| 1. |
- Jones, Richard W., et al.
(author)
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A framework for intelligent medical diagnosis using the theory of evidence
- 2002
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In: Knowledge-Based Systems. - 0950-7051 .- 1872-7409. ; 15:1-2, s. 77-84
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Journal article (peer-reviewed)abstract
- In designing fuzzy logic systems for fault diagnosis, problems can be encountered in the choice of symptoms to use fuzzy operators and an inability to convey the reliability of the diagnosis using just one degree of membership for the conclusion. By turning to an evidential framework, these problems can be resolved whilst still preserving a fuzzy relational model structure. The theory of evidence allows for utilisation of all available information. Relationships between sources of evidence determine appropriate combination rules. By generating belief and plausibility measures it also communicates the reliability of the diagnosis, and completeness of information. In this contribution medical diagnosis is considered using the theory of evidence, in particular the diagnosis of inadequate analgesia is considered
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| 2. |
- Kruusmaa, Maarja, et al.
(author)
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Covering the path space : a casebase analysis for mobile robot path planning
- 2003
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In: Knowledge-Based Systems. - Guildford, Surrey : Elsevier. - 0950-7051 .- 1872-7409. ; 16:5-6, s. 235-242
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Journal article (peer-reviewed)abstract
- This paper presents a theoretical analysis of a casebase used for mobile robot path planning in dynamic environments. Unlike other case-based path planning approaches, we use a grid map to represent the environment that permits the robot to operate in unstructured environments. The objective of the mobile robot is to learn to choose paths that are less risky to follow. Our experiments with real robots have shown the efficiency of our concept. In this paper, we replace a heuristic path planning algorithm of the mobile robot with a seed casebase and prove the upper and lower bounds for the cardinality of the casebase. The proofs indicate that it is realistic to seed the casebase with some solutions to a path-finding problem so that no possible solution differs too much from some path in the casebase. This guarantees that the robot would theoretically find all paths from start to goal. The proof of the upper bound of the casebase cardinality shows that the casebase would in a long run grow too large and all possible solutions cannot be stored. In order to keep only the most efficient solutions the casebase has to be revised at run-time or some other measure of path difference has to be considered.
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| 3. |
- Verikas, Antanas, et al.
(author)
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An intelligent system for tuning magnetic field of a cathode ray tube deflection yoke
- 2003
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In: Knowledge-Based Systems. - Amsterdam : Elsevier Science. - 0950-7051 .- 1872-7409. ; 16:3, s. 161-164
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Journal article (peer-reviewed)abstract
- This short communication concerns identification of the number of magnetic correction shunts and their positions for deflection yoke tuning to correct the misconvergence of colours of a cathode ray tube. The misconvergence of colours is characterised by the distances measured between the traces of red and blue beams. The method proposed consists of two phases, namely, learning and optimisation. In the learning phase, the radial basis function neural network is trained to learn a mapping: correction shunt position→changes in misconvergence. In the optimisation phase, the trained neural network is used to predict changes in misconvergence depending on a correction shunt position. An optimisation procedure based on the predictions returned by the neural net is then executed in order to find the minimal number of correction shunts needed and their positions. During the experimental investigations, 98% of the deflection yokes analysed have been tuned successfully using the technique proposed.
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| 4. |
- Amon, B., et al.
(author)
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From first-order logic to automated word generation for Lyee
- 2003
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In: Knowledge-Based Systems. - : Elsevier BV. - 0950-7051 .- 1872-7409. ; 16:07-8, s. 413-429
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Journal article (peer-reviewed)abstract
- A conceptual schema can be viewed as a language to describe the phenomena in a system to be modelled, i.e. a set of derivation rules and integrity constraints as well as a set of event-rules describing the behaviour of an object system. In this paper, we investigate the relationship between the Lyee software requirements concepts with various constructs in conceptual modelling. Within our work we choose the Unified Modelling Language (UML) as a modelling notation for explaining conceptual models. The result obtained models a fully expressive set of UML and First Order Logic constructs mapped into Lyee concepts.
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| 5. |
- Bayram, Firas, et al.
