The road safety performance of countries is conducted by combining seven main risk indicators into one index using a particular weighting and aggregation method. Weights can be determined with respect to the assumed importance of the indicator, whereas aggregation operators can be used to stress better performances differently from worse performances irrespective of the indicator’s meaning. In ...

NeuroEvolution (NE) is the application of evolutionary algorithms to Artificial Neural Networks (ANN). This paper reports on an investigation into the relative importance of weight evolution and topology evolution when training ANN using NE. This investigation used the NE technique Cartesian Genetic Programming of Artificial Neural Networks (CGPANN). The results presented show that the choice o...

Keywords: Cluster analysis Maximum entropy principle k-means Fuzzy c-means Sample weights Robustness a b s t r a c t Although there have been many researches on cluster analysis considering feature (or variable) weights, little effort has been made regarding sample weights in clustering. In practice, not every sample in a data set has the same importance in cluster analysis. Therefore, it is in...

Governments and authorities worldwide consider road traffic crashes (RTCs) to be a major concern. These incur losses in terms of productivity, property, life. For country establish its action plans, it is crucial comprehend the reasons for consequences collisions. The main objective this research study was evaluate rank important supporting factors influencing on road. To identify most signific...

The Award Committee – Steffen Dereich, TU Berlin, Germany, and Frances Kuo, University of New South Wales, Australia — determined that the following two papers exhibited exceptional merit and therefore awarded the prize to: AickeHinrichs, for paper ‘‘Optimal importance sampling for the approximation of integrals’’, which appeared in April, 2010, vol. 26, pp. 125–134. Simon Foucart, Alain Pajor,...

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We study the combination problem for credal sets via the robust Bayesian combination operator. We extend Walley’s notion of degree of imprecision and introduce a measure for degree of conflict between two credal sets. Several examples are presented in order to explore the behavior of the robust Bayesian combination operator in terms of imprecision and conflict. We further propose a discounting ...

The present paper examines the microfoundations of how households form subjective expectations about the macroeconomy. In particular, we are interested in the role of perceived news. The paper outlines a theoretical model where households may give unequal importance (or weights) to „good‟ and „bad‟ news. We also consider whether the relationship is state-varying and has any structural changes. ...

Optical strain characterizes the relative amount of displacement by a moving object within a time interval. Its ability to compute any small muscular movements on faces can be advantageous to subtle expression research. This paper proposes a novel optical strain weighted feature extraction scheme for subtle facial micro-expression recognition. Motion information is derived from optical strain m...

This paper presents a new k-means type clustering algorithm that can calculate weights to the variables. This method is efficient for dynamic data streams in order to overcome the global optimum problems. The variable weights produced by the algorithm measures the importance of variable in clustering and can be used in variable selection in which the data items with similar properties are group...