electronically.

Pier Luca Lanzi (EIC)