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Computational Cybernetics, 2005. ICCC 2005. IEEE 3rd International Conference on

Date 13-16 April 2005

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Displaying Results 1 - 25 of 74
  • Thesaurus in user interface - optimum presentation of thesauri

    Publication Year: 2005 , Page(s): 175 - 180
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (360 KB) |  | HTML iconHTML  

    When thesauri are used in online applications, their efficiency can be increased significantly. This requires an appropriate user interface. The designers of data bases are, however, not in the possession of information about neither the use of thesauri nor other authority files at a satisfactory level. Programs created till now support the search only in a poor form, via primitive indices. The aim of the present paper is to give ergonomically suitable and more precise requirements. View full abstract»

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  • Reconstruction of planar graphs from their centered triangulations in some spatio-relational models

    Publication Year: 2005 , Page(s): 181 - 185
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (281 KB) |  | HTML iconHTML  

    In this paper we continue the investigation of an interoperability problem and its complexity in connection with spatio-relational database models. The result, however, is also interesting from the point of view of graph theory, since the main result is that there is a linear-time algorithm for deciding whether a given triangulation can be seen as a centered triangulation of a certain planar graph. View full abstract»

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  • The use of genetic algorithms and neural networks to approximate missing data in database

    Publication Year: 2005 , Page(s): 207 - 212
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (275 KB) |  | HTML iconHTML  

    Missing data creates various problems in analysing and processing data in databases. In this paper we introduce a new method aimed at approximating missing data in a database using a combination of genetic algorithms and neural networks. The proposed method uses genetic algorithm to minimise an error function derived from an auto-associative neural network. Multi-layer perceptron (MLP) and radial basis function (RBF) networks are employed to train the neural networks. Our focus also lies on the investigation of using the proposed method in accurately predicting missing data as the number of missing cases within a single record increases. It is observed that there is no significant reduction in accuracy of results as the number of missing cases in a single record increases. It is also found that results obtained using RBF are superior to MLP. View full abstract»

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  • American option pricing using Bayesian multi-layer perceptrons and Bayesian support vector machines

    Publication Year: 2005 , Page(s): 219 - 224
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (422 KB) |  | HTML iconHTML  

    An option is the right, not the obligation, to buy or sell an underlying asset at a later date but by fixing the price of the asset now. There are European and American styled options. European styled options can be priced using the Black-Scholes equations but American options are more complex and valuable due to the second random process they introduce. Multi-layer perceptrons and support vector machines have been used previously to price American options and what is introduced here is Bayesian techniques to both these approaches. Bayesian techniques used with both these approaches are compared in terms of pricing accuracy and time to train each of the learning algorithms. It was found that Bayesian SVM's out-performed Bayesian MLP's and that there is scope for further work. However, Bayesian SVM's took much longer to train than Bayesian MLP's even though they produced better error results. View full abstract»

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  • A fuzzy controller to overcome saturation non-linearity

    Publication Year: 2005 , Page(s): 53 - 56
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (192 KB) |  | HTML iconHTML  

    Gate limitation in a hydroelectric plant can deteriorate the performance of the system by causing large overshoot and settling time. In this paper, a fuzzy controller is used to cope with the problem of saturation in an isolated hydroelectric generating unit. A linear stable model of the system under consideration is developed to study the load and frequency control problem and the performance of the system is studied when the governor controlled gate is subjected to saturation. A fuzzy controller is then incorporated into to system to improve the performance. Simulation results obtained show the effectiveness of the controller. View full abstract»

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  • Monitoring financial market using French written textual data

    Publication Year: 2005 , Page(s): 239 - 242
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (255 KB) |  | HTML iconHTML  

    This paper describes the implementation of a French language information extraction system that can extract key terms from French written financial texts to provide information regarding direction of market trend. The aim is to reduce reading workload on financial investors, especially in stock market business, whereby large amount of available textual data is to be assimilated and interpreted in a limited period of time. Results obtained show that accuracy of the technique employed in information extraction is very promising and can very well be considered as an important step in advanced applications like information management and knowledge discovery from textual data. View full abstract»

