Tag: Soft Computing – A Fusion of Foundations, Methodologies and Applications

Heterogeneous computing scheduling with evolutionary algorithms

Abstract  This work presents sequential and parallel evolutionary algorithms (EAs) applied to the scheduling problem in heterogeneous
computing environments, a NP-hard problem with capital relevance in distributed computing. These methods ha…

Abstract  

This work presents sequential and parallel evolutionary algorithms (EAs) applied to the scheduling problem in heterogeneous
computing environments, a NP-hard problem with capital relevance in distributed computing. These methods have been specifically
designed to provide accurate and efficient solutions by using simple operators that allow them to be later extended for solving
realistic problem instances arising in distributed heterogeneous computing (HC) and grid systems. The EAs were codified over
MALLBA, a general-purpose library for combinatorial optimization. Efficient numerical results are reported in the experimental
analysis performed on well-known problem instances. The comparative study of scheduling methods shows that the parallel versions
of the implemented evolutionary algorithms are able to achieve high problem solving efficacy, outperforming traditional scheduling
heuristics and also improving over previous results already reported in the related literature.

  • Content Type Journal Article
  • Pages 1-17
  • DOI 10.1007/s00500-010-0594-y
  • Authors
    • Sergio Nesmachnow, Universidad de la República Montevideo Uruguay
    • Héctor Cancela, Universidad de la República Montevideo Uruguay
    • Enrique Alba, Universidad de Málaga Málaga Spain

Semi-supervised model applied to the prediction of the response to preoperative chemotherapy for breast cancer

Abstract  Breast cancer is the second most frequent one, and the first one affecting the women. The standard treatment has three main
stages: a preoperative chemotherapy followed by a surgery operation, then an post-operatory chemotherapy. B…

Abstract  

Breast cancer is the second most frequent one, and the first one affecting the women. The standard treatment has three main
stages: a preoperative chemotherapy followed by a surgery operation, then an post-operatory chemotherapy. Because the response
to the preoperative chemotherapy is correlated to a good prognosis, and because the clinical and biological information do
not yield to efficient predictions of the response, a lot of research effort is being devoted to the design of predictors
relying on the measurement of genes’ expression levels. In the present paper, we report our works for designing genomic predictors
of the response to the preoperative chemotherapy, making use of a semi-supervised machine learning approach. The method is
based on margin geometric information of patterns of low density areas, computed on a labeled dataset and on an unlabeled
one.

  • Content Type Journal Article
  • Pages 1-8
  • DOI 10.1007/s00500-010-0589-8
  • Authors
    • Frederico Coelho, PPGEE, CPDEE Universidade Federal de Minas Gerais Belo Horizonte Brazil
    • Antônio de Pádua Braga, PPGEE, CPDEE Universidade Federal de Minas Gerais Belo Horizonte Brazil
    • René Natowicz, Université Paris-Est ESIEE-Paris, Département d’ínformatiquex Paris France
    • Roman Rouzier, Hôpital Tenon Départment of Gynecology Paris France

The inheritance of BDE-property in sharply dominating lattice effect algebras and (o)-continuous states

Abstract  We study remarkable sub-lattice effect algebras of Archimedean atomic lattice effect algebras E, namely their blocks M, centers C(E), compatibility centers B(E) and sets of all sharp elements S(E) of E. We show that in every such ef…

Abstract  

We study remarkable sub-lattice effect algebras of Archimedean atomic lattice effect algebras E, namely their blocks M, centers C(E), compatibility centers B(E) and sets of all sharp elements S(E) of E. We show that in every such effect algebra E, every atomic block M and the set S(E) are bifull sub-lattice effect algebras of E. Consequently, if E is moreover sharply dominating then every atomic block M is again sharply dominating and the basic decompositions of elements (BDE of x) in E and in M coincide. Thus in the compatibility center B(E) of E, nonzero elements are dominated by central elements and their basic decompositions coincide with those in all atomic blocks
and in E. Some further details which may be helpful under answers about the existence and properties of states are shown. Namely,
we prove the existence of an (o)-continuous state on every sharply dominating Archimedean atomic lattice effect algebra E with


B(E)\not = C(E).

Moreover, for compactly generated Archimedean lattice effect algebras the equivalence of (o)-continuity of states with their complete additivity is proved. Further, we prove “State smearing theorem” for these lattice
effect algebras.