(author)
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From concept drift to model degradation : An overview on performance-aware drift detectors
- 2022
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In: Knowledge-Based Systems. - : Elsevier BV. - 0950-7051 .- 1872-7409. ; 245
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Research review (peer-reviewed)abstract
- The dynamicity of real-world systems poses a significant challenge to deployed predictive machine learning (ML) models. Changes in the system on which the ML model has been trained may lead to performance degradation during the system’s life cycle. Recent advances that study non-stationary environments have mainly focused on identifying and addressing such changes caused by a phenomenon called concept drift. Different terms have been used in the literature to refer to the same type of concept drift and the same term for various types. This lack of unified terminology is set out to create confusion on distinguishing between different concept drift variants. In this paper, we start by grouping concept drift types by their mathematical definitions and survey the different terms used in the literature to build a consolidated taxonomy of the field. We also review and classify performance-based concept drift detection methods proposed in the last decade. These methods utilize the predictive model’s performance degradation to signal substantial changes in the systems. The classification is outlined in a hierarchical diagram to provide an orderly navigation between the methods. We present a comprehensive analysis of the main attributes and strategies for tracking and evaluating the model’s performance in the predictive system. The paper concludes by discussing open research challenges and possible research directions.
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| 6. |
- Cacciarelli, Davide, et al.
(author)
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Stream-based active learning with linear models
- 2022
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In: Knowledge-Based Systems. - : Elsevier. - 0950-7051 .- 1872-7409. ; 254
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Journal article (peer-reviewed)abstract
- The proliferation of automated data collection schemes and the advances in sensorics are increasing the amount of data we are able to monitor in real-time. However, given the high annotation costs and the time required by quality inspections, data is often available in an unlabeled form. This is fostering the use of active learning for the development of soft sensors and predictive models. In production, instead of performing random inspections to obtain product information, labels are collected by evaluating the information content of the unlabeled data. Several query strategy frameworks for regression have been proposed in the literature but most of the focus has been dedicated to the static pool-based scenario. In this work, we propose a new strategy for the stream-based scenario, where instances are sequentially offered to the learner, which must instantaneously decide whether to perform the quality check to obtain the label or discard the instance. The approach is inspired by the optimal experimental design theory and the iterative aspect of the decision-making process is tackled by setting a threshold on the informativeness of the unlabeled data points. The proposed approach is evaluated using numerical simulations and the Tennessee Eastman Process simulator. The results confirm that selecting the examples suggested by the proposed algorithm allows for a faster reduction in the prediction error.
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| 7. |
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| 8. |
- Danielson, Mats, et al.
(author)
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A second-order-based decision tool for evaluating decisions under conditions of severe uncertainty
- 2020
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In: Knowledge-Based Systems. - : Elsevier BV. - 0950-7051 .- 1872-7409. ; 191
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Journal article (peer-reviewed)abstract
- The requirement to assign precise numerical values to model entities such as criteria weights, probabilities, and utilities is too strong in most real-life decision situations, and hence alternative representations and evaluation mechanisms are important to consider. In this paper, we discuss the DecideIT 3.0 state-of-the-art software decision tool and demonstrate its functionality using a real-life case. The tool is based on a belief mass interpretation of the decision information, where the components are imprecise by means of intervals and qualitative estimates, and we discuss how multiplicative and additive aggregations influence the resulting distribution over the expected values.
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| 9. |
- Danielson, Mats, et al.
(author)
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An improvement to swing techniques for elicitation in MCDM methods
- 2019
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In: Knowledge-Based Systems. - : Elsevier BV. - 0950-7051 .- 1872-7409. ; 168, s. 70-79
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Journal article (peer-reviewed)abstract
- Several approaches that utilise various questioning procedures to elicit criteria weights exist, ranging from direct rating and point allocation to more elaborate methods. However, decision makers often find it difficult to understand how these methods work and how they should be comprehended. This article discusses the SWING family of elicitation techniques and suggests a refined method: the P-SWING method. Based on this, we provide an integrated framework for elicitation, modelling and evaluation of multi-criteria decision problems.
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| 10. |
- Davies, Guy, et al.
(author)
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Model correspondence as a basis for schema domination
- 2010
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In: Knowledge-Based Systems. - : Elsevier BV. - 0950-7051 .- 1872-7409. ; 23:7, s. 693-703
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Journal article (peer-reviewed)abstract
- Conceptual schemata each representing some component of a system in the making, can be integrated in a variety of ways. Herein, we explore some fundamental notions of this. In particular, we examine some ways in which integration using correspondence assertions affects the interrelationship of two component schemata. Our analysis of the logic leads us to reject the commonly asserted requirement of constraining correspondence assertions to single predicates from a source schema. Much previous work has focussed on dominance with regard to preservation of information capacity as a primary integration criterion. However, even though it is desirable that the information capacity of a combined schema dominate one or both of its constituent schemata, we here discuss some aspects of why domination based on information capacity alone is insufficient for the integration to be semantically satisfactory, and we provide a framework for detecting mappings that prevent schema domination.
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