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  • On-line optimizing neural networks for Kalman filtered real-time identification

    Publication Year: 2005 , Page(s): 303 - 307
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (250 KB) |  | HTML iconHTML  

    The questions addressed in this paper concern the applicability of system parameters recursive identification using neural networks as well as a method how the exposed problems can be reduced to a standard formulation using dual heuristic dynamic programming and back-propagation training. Some background materials are presented on the recursive least-square methods and task-determination of neural network structure, formulated in terms of generalized linear quadratic control. The results arise with such representation and their training capability could be useful in dynamic systems for adaptive identification and control. View full abstract»

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  • Fractional order adaptive control for hydraulic differential cylinders

    Publication Year: 2005 , Page(s): 225 - 229
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (298 KB) |  | HTML iconHTML  

    Hydraulic servo valve controlled differential cylinders are non-linear, strongly coupled multivariable electromechanical tools applicable for driving e.g. manipulators. Traditional PID control of such equipment have to cope with the problem of instabilities due to the friction forces between the piston and the cylinder, and the uncertainties and variation of its hydrodynamic parameters that in general makes it unrealistic to develop an accurate model for them. Brocker and Lemmen proposed two different control approaches for such systems, based on the disturbance rejection, and on the partial flatness principles, respectively. In each case it is necessary to measure the external disturbance force and its time-derivative as well as to know the exact model of the hydraulic cylinder. Later on Tar et al. proposed an alternative adaptive approach that does not require to measure the disturbance force and to know the exact parameters of the cylinder. This method rejected to use time-derivatives because of the presence of friction, and, as a consequence it resulted in a very hectic transient phase of learning. In this paper an alternative approach is presented that combines this approach with the use of calculated time-derivatives that are "rejected" by adaptively varying the order of the derivations applied. In this way the harsh initial transients can be evaded. The operation of the method is presented by simulations. View full abstract»

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  • The effect of varying parameters on performance for adaptive agents in technical equity market trading

    Publication Year: 2005 , Page(s): 243 - 248
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (368 KB) |  | HTML iconHTML  

    This paper investigates the impact of varying the quantity of data and the number of generations run for every re-training step in an adaptive trading system. Using historical equity data, populations of agents are continuously retrained and assessed based on their performance across an out-of-sample data set. Comparison was performed using three test sets, for which each had one variable altered for every run. Results showed significant differences in performance when varying the number of trading days, while no difference was found when varying generations. View full abstract»

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  • Investigation of a round circular cylinder in case of high Reynolds number around

    Publication Year: 2005 , Page(s): 309 - 312
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (149 KB) |  | HTML iconHTML  

    This paper is the first part of a series of studies where we examine several methods for the solution of the boundary layer equation of the fluid mechanics. The first of these is the analytical or rather quasi analytical method due to Blasius. This method reduces a system of partial differential equations to a system of ordinary differential equations and these in turn are solved by numerical methods since no exact solution of the Blasius type equations is known. We determined all the Blasius equation necessary for up to 11-th order approximation. Our further aim to study the finite difference numerical solutions of the boundary layer equation and some of the methods applying weighted residual principles and by comparing these with the "exact" solutions arrived at by Blasius method develop a quick reliable method for solving the boundary layer equation. View full abstract»

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  • TP model transformation in non-linear system control

    Publication Year: 2005 , Page(s): 111 - 119
    Cited by:  Papers (7)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (437 KB) |  | HTML iconHTML  

    The main objective of the paper is to study the recently proposed tensor product distributed compensation (TPDC) based design framework in the case of observer and controller design. The TPDC links the TP model transformation and the parallel distributed compensation (PDC) framework. The study is conducted trough the output feedback control design of the prototypical aeroelastic wing section that is used for the theoretical as well as experimental analysis of two-dimensional aeroelastic behavior and exhibits limit cycle oscillation without control effort. The control strategy is based on a state feedback controller and an observer to estimate the available state values. View full abstract»