  • Content Type Journal Article
  • Pages 1-13
  • DOI 10.1007/s00500-010-0561-7
  • Authors
    • Jan Paseka, Masaryk University Department of Mathematics and Statistics, Faculty of Science Kotlářská 2 611 37 Brno Czech Republic
    • Zdenka Riečanová, Slovak University of Technology Department of Mathematics, Faculty of Electrical Engineering and Information Technology Ilkovičova 3 812 19 Bratislava Slovak Republic

Optimization of interval type-2 fuzzy logic controllers using evolutionary algorithms

Abstract  A method for designing optimal interval type-2 fuzzy logic controllers using evolutionary algorithms is presented in this
paper. Interval type-2 fuzzy controllers can outperform conventional type-1 fuzzy controllers when the proble…

Abstract  

A method for designing optimal interval type-2 fuzzy logic controllers using evolutionary algorithms is presented in this
paper. Interval type-2 fuzzy controllers can outperform conventional type-1 fuzzy controllers when the problem has a high
degree of uncertainty. However, designing interval type-2 fuzzy controllers is more difficult because there are more parameters
involved. In this paper, interval type-2 fuzzy systems are approximated with the average of two type-1 fuzzy systems, which
has been shown to give good results in control if the type-1 fuzzy systems can be obtained appropriately. An evolutionary
algorithm is applied to find the optimal interval type-2 fuzzy system as mentioned above. The human evolutionary model is
applied for optimizing the interval type-2 fuzzy controller for a particular non-linear plant and results are compared against
an optimal type-1 fuzzy controller. A comparative study of simulation results of the type-2 and type-1 fuzzy controllers,
under different noise levels, is also presented. Simulation results show that interval type-2 fuzzy controllers obtained with
the evolutionary algorithm outperform type-1 fuzzy controllers.

  • Content Type Journal Article
  • Pages 1-16
  • DOI 10.1007/s00500-010-0588-9
  • Authors
    • O. Castillo, Tijuana, Institute of Technology Tijuana BC Mexico
    • P. Melin, Tijuana, Institute of Technology Tijuana BC Mexico
    • A. Alanis, Tijuana, Institute of Technology Tijuana BC Mexico
    • O. Montiel, Center for Research in Digital Systems, IPN Tijuana BC Mexico
    • R. Sepulveda, Center for Research in Digital Systems, IPN Tijuana BC Mexico

A hybrid neural network cybernetic system for quantifying cross-market dynamics and business forecasting

Abstract  The internal structure of a complex system can manifest itself with correlations among its components. In global business,
the interactions between different markets cause collective lead–lag behavior having special statistical p…

Abstract  

The internal structure of a complex system can manifest itself with correlations among its components. In global business,
the interactions between different markets cause collective lead–lag behavior having special statistical properties which
reflect the underlying dynamics. In this work, a cybernetic system of combining the vector autoregression (VAR) and genetic
algorithm (GA) with neural network (NN) is proposed to take advantage of the lead–lag dynamics, to make the NN forecasting
process more transparent and to improve the NN’s prediction capability. Two business case studies are carried out to demonstrate
the advantages of our proposed system. The first one is the tourism demand forecasting for the Hong Kong market. Another business
case study is the modeling and forecasting of Asian Pacific stock markets. The multivariable time series data is investigated
with the VAR analysis, and then the NN is fed with the relevant variables determined by the VAR analysis for forecasting.
Lastly, GA is used to cope with the time-dependent nature of the co-relationships among the variables. Experimental results
show that our system is more robust and makes more accurate prediction than the benchmark NN. The contribution of this paper
lies in the novel application of the forecasting modules and the high degree of transparency of the forecasting process.

  • Content Type Journal Article
  • Pages 1-13
  • DOI 10.1007/s00500-010-0580-4
  • Authors
    • S. I. Ao, International Association of Engineers Hong Kong China

Validating criteria with imprecise data in the case of trapezoidal representations

Abstract  We are interested in the issue of determining an alternative’s satisfaction to a criterion when the alternative’s associated
attribute value is imprecise. We introduce two approaches to the determination of criteria satisfactio…

Abstract  

We are interested in the issue of determining an alternative’s satisfaction to a criterion when the alternative’s associated
attribute value is imprecise. We introduce two approaches to the determination of criteria satisfaction in this uncertain
environment, one based on the idea of containment and the other on the idea of possibility. We are particularly interested
in the case in which the imprecise data is expressed in terms of a trapezoidal type distribution. We provide an algorithmic
solution to this problem enabling it to be efficiently implemented in a digital environment. A number of examples are provided
illustrating our algorithms.

  • Content Type Journal Article
  • Pages 1-12
  • DOI 10.1007/s00500-010-0569-z
  • Authors
    • Ronald R. Yager, Iona College Machine Intelligence Institute New Rochelle NY 10801 USA

Detecting anomalies from high-dimensional wireless network data streams: a case study

Abstract  In this paper, we study the problem of anomaly detection in wireless network streams. We have developed a new technique, called
Stream Projected Outlier deTector (SPOT), to deal with the problem of anomaly detection from multi-dime…

Abstract  

In this paper, we study the problem of anomaly detection in wireless network streams. We have developed a new technique, called
Stream Projected Outlier deTector (SPOT), to deal with the problem of anomaly detection from multi-dimensional or high-dimensional
data streams. We conduct a detailed case study of SPOT in this paper by deploying it for anomaly detection from a real-life
wireless network data stream. Since this wireless network data stream is unlabeled, a validating method is thus proposed to
generate the ground-truth results in this case study for performance evaluation. Extensive experiments are conducted and the
results demonstrate that SPOT is effective in detecting anomalies from wireless network data streams and outperforms existing
anomaly detection methods.

