PL
 |
EN
Preferencje help
Polish version English version Język
Widoczny [Schowaj] Abstrakt
Liczba wyników

Znaleziono wyników: 13

Liczba wyników na stronie
first rewind previous Strona / 1 next fast forward last
Wyniki wyszukiwania
Wyszukiwano:
w słowach kluczowych:  knowledge-based systems
help Sortuj według:

help Ogranicz wyniki do:
first rewind previous Strona / 1 next fast forward last
1
Content available remote Rule-based controlling of a multiscale model of precipitation kinetics
Macioł Piotr
Computer Methods in Materials Science
|
2018
|
Vol. 18, No. 2
64--78
EN
One of the most important obstacles of widening of multiscale modelling is its high computational demand. It is caused by the fact, that each of numerous fine scale models has comparable computational requirements to a coarse scale one. There are several ways of decreasing of computational time of multiscale models. Adaptation of a structure of a model is one of the most promising. In this paper the Adaptive Multiscale Modelling Methodology is described, including Knowledge-Based adaptation of the multiscale model of precipitation kinetics during heat treatment. Core features of the methodology are introduced. The numerical model of heat treatment of an aluminium alloy based on the methodology and the dedicated framework is presented. Besides modelling of macroscopic heat transfer, models of precipitation kinetics based on thermodynamic calculations are included. To decrease computational requirements arising from coupling of the macroscale model and the thermodynamic models, metamodeling and similarity approaches are applied. Computations with several configuration of rules are described, as well as their results. Reliability and time consumption of computations are discussed. Future perspectives of combining of modelling and metamodeling in one, integrated model are discussed.
2
Content available remote Outlier mining using the DBSCAN algorithm
Nowak-Brzezińska A., Xięski T.
Journal of Applied Computer Science
|
2017
|
Vol. 25, nr 2
53--68
EN
This paper introduces an approach to outlier mining in the context of a real-world dataset containing information about the mobile transceivers operation. The goal of the paper is to analyze the influence of using different similarity measures and multiple values of input parameters for the densitybased clustering algorithm on the number of outliers discovered during the mining process. The results of the experiments are presented in section 4 in order to discuss the significance of the analyzed parameters.
3
Content available remote Outlier mining in rule-based knowledge bases
Nowak-Brzezińska A.
Journal of Applied Computer Science
|
2017
|
Vol. 25, nr 2
7--27
EN
This paper introduces an approach to outlier mining in the context of rule-based knowledge bases. Rules in knowledge bases are a very specific type of data representation and it is necessary to analyze them carefully, especially when they differ from each other. The goal of the paper is to analyze the influence of using different similarity measures and clustering methods on the number of outliers discovered during the mining process. The results of the experiments are presented in Section 6 in order to discuss the significance of the analyzed parameters.
4
Content available Smart product design and production control for effective mass customization in the Industry 4.0 concept
Zawadzki P., Żywicki K.
Management and Production Engineering Review
|
2016
|
Vol. 7, No. 3
105--112
EN
The paper presents a general concept of smart design and production control as key elements for efficient operation of a smart factory. The authors present various techniques that aid the design process of individualized products and organization of their production in the context of realization of the mass customization strategy, which allows a shortened time of development for a new product. Particular attention was paid to integration of additive manufacturing technologies and virtual reality techniques, which are a base of the so-called hybrid prototyping.
5
Content available Semantic Knowledge Engineering - Main Concepts
Nalepa G. J.
Pomiary Automatyka Robotyka
|
2011
|
R. 15, nr 12
236-238
EN
The Semantic Knowledge Engineering approach aims at providing new design and analysis methods for rule-based intelligent systems. It uses the XTT2 knowledge representation for building modularized rule bases that form decision networks. The representation is formalized, thus allowing for the anayslys of the designed system with respect to its qualitative properties. The visual design is supported by practical tools.