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  • Detection of epileptiform activity in human EEG signals using Bayesian neural networks

    Publication Year: 2005 , Page(s): 231 - 237
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (425 KB) |  | HTML iconHTML  

    In this paper, we investigate the application of neural networks to the problem of detecting inter-ictal epileptiform activity in the electroencephalogram (EEG). The proposed detector consists of a segmentation, feature extraction and classification stage. For the feature extraction stage, coefficients of the discrete wavelet transform (DWT), real and imaginary parts of the fast Fourier transform and raw EEG data were all found to be well-suited to EEG classification. Principal component analysis was used to reduce the dimensionality of the features. For the classification stage, multi-layer perceptron neural networks were implemented according to maximum likelihood and Bayesian learning formulations. The latter was found to make better use of training data and consequently produced better trained neural networks. Rejection thresholds of 0.9 were applied to the network output as a doubt level in order to ensure that only reliable classification decisions are made. A maximum classifier accuracy of 95,10% was achieved with 24,97% of patterns not being classified. Bayesian moderated outputs could not improve on these classification predictions significantly enough to warrant their added computational overhead. View full abstract»

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  • Perceptive awareness in building automation

    Publication Year: 2005 , Page(s): 259 - 264
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (386 KB) |  | HTML iconHTML  

    In this paper, we introduce a system that uses a bionic approach to process the information obtained from a large number of diverse sensors. By means of the process of symbolization, the amount of information to be processed is drastically reduced, and used to create an inner representation of the real world. Three different applications involving human actions in a building are introduced and briefly discussed. It is argued that by making use of microsymbols, the proposed approach leads to greater flexibility, able to adapt to changing sensor inputs in an intelligent way. View full abstract»

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  • Construction and control of a high precision co-ordinate table

    Publication Year: 2005 , Page(s): 67 - 70
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (191 KB) |  | HTML iconHTML  

    With the appearance of micromachined mechanical elements and nanotechnology increased demand can be observed for coordinate tables having submicron position accuracy. The paper describes the construction of a small (100×100mm) high precision (0,01 μm resolution, less then 0,1 μm measuring accuracy over the full range) coordinate table. It was decided to design a modular system with independent metrological and structural frames. The construction enables the application of various measuring element like optical grid or laser interferometer combined with capacitive sensors to supervise the gap between the table and the guiding surface. The table was developed as part of an optical co-ordinate measuring machine intended for the quality control of filaments and filament assemblies for energy saving bulbs. View full abstract»

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  • Fuzzy and anytime signal processing approaches for supporting modeling and control of transportation systems

    Publication Year: 2005 , Page(s): 339 - 344
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (413 KB) |  | HTML iconHTML  

    Nowadays, in solving control problems, the processing of the information always involves some kind of measurement and signal processing tasks, as well. This fact has pressed experts focus more deeply on modeling and signal processing techniques and to apply non-classical, artificial intelligence, and soft computing based methods to overcome problems arising from the increased complexity of the today's systems. In this paper, the author shows that measurement and signal processing problems of now-a-days open new dimensions for the interpretation of the basic concepts of measurement and signal processing and make the reevaluation of these concepts necessary. Traditional methods fail in many cases to yield useful solutions, especially when measurement and signal processing problems reveal considerable complexity, involve a wide spectrum of various disciplines and require a multitude of components and methods. The paper gives a brief overview of various imprecise computational methods and discusses their applicability to treat complex modeling, signal processing, and control problems. View full abstract»

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  • Managing the development of a regional e-administration network with academic expertise

    Publication Year: 2005 , Page(s): 319 - 324
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (438 KB) |  | HTML iconHTML  