  • Content Type Journal Article
  • Pages 1-21
  • DOI 10.1007/s00500-010-0575-1
  • Authors
    • Ji Zhang, University of Southern Queensland Toowoomba QLD Australia
    • Qigang Gao, Dalhousie University Halifax NS Canada
    • Hai Wang, Saint Mary’s University Halifax NS Canada
    • Hua Wang, University of Southern Queensland Toowoomba QLD Australia

The sufficient and necessary condition for chance distribution of bifuzzy variable

Abstract  Fuzzy sets and fuzzy variables have undergone several different extensions overtime. One of them involved including a “bifuzzy
variable” as a fuzzy element for describing the more complete systems. The properties of bifuzzy var…

Abstract  

Fuzzy sets and fuzzy variables have undergone several different extensions overtime. One of them involved including a “bifuzzy
variable” as a fuzzy element for describing the more complete systems. The properties of bifuzzy variable were obtained by
introducing the concept of “chance distribution”. In this paper, we will present a sufficient and necessary condition for
chance distribution of bifuzzy variable. Here we present a constructive proof base on credibility theory for the sufficient
part.

  • Content Type Journal Article
  • Pages 1-5
  • DOI 10.1007/s00500-010-0567-1
  • Authors
    • Zhongfeng Qin, Beihang University School of Economics and Management Beijing 100191 China
    • Xiang Li, Beijing Jiaotong University The State Key Laboratory of Rail Traffic Control and Safety Beijing 100044 China

Case study of inaccuracies in the granulation of decision trees

Abstract  Cybernetics studies information process in the context of interaction with physical systems. Because such information is sometimes
vague and exhibits complex interactions; it can only be discerned using approximate representations….

Abstract  

Cybernetics studies information process in the context of interaction with physical systems. Because such information is sometimes
vague and exhibits complex interactions; it can only be discerned using approximate representations. Machine learning provides
solutions that create approximate models of information and decision trees are one of its main components. However, decision
trees are susceptible to information overload and can get overly complex when a large amount of data is inputted in them.
Granulation of decision tree remedies this problem by providing the essential structure of the decision tree, which can decrease
its utility. To evaluate the relationship that exists between granulation and decision tree complexity, data uncertainty and
prediction accuracy, the deficiencies obtained by nursing homes during annual inspections were taken as a case study. Using
rough sets, three forms of granulation were performed: (1) attribute grouping, (2) removing insignificant attributes and (3)
removing uncertain records. Attribute grouping significantly reduces tree complexity without having any strong effect upon
data consistency and accuracy. On the other hand, removing insignificant features decrease data consistency and tree complexity,
while increasing the error in prediction. Finally, decrease in the uncertainty of the dataset results in an increase in accuracy
and has no impact on tree complexity.

  • Content Type Journal Article
  • Pages 1-8
  • DOI 10.1007/s00500-010-0587-x
  • Authors
    • Salman Badr, University of Nottingham School of Computer Science, Faculty of Science Malaysia Campus 43500 Semenyih Malaysia
    • Andrzej Bargiela, University of Nottingham School of Computer Science, Faculty of Science Malaysia Campus 43500 Semenyih Malaysia

Granular computing based on fuzzy similarity relations

Abstract  Rough sets and fuzzy rough sets serve as important approaches to granular computing, but the granular structure of fuzzy rough
sets is not as clear as that of classical rough sets since lower and upper approximations in fuzzy rough…

Abstract  

Rough sets and fuzzy rough sets serve as important approaches to granular computing, but the granular structure of fuzzy rough
sets is not as clear as that of classical rough sets since lower and upper approximations in fuzzy rough sets are defined
in terms of membership functions, while lower and upper approximations in classical rough sets are defined in terms of union
of some basic granules. This limits further investigation of the existing fuzzy rough sets. To bring to light the innate granular
structure of fuzzy rough sets, we develop a theory of granular computing based on fuzzy relations in this paper. We propose
the concept of granular fuzzy sets based on fuzzy similarity relations, investigate the properties of the proposed granular
fuzzy sets using constructive and axiomatic approaches, and study the relationship between granular fuzzy sets and fuzzy relations.
We then use the granular fuzzy sets to describe the granular structures of lower and upper approximations of a fuzzy set within
the framework of granular computing. Finally, we characterize the structure of attribute reduction in terms of granular fuzzy
sets, and two examples are also employed to illustrate our idea in this paper.

  • Content Type Journal Article
  • Pages 1-12
  • DOI 10.1007/s00500-010-0583-1
  • Authors
    • Chen Degang, North China Electric Power University Department of Mathematics and Physics Beijing 102206 People’s Republic of China
    • Yang Yongping, North China Electric Power University Beijing Key Laboratory of Safety and Clean Utilization of Energy Beijing 102206 China
    • Wang Hui, University of Ulster Faculty of Engineering, School of Computing and Mathematics Jordanstown Northern Ireland, UK