Search results for "Knowledge based systems"
showing 9 items of 29 documents
Learning automata-based solutions to the optimal web polling problem modelled as a nonlinear fractional knapsack problem
2011
Accepted version of an article from the journal: Engineering Applications of Artificial Intelligence. Definitive published version on Elsevier Science Direct: http://dx.doi.org/10.1016/j.engappai.2011.05.018 We consider the problem of polling web pages as a strategy for monitoring the world wide web. The problem consists of repeatedly polling a selection of web pages so that changes that occur over time are detected. In particular, we consider the case where we are constrained to poll a maximum number of web pages per unit of time, and this constraint is typically dictated by the governing communication bandwidth, and by the speed limitations associated with the processing. Since only a fra…
Service selection in stochastic environments: a learning-automaton based solution
2011
Published version of an article from the journal: Applied Intelligence. Also available from the publisher on SpringerLink: http://dx.doi.org/10.1007/s10489-011-0280-5 In this paper, we propose a novel solution to the problem of identifying services of high quality. The reported solutions to this problem have, in one way or the other, resorted to using so-called “Reputation Systems” (RSs). Although these systems can offer generic recommendations by aggregating user-provided opinions about the quality of the services under consideration, they are, understandably, prone to “ballot stuffing” and “badmouthing” in a competitive marketplace. In general, unfair ratings may degrade the trustworthine…
Optimal “anti-Bayesian” parametric pattern classification for the exponential family using Order Statistics criteria
2012
Published version of a chapter in the book: Image Analysis and Recognition. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-642-31295-3_2 This paper reports some pioneering results in which optimal parametric classification is achieved in a counter-intuitive manner, quite opposed to the Bayesian paradigm. The paper, which builds on the results of [1], demonstrates (with both theoretical and experimental results) how this can be done for some distributions within the exponential family. To be more specific, within a Bayesian paradigm, if we are allowed to compare the testing sample with only a single point in the feature space from each class, the optimal Bayesian strat…
On using prototype reduction schemes to optimize locally linear reconstruction methods
2012
Authors version of an article published in the journal: Pattern Recognition. Also available from the publisher at: http://dx.doi.org/10.1016/j.patcog.2011.06.021 This paper concerns the use of prototype reduction schemes (PRS) to optimize the computations involved in typical k-nearest neighbor (k-NN) rules. These rules have been successfully used for decades in statistical pattern recognition (PR) [1,15] applications and are particularly effective for density estimation, classification, and regression because of the known error bounds that they possess. For a given data point of unknown identity, the k-NN possesses the phenomenon that it combines the information about the samples from a pri…
On the pattern recognition and classification of stochastically episodic events
2012
Published version of a chapter published in the book: Transactions on Compuational Collective Intelligence VI. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-642-29356-6_1 Researchers in the field of Pattern Recognition (PR) have traditionally presumed the availability of a representative set of data drawn from the classes of interest, say ω 1 and ω 2 in a 2-class problem. These samples are typically utilized in the development of the system’s discriminant function. It is, however, widely recognized that there exists a particularly challenging class of PR problems for which a representative set is not available for the second class, which has motivated a great deal of…
Tracking the Preferences of Users Using Weak Estimators
2011
Published version of am article from the book:AI 2011: Advances in Artificial Intelligence. Also available from the publisher on SpringerLink:http://dx.doi.org/10.1007/978-3-642-25832-9_81 Since a social network, by definition, is so diverse, the problem of estimating the preferences of its users is becoming increasingly essential for personalized applications which range from service recommender systems to the targeted advertising of services. However, unlike traditional estimation problems where the underlying target distribution is stationary, estimating a user’s interests, typically, involves non-stationary distributions. The consequent time varying nature of the distribution to be trac…
Fuzzy reliable tracking control for flexible air-breathing hypersonic vehicles
2011
Published version of an article in the journal: International Journal of Fuzzy Systems. Also available from the publisher: http://www.ijfs.org.tw/ In this paper, we present a fuzzy reliable tracking control design method for flexible air-breathing hypersonic vehicles (FAHVs) subject to disturbances and possible sensor/actuator failures. This problem is challenging due to the strong coupling effects, variable operating conditions and possible failures in FAHVs. First, Takagi-Sugeno (T-S) fuzzy model isused to represent the longitudinal dynamics model of FAHVs. Then, by considering the disturbances and the faults, the fuzzy reliable tracking problem is proposed, and the tracking control probl…
Networking logistic neurons can yield chaotic and pattern recognition properties
2011
Accepted version of an article the book: 2011 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications (CIMSA) Proceedings. Published version available from IEEE: http://dx.doi.org/10.1109/CIMSA.2011.6059914 Over the last few years, the field of Chaotic Neural Networks (CNNs) has been extensively studied because of their potential applications in the understanding/recognition of patterns and images, their associative memory properties, their relationship to complex dynamic system control, and their capabilities in the modeling and analysis of other measurement systems. However, the results concerning CNNs which can demonstrate chaos, quasi-chaos, …
Knowledge organization for modelling workflows in Taverna environment
2014
Today Workflow Management Systems (WFMS), like Taverna and Kepler, have a very important place in the everyday work of the scientist. These tools support the access to computational resources and act as interface for building complex data processing chains. The next step is to support decisions of the researcher on autonomously developing workflow parts guided by requirements of the scientist while she/he is working on the high-level goal of the experiment. To this aim, it is necessary an ontology to store the knowledge related to the experiments and tools used, and to make this knowledge available not only to the scientist, but also to a suitable artificial intelligent system. In this pape…