27330707
Some recent advances on the possibility measure theory
29035045
Genetic algorithms for determining fuzzy measures from data
A synthetic evaluation of a given object in terms of multiple factors that contribute to some feature of the object (quality, performance, etc.) may be regarded as a system with multiple inputs and one output. Traditionally, the output is expressed as the weighted average of the inputs. Unfortunately, this method is severely limited as it cannot capture any inherent relation among the factors involved. This limitation can be overcome by using the Choquet integral or the fuzzy integral with respect to a fuzzy measure that captures the relation among the factors. The crux of this method is to determine the right fuzzy measure. In this paper, we describe an efficient genetic algorithm for constructing a suitable fuzzy measure from relevant input-output data. This algorithm has a broad applicability in various problem areas, such as decision making, cluster analysis, pattern recognition, image and speech processing, and expert systems.
28890
Extension of Lower Probabilities and Coherence of Belief Measures
Coherence is an important concept which is introduced and discussed in a new mathematics branch, Imprecise Probability Theory. By using the Choquet integral, belief measures can be extended to be coherent lower previsions on the linear space consisting of all bounded functions. As a special case, we establish that all belief measures are coherent imprecise probabilities.
1885677
Learning nonlinear multiregression networks based on evolutionary computation
This paper describes a novel knowledge discovery and data mining framework dealing with nonlinear interactions among domain attributes. Our network-based model provides an effective and efficient reasoning procedure to perform prediction and decision making. Unlike many existing paradigms based on linear models, the attribute relationship in our framework is represented by nonlinear nonnegative multiregressions based on the Choquet integral. This kind of multiregression is able to model a rich set of nonlinear interactions directly. Our framework involves two layers. The outer layer is a network structure consisting of network elements as its components, while the inner layer is concerned with a particular network element modeled by Choquet integrals. We develop a fast double optimization algorithm (FDOA) for learning the multiregression coefficients of a single network element. Using this local learning component and multiregression-residual-cost evolutionary programming (MRCEP), we propose a global learning algorithm, called MRCEP-FDOA, for discovering the network structures and their elements from databases. We have conducted a series of experiments to assess the effectiveness of our algorithm and investigate the performance under different parameter combinations, as well as sizes of the training data sets. The empirical results demonstrate that our framework can successfully discover the target network structure and the regression coefficients.
2505136
Indeterminate integrals with respect to nonadditive measures
Recently, nonadditive set functions have been used in information fusion and data mining to describe the interaction among the predictive attributes. In this case, replacing the traditional weighted average or, more generally, the linear mapping from a higher dimensional space to a one-dimensional space, relevant nonlinear integrals should be used as the aggregation tool to express how the objective attribute depends on predictive attributes. Several different types of nonlinear integral, such as the Choquet integral and the Wang integral, have been discussed in literature. In these models, the objective attribute is the integral, while the predictive attributes are the integrand. In this paper, a new concept of indeterminate integral is introduced when the universe of discourse is finite. It is a family of integrals including nonlinear integrals mentioned above and, therefore, possesses a large adaptability as a new aggregation tool. Each specified type of indeterminate integral can be obtained from the family of indeterminate integrals by specifying a decomposition of the integrand. Such a new aggregation tool can be used in information fusion and data mining as well as in expert systems.
8746593
Modal logic interpretation of Dempster-Shafer theory: An infinite case
Abstract A modal logic interpretation of belief and plausibility measures defined on infinite sets is established. As a special case, a modal logic interpretation of necessity and possibility measures defined on infinite sets is also established. It is proven in both cases that the interpretation is complete. These results establish, in effect, modal logic interpretations of the Dempster-Shafer theory and possibility theory.
10182592
A Software Component Model and Its Preliminary Formalisation
A software component model should define what components are, and how they can be composed. That is, it should define a theory of components and their composition. Current software component models tend to use objects or port-connector type architectural units as components, with method calls and port-to-port connections as composition mechanisms. However, these models do not provide a proper composition theory, in particular for key underlying concepts such as encapsulation and compositionality. In this paper, we outline our notion of these concepts, and give a preliminary formalisation of a software component model that embodies these concepts.
15745002
Blind measurement of blocking artifacts in images
The objective measurement of blocking artifacts plays an important role in the design, optimization, and assessment of image and video coding systems. We propose a new approach that can blindly measure blocking artifacts in images without reference to the originals. The key idea is to model the blocky image as a non-blocky image interfered with a pure blocky signal. The task of the blocking effect measurement algorithm is then to detect and evaluate the power of the blocky signal. The proposed approach has the flexibility to integrate human visual system features such as the luminance and the texture masking effects.
27067527
A faster method for modeling virtual colony
A virtual colony composed by vivid personal characters with different facial texture and body size, will strongly enhance the reality of the whole virtual environment. This paper describes a fast, economic but realistic method for modeling virtual colony. The system has two major components: photographs based human model reconstruction and anthropometry based automatic human model edit, both of them were advanced to achieve more practical and realistic purpose. To demonstrate the power of this approach, the method was applied to generate some virtual colonies.
18764674
Image information restoration based on long-range correlation
A new class of image information restoration algorithms, virtually different from traditional techniques, is proposed. In comparison with other approaches, our methods use not only the information in local areas, but also that in the remote regions of the image. The methods originate from the idea that there exists abundant long-range correlation within natural images and the human vision system, composed of our eyes and brains, can sufficiently utilize such types of information redundancy to implement the functions of image interpretation, representation, restoration, enhancement and error concealment. Our general approach can be summarized as five basic steps: fetching, searching, matching, competing and recovering. The experimental results on several practical applications show that our methods perform substantially better than many other state-of-the-art methods.
17941589
Novel integrated optical router for microphotonic switching
In this paper, a novel integrated optical beam router for microphotonic switching is presented. The router uses a piecewise linear optic that steers and couples optical collimated beams to optical fibre ports with minimum loss and excellent tolerance to fluctuations in design parameters. Experimental results show that for a 1/spl times/2 MicroPhotonic switch, fibre-to-fibre optical coupling loss less than 1.05 dB and insertion loss uniformity better than 0.2 dB can be achieved, and the measured loss penalty for changes /spl plusmn/0.5 mm in component position is negligible.