PL
Celem podejścia semantycznej inżynierii wiedzy jest dostarczenie nowych metod projektowania i analizy systemów inteligentnych wykorzystujących reprezentację regułową. Podejście to bazuje na metodzie XTT2 służącej do budowania na poziomie logicznym zmodularyzowanej bazy reguł stanowiącej sieć wnioskującą. Metoda ta jest sformalizowana, co pozwala na przeprowadzenie analizy systemu pod kątem jego jakości.
6
Modelling evolution of knowledge-based information technology organization; the concept and perspective
Chabik J., Orłowski C.
Systems Science
|
2010
|
Vol. 36, no 1
27-33
EN
Increasing pressure on improving the efficiency of companies' operations leads to transformation of their Information Technology (IT) organizations from technology-oriented to service-oriented, based on the Information Technology Infrastructure Library (ITIL) model. The evolution of these IT organizations can be supported by the knowledge-based systems centered on the rules determined through aggregation and refinement of existing organizations' evolution and fuzzy logic modelling principles. The paper describes details of building such models and describes its applicability in business practice.
7
Content available remote A decision support system for alternative project choice based on fuzzy neutral networks
Relich M.
Management and Production Engineering Review
|
2010
|
Vol. 1, No. 4
46-54
EN
The paper aims to present possibilities of management support by more precise estimates of critical tasks in projects through the use of intelligent techniques. In this paper a case is considered in which the client is forced to change the project specification after commencement of investment. To minimize the loss, the client may attempt to find other alternative solutions to complete the project. In view of expenditure and investment in progress, a group of alternative projects that fulfill the assumed constraints (e.g. financial and temporal) is sought. To support the choice of alternative projects, estimates of critical tasks within the project are calculated, using intelligent techniques as well as traditional statistical methods. The results are determined using the database of past projects that are found in the information systems of the enterprise.
8
Content available Product configuration use chosen artificial intelligent method
Kutschenreiter-Praszkiewicz I.
Applied Computer Science
|
2010
|
Vol. 6, no 2
71--79
EN
Product adjustment to customer expectation, which means product customization, decides about its commercial success. Developing methods helpful in the early phase of product design is needed to product customization. The aim of this paper is to present application of knowledge-based systems (KBS) in product customization.
9
Content available remote Application of uncertain variables to production planning in a class of manufacturing systems
Gąsior D., Józefczyk J.
Bulletin of the Polish Academy of Sciences. Technical Sciences
|
2009
|
Vol. 57, nr 3
249-256
EN
A production planning problem is addressed in the paper. It consists in the determination of a production plan of products to maximize a total utility connected with their manufacture taking into account a limited amount of resources of different types which are necessary for the production. An uncertain version of the problem is considered when an amount of the resources are not precisely known. The formalism of uncertain variables is proposed in the paper to solve this problem. The solution algorithms for two versions of the uncertain production planning problem are presented. It turned out possible to replace the uncertain problems by their deterministic counterparts. A simple numerical example illustrates the solution algorithms.
10
Content available remote Maryland virtual patient: a knowledge-based, language-enabled simulation and training system
McShane M., Nirenburg S., Jarrell B., Beale S., Fantry G.
Bio-Algorithms and Med-Systems
|
2009
|
Vol. 5, no. 9
57--63
EN
Maryland Virtual Patient (MVP) is system aimed at training medical personnel in certain aspects of clinical medicine. The user plays the role of attending physician and is tasked with diagnosing and treating virtual patients (VPs), with or without the help of a virtual tutor. Each VP is composed of both a realistically functioning physiological side and a reasoning - and language-enabled cognitive side. The former permits the VP to undergo the physiological states and changes associated with diseases, their treatments, and even unexpected external stimuli, such as clinically counterindicated interventions. The latter permits the VP to consciously experience and reason about its disease state, make decisions about its lifestyle and medical care, and discuss all of these with its attending physician (the user). This paper provides a brief overview of core aspects of MVP.