    This paper presents several aspects of developing an integrated regional e-administration system, by adding "pieces" successively developed under the frame of two PHARE projects. These projects have a consistent technical background, result of the strong implication of the local academics. Due to this implication, a unitary approach ensures the continuity and the integration of the results of these projects into a coherent, useful system. The first project is an interactive map, based on Java technology. The other project has as a result a document-oriented, data collecting network that ensures the link between the Timis County Council and the local administration and is based on Lotus technology. Several considerations about the management of the involvement of the academic expertise in this domain are presented and conclusions are yielded. View full abstract»

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  • Optimising the verification of patient positioning in proton beam therapy

    Publication Year: 2005 , Page(s): 279 - 284
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (385 KB) |  | HTML iconHTML  

    A new patient positioning system incorporating a robotic arm is currently being designed for proton beam therapy. This requires aligning a treatment image with a pre-defined reference image. This is achieved by the alignment of the radiation and reference field boundaries, followed by registering the patient's anatomy relative to the boundary. This paper compares and tests methods for both field boundary and anatomy alignment. For field boundary alignment, it is proposed to use a powerful object detection algorithm known as the generalised Hough transform (GHT). It was found that the GHT algorithm, followed by an optimisation routine, worked successfully and overcame problems in existing solutions. For anatomical-body alignment, a number of intensity-based similarity measures and optimisation routines are tested. It was found that the genetic algorithm, minimising the correlation coefficient similarity measure worked the best. View full abstract»

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  • A framework for agent-based modeling of communication and knowledge networks in corporate R&D

    Publication Year: 2005 , Page(s): 133 - 138
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (444 KB) |  | HTML iconHTML  

    Recent changes in business environment call for thorough studying of communication and knowledge in corporate R&D activity. The paper defines knowledge (corporate R&D) networks and describes them as complex systems. Agent-based modeling is offered as a tool for studying these knowledge networks. A choice of transactive memory theory for defining the rules of agents' interactions is justified. View full abstract»

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  • Potential-based fuzzy clustering and cluster validity for categorical data and its application in modeling cultural data

    Publication Year: 2005 , Page(s): 81 - 86
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (288 KB) |  | HTML iconHTML  

    This paper introduces a novel hierarchical fuzzy algorithm for clustering categorical attributes, which consists of three basic design steps. It incorporates a potential-based clustering scheme with a cluster validity index into a framework that is based on the use of the weighted fuzzy c-modes. The novelty of the contribution lies in the following properties: (a) the potential-based clustering scheme reduces the dependence of the algorithm on initialization, (b) the weighted fuzzy c-modes provides flexibility in detecting the real data structure, and (c) the cluster validity index determines the appropriate number of clusters. The algorithm is applied to model (classify) cultural data related to a number of painters of the seventeenth century, where its performance is compared to the respective performance of an agglomerative hierarchical clustering algorithm. View full abstract»

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  • Intelligent computing for the management of changes in industrial engineering modeling processes

    Publication Year: 2005 , Page(s): 249 - 254
    Cited by:  Papers (9)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (365 KB) |  | HTML iconHTML  

    Advancements in engineering modeling have changed work of engineers during the last two decades. Sophisticated descriptions store information about shape oriented engineering objects and their relationships. Boundary representations of form features constitute shape models. Rules and checks have replaced simple data form of shape model entity attributes. This change of modeling facilitates a next step towards application of computer intelligence at engineering object related decisions. The authors propose a method of intelligent attribute definition for integrated decision assistance environments of modeling systems. This method provides quick and comprehensive assessment of situations for decisions on modification of modeled objects in very complex information environments. The paper starts with an outline of the approach to intelligent decision assistance by the authors. Next, an Internet portal communicated scenario of the proposed modeling is discussed. Following this, multilevel solution for modeling, adding characteristics for engineering objects, and definitions and communications are detailed as essential methods in the proposed modeling. Finally, behaviors for essential classes of modeled objects and an example for the definition of situations and behaviors represent implementation issues. View full abstract»

