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2nd international conference on intelligent data engineering and automated learning, IDEAL 2000

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2nd international conference on intelligent data engineering and automated learning, IDEAL 2000

ISBN: (纸本)3540414509

The proceedings contain 82 papers. The special focus in this conference is on data Mining, Financial engineering and intelligent Agents. The topics include: Analyses on the generalised lotto-type competitive learning;extended k-means with an efficient estimation of the number of clusters;an interactive approach to building classification models by clustering and cluster validation;a new nonhierarchical clustering procedure for symbolic objects;information-based classification by aggregating emerging patterns;a new algorithm to select learning examples from learning data;data ranking based on spatial partitioning;visualisation of temporal interval association rules;fuzzy hydrocyclone modelling for particle separation using fuzzy rule interpolation;observational learning with modular networks;a note on learning automata based schemes for adaptation of BP parameters;a general class of neural networks for principal component analysis and factor analysis;integrating KPCA with an improved evolutionary algorithm for knowledge discovery in fault diagnosis;nonlinear and noisy time series prediction using a hybrid nonlinear neural predictor;wavelet methods in PDE valuation of financial derivatives;fast algorithms for computing corporate default probabilities;applying mutual information to adaptive mixture models;feature selection for support vector machines in financial time series forecasting;a computational framework for convergent agents;building an ontology for financial investment;a multi-agent negotiation algorithm for load balancing in CORBA-based environment and combining exploitation-based and exploration-based approach in reinforcement learning.

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A fault classification method by RBF neural network with OLS learning procedure [PowerPoint Presentation]

A fault classification method by RBF neural network with OLS...

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Power Industry Computer Application conference (PICA)

作者： W.M. Lin C.D. Yang J.H. Lin M.T. Tsay

A collection of slides from the author's powerpoint conference presentation is provided. The presentation highlights the RBF artificial neural network (ANN); OLS learning procedure; development of the proposed ANN... 详细信息

ISBN: (纸本)0780366816

关键词： Neural networks Artificial neural networks Protection Protective relaying intelligent networks Testing Fault detection Fault location Network topology Radial basis function networks

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intelligent decision support for protection scheme design associated with electrical transmission systems

Intelligent decision support for protection scheme design as...

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Power Industry Computer Application conference (PICA)

作者： G.M. West S.M. Strachan A. Moyes J.R. McDonald Centre for Electrical Power Engineering University of Strathclyde Glasgow UK

ISBN: (纸本)0780366816

This paper focuses on collaborative research activities conducted with two major UK utilities, describing the development of a web-based, Design engineering Knowledge Application System (DEKAS). This system offers automatic intelligent decision support to engineers responsible for the design and application of protection schemes associated with EHV transmission power systems. A web-based environment is promoted as the most effective medium for company-wide dissemination of the information and, knowledge captured within DEKAS. The paper also describes the integration of DEKAS with existing company data repositories in order to provide a single storage and retrieval mechanism for all pertinent information/documentation. Following the identification of 'what', 'where' and 'when' information and data are utilised within the overall protection design process, the paper then concentrates on 'how' better use can be made of existing engineering resources, through the development of an intelligent decision support facility, utilising case-base reasoning (CBR) techniques.

关键词： Design engineering Knowledge engineering Documentation Power engineering and energy Process design data engineering Power system protection Collaboration intelligent systems Information retrieval

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intelligent virtual systems in learning

Intelligent virtual systems in learning

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22nd Annual international conference of the IEEE-engineering-in-Medicine-and-Biology-Society

作者： Spasic, VA Univ Belgrade Ctr Multidisciplinary Studies YU-11000 Belgrade Yugoslavia

ISBN: (纸本)0780364651;078036466X

Computer Assisted learning (CAL) in it's wide range of methods, successfully merges with many new fields of research. One is the field of Artificial Intelligence which strongly supports development of intelligent Computer Assisted learning (ICAL), We have developed our approach to intelligent tutoring implemented as ICAL, Approach can be described as intelligent computerized speaking tutor that supports learning based on experiments with virtual dynamic systems. Approach is suitable for learning the behavior of any dynamic system, especially in the field of complex, live, bio-medical systems. We are now implementing this approach in the field of biomedicine. Two important systems are our virtual system GLUCOMAT - homeostatic glucose regulation in human, and ECBLOG - population growth in natural eco-system.

关键词： virtual systems virtual experiment artificial speech AI ICAL

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Modeling of neumuscular blockade system using neural networks

Modeling of neumuscular blockade system using neural network...

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22nd Annual international conference of the IEEE-engineering-in-Medicine-and-Biology-Society

作者： Najarian, K Dumont, GA Davies, MS Univ British Columbia Dept Elect & Comp Engn Vancouver BC V6T 1Z4 Canada

ISBN: (纸本)078036466X

Delivering drugs for muscle relaxation if;known to be a delicate process, which is highly nonlinear in nature. On of the most commonly-used drugs to create neurmucular blockade is atricurium. Here, we develop a dynamic neural network to model neuromuscular blockade system when atricurium is used for paralysis. The minimum-complexity neural modeling algorithm used here is based on the PAC learning theory and is shown to perform similarly on the testing and training data. The resulting model is proved to be stochastically stable and can be used as a reliable and accurate model of neuromuscular blockade system.

关键词： neuromuscular blockade drug delivery systems sigmoid neural networks PAC learning theory nonlinear ARX models

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A real-time novelty detector for artefact identification in physiological measurements.

A real-time novelty detector for artefact identification in ...