11
Content available remote A Hybrid Expert Systems Architecture for Yarn Fault Diagnosis
Dlodlo N., Hunter L., Cele C., Metelerkamp R., Botha A. F.
Fibres & Textiles in Eastern Europe
|
2007
|
Vol. 15, no. 2 (61)
43--49
EN
This article describes a hybrid expert system architecture to support yarn fault diagnosis. The system uses a combination of rule-based and case-based techniques to achieve the diagnosis. Rule-based systems handle problems with well-defined knowledge bases, which limits the flexibility of such systems. To overcome this inherent weakness of rule-based systems (RBS), case-based reasoning (CBR) has been adopted to improve the performance of the expert system by incorporating previous cases in the generation of new cases. The idea of this research is to use rules to generate a diagnosis on a fault and to use cases to handle exceptions to the rules. The cases are represented using an object-oriented approach to support abstraction, re-use and inheritance features.
PL
Artykuł ten opisuje architekturę hybrydowego systemu eksperckiego, stosowanego jako pomoc w rozpoznawaniu błędów przędzy. W celu dokonania rozpoznania uszkodzeń, system hybrydowy oparty jest na kombinacji technik, których podstawami są „reguły” i „przypadki”. Systemy oparte na „regułach” (SOR) rozwiązują problemy o dobrze znanych i określonych zasadach, co ogranicza elastyczność takich systemów. Aby pokonać tą ich nieodłączną niesprawność i polepszyć działanie systemu, zastosowano podsystemy rozpoznające przypadki (SRP), dla generacji nowych przypadków na podstawie analizy dotychczasowych. Myślą przewodnią przedstawionego opracowania jest stosowanie reguł dla generowania diagnozy, dotyczącej danego błędu i wykorzystania przypadków dla rozpatrywania odstępstw od reguł. Przypadki są reprezentowane poprzez dochodzenie do celu zorientowanie na obiekt dla wsparcia abstrakcji reguły i powtórnej realizacji zadania.
12
Content available remote Rough Set-Based Dimensionality Reduction for Supervised and Unsupervised Learning
Shen Q., Chouchoulas A.
International Journal of Applied Mathematics and Computer Science
|
2001
|
Vol. 11, no 3
583-601
EN
The curse of dimensionality is a damning factor for numerous potentially powerful machine learning techniques. Widely approved and otherwise elegant methodologies used for a number of different tasks ranging from classification to function approximation exhibit relatively high computational complexity with respect to dimensionality. This limits severely the applicability of such techniques to real world problems. Rough set theory is a formal methodology that can be employed to reduce the dimensionality of datasets as a preprocessing step to training a learning system on the data. This paper investigates the utility of the Rough Set Attribute Reduction (RSAR) technique to both supervised and unsupervised learning in an effort to probe RSAR's generality. FuREAP, a Fuzzy-Rough Estimator of Algae Populations, which is an existing integration of RSAR and a fuzzy Rule Induction Algorithm (RIA), is used as an example of a supervised learning system with dimensionality reduction capabilities. A similar framework integrating the Multivariate Adaptive Regression Splines (MARS) approach and RSAR is taken to represent unsupervised learning systems. The paper describes the three techniques in question, discusses how RSAR can be employed with a supervised or an unsupervised system, and uses experimental results to draw conclusions on the relative success of the two integration efforts.
13
Learning algorithms for a class of knowledge-based systems with dynamical knowledge representation.
Bubnicki Z.
Systems Science
|
2000
|
Vol. 26, nr 1
15-27
EN
The paper deals with a specific class of knowledge-based systems with a dynamical plant described by a knowledge representation with unknown parameters. The learning consists of step by step knowledge evaluation and updating, and using the results for the determination of the current control decisions. The paper presents an extension of methods and algorithms described by the author (1999) for the knowledge-based learning systems with a static plant. Two forms of the plant descriptions are taken into account: the relational knowledge representation, and the logical knowledge representation. A simple illustrative example is given.
first rewind previous Strona / 1 next fast forward last
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.