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  • An optimization model for maintenance of engineering structures

    Publication Year: 2005 , Page(s): 265 - 268
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (196 KB) |  | HTML iconHTML  

    With the recognition that the engineering structures maintenance and repair needs far exceed the resources available to address these needs, many firms have turned to the development of ESMS (engineering structures management system) as a method to improve the allocation of these limited resources and the condition of their engineering structures. The paper provides an overview of the need for ESMS. The concepts of level-of-service goals for functional adequacy, deterioration modeling and the relation of structural adequacy and optimization strategies for resource allocation. View full abstract»

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  • Adaptive peer-to-peer network using semantic relations

    Publication Year: 2005 , Page(s): 195 - 199
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (339 KB) |  | HTML iconHTML  

    The graph structure of a peer-to-peer network defines the neighboring relations between peer nodes. The nodes can issue queries only with the assistance of the graph edges. For that reason it is essential to find the most valuable edges, that is, the edges that provide the most answers for the queries of a given node. However, the basic peer-to-peer protocols construct this graph on a random manner and they do not take the content of the stored or searched documents into account. Our solution improves the performance of a peer-to-peer network by constructing semantic profiles based on document metadata followed by a comparison of the semantic similarities on generalized topics, where these topic generalizations are made with an adaptive algorithm that utilize a well-tried full-language taxonomy. We expect that as time goes on our protocol, the SemPeer, transforms the graph so that neighboring nodes can answer each others queries with greater probability than with the previous graph structures. View full abstract»

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  • Applying intelligent methods in logistics control

    Publication Year: 2005 , Page(s): 71 - 74
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (232 KB) |  | HTML iconHTML  

    The purpose of this research and development project is to construct the foundations of a logistics IT center with a universal and intermodal character, i.e., covering all modes of transportation and corresponding central functions related to warehouses and container terminals. Through its modular structure it is applicable to arbitrary concrete site dependent needs. It also contains intelligent elements, which offer suboptimal solutions to certain classic mathematical optimization problems connected to logistics, acceptable from a practical point of view and tractable in the computer science sense. In order to realize and implement this system, several basic research tasks both in logistics and IT were solved. A model for a logistics center was constructed, suitable for present infrastructural situation in Central and Eastern Europe but compatible with European Union standards. View full abstract»

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  • Multiversion data warehouses: challenges and solutions

    Publication Year: 2005 , Page(s): 139 - 144
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (366 KB) |  | HTML iconHTML  

    A multiversion data warehouse (MVDW) is a promising approach to handling structural changes in external data sources as well as for simulating alternative business solutions. A MVDW is composed of the set of its versions, each of which is in turn composed of a schema version and an instance version. A single version stores a data warehouse state valid in a certain time period or a simulation scenario. In order to manage and analyze multiversion data, new challenging issues are to be solved, that include among others metadata management, schema and data versions management, data sharing, multiversion query languages, and a transactional DW management. These issues are briefly discussed in the paper based on our experience in designing and implementing a multiversion data warehouse management system. View full abstract»

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  • Fuzzy logic based speed control and slip compensation for rotor time constant variations in a field-oriented induction motor drive

    Publication Year: 2005 , Page(s): 57 - 62
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (290 KB) |  | HTML iconHTML  

    Indirect field oriented (IFO) induction motor drives can provide fast dynamic torque response and track rapid changes in reference speed and load torques. However the decoupled control of torque and flux is affected due to variations in the rotor electrical time constant. As a result, the drive performance is seriously degraded, unless some form of adaptation is employed. This paper presents an IFO drive consisting of two fuzzy controllers, which respectively regulate the rotor speed and adjust the applied slip frequency as a result of detuning. The proposed drive is shown to regulate the rotor flux and maintain field orientation under a wide range of rotor time constant variations. View full abstract»

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