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22nd Annual international conference of the IEEE-engineering-in-Medicine-and-Biology-Society

作者： Beatty, PCW Hoare, SW Asbridge, D Univ Manchester Div Imaging Sci & Biomed Engn Manchester Lancs England

ISBN: (纸本)078036466X

We report the design of a kernel-based on-line novelty detector (ADDaM - Automatic Dynamic data Mapper) and its use in the detecting of artefacts in physiological data streams gathered during general anaesthesia. ADDaM is an on-line method, that produces a robust and principled statistically partitioned history of any ordered data stream. It then constructs a probability distribution function (PDF) of the values in the stream by placing suitable Gaussian kernels at the centres of each of the partitions. The novelty of the next point entering the stream is assessed by testing against the current PDF. The more novel the point the more likely it is to be an artefact. The partitions and the PDFs are then updated after the novelty of each new point is assessed. The performance of this method is compared with artefact detection using both conventional on and off-line methods including Kalman filters, ARIMA and moving median or mean methods. The study shows that the performance of our novelty detector is as least as good as the best alternative on or off-line methods. Typical, error rates for artefact identification of 9.2% were achieved by ADDaM, compared with 16.5% for the best Kalman filtering, 9.3% for the best ARIMA model tested, 5.3% for the best moving mean method and 9.6% for the best moving median method.

关键词： artefact identification novelty detection intelligent filtering

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intelligent management of processes in a ICU telemedicine system

Intelligent management of processes in a ICU telemedicine sy...

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22nd Annual international conference of the IEEE-engineering-in-Medicine-and-Biology-Society

作者： Dafonte, C Gómez, A Arcay, B Taboada, JA Univ A Coruna Fac Informat Dept Comp Sci A Coruna 15071 Spain

ISBN: (纸本)078036466X

This work presents a project of telemedicine applied to Intensive Care Units (ICUs). The implemented communications scheme can be adapted to patients interned in an ICU as well as to remote patients connected to the principal hospital through the communication lines. The developed system also provides maximal flexibility on the physical level allowing ISDN, ADSL, ATM and dedicated lines. This project focuses on the acquisition of medical data, the management of the communications and the visualization and posterior analysis of the data. It also includes a series of multimedia options that facilitate the collaboration during the diagnosis: use of videoconferences following video compression protocols (H.323), collaborative whiteboard (norm T.120), visualization of graphic files related to the patient, transmission of files by means of sockets, etc. The global system follows the IEEE MW P-1073 standard, which it improves by including the acquisition of analog signals and to which it adds a component of intelligent monitoring using a knowledge based system (alarm check, tendencies analysis, communications control, etc.). The system disposes oil an intelligent module (rules based system developed in OPS/R2) charged with the management of the communication between the different processes, with the data transmission priorities, the bandwidth management, the management of the charge between various resources, etc.

关键词： telemedicine monitoring ICU visualization multimedia

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Combining data from different algorithms to segment the skin-air interface in mammograms

Combining data from different algorithms to segment the skin...

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22nd Annual international conference of the IEEE-engineering-in-Medicine-and-Biology-Society

作者： Masek, M Attikiouzel, Y deSilva, CJS Univ Western Australia Dept Elect & Elect Engn Ctr Intelligent Informat Proc Syst Perth WA 6907 Australia

ISBN: (纸本)078036466X

This paper presents a method For combining several different estimates of the mammographic skin-air interface In order to eliminate noise inherent to each individual segmentation algorithm, Given that each algorithm provides a binary mask of the breast, the first step is to isolate pixels adjacent to the skin-air interface. A final estimate of the skin-air interface for each point results from the combination of skin-air Interface location data from each procedure. data for each point is grouped as a set, upon which statistical operators, such as the elimination of outliers, are applied. Since the skin-air interface Is a continuous line, data from prior points is also used as an estimate of points that follow. Results are evaluated in terms of success with the combination of two skin-air interface segmentation algorithms. The resulting 'hybrid' technique overcomes several problems that beset each individual algorithm.

关键词： mammogram skin-air interface

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Observational learning with modular networks 2

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2nd international conference on intelligent data engineering and automated learning, IDEAL 2000

作者： Shin, Hyunjung Lee, Hyoungjoo Cho, Sungzoon Department of Industrial Engineering Seoul National University San56-1 ShilimDong Kwanakgu Seoul151-742 Korea Republic of

ISBN: (纸本)3540414509

Observational learning algorithm is an ensemble algorithm where each network is initially trained with a bootstrapped data set and virtual data are generated from the ensemble for training. Here we propose a modular OLA approach where the original training set is partitioned into clusters and then each network is instead trained with one of the clusters. Networks are combined with different weighting factors now that are inversely proportional to the distance from the input vector to the cluster centers. Comparison with bagging and boosting shows that the proposed approach reduces generalization error with a smaller number of networks employed. © Springer-Verlag Berlin Heidelberg 2000.

关键词： learning algorithms

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Real-time web data mining and visualisation 2

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2nd international conference on intelligent data engineering and automated learning, IDEAL 2000

作者： Li, Bai Ni, Guohua School of Computer Science and Information Technology The University of Nottingham NottinghamNG8 1BB United Kingdom

ISBN: (纸本)3540414509

This paper presents new services for intelligent monitoring and visualising user accesses to a university’s web site. These are based on the use of data mining techniques to process data recorded in the web log files and visualise it. The system is to be used by the University of Nottingham's web server to monitor the interests of potential students and to predict the student numbers and their geographical distributions for the next academic year. The system could be adapted for other academic and commercial web sites to assist intelligent decision making. © Springer-Verlag Berlin Heidelberg 2000.

关键词： Websites

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