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Johansson, Ronnie
Publications (10 of 17) Show all publications
Karami, A. & Johansson, R. (2014). Utilization of multi attribute decision making techniques to integrate automatic and manual ranking of options. Journal of information science and engineering, 30(2), 519-534
Open this publication in new window or tab >>Utilization of multi attribute decision making techniques to integrate automatic and manual ranking of options
2014 (English)In: Journal of information science and engineering, ISSN 1016-2364, Vol. 30, no 2, p. 519-534Article in journal (Refereed) Published
Place, publisher, year, edition, pages
Institute of Information Science, 2014
Keywords
Bayesian networks, sensor allocation, TOPSIS, SAW, AHP, entropy
National Category
Computer Sciences
Research subject
Distributed Real-Time Systems
Identifiers
urn:nbn:se:his:diva-14961 (URN)10.1688/JISE.2014.30.2.14 (DOI)000333657300014 ()2-s2.0-84912059079 (Scopus ID)
Available from: 2018-03-15 Created: 2018-03-15 Last updated: 2019-11-26Bibliographically approved
Karlsson, A., Johansson, R. & Andler, S. F. (2011). Characterization and Empirical Evaluation of Bayesian and Credal Combination Operators. Journal of Advances in Information Fusion, 6(2), 150-166
Open this publication in new window or tab >>Characterization and Empirical Evaluation of Bayesian and Credal Combination Operators
2011 (English)In: Journal of Advances in Information Fusion, ISSN 1557-6418, Vol. 6, no 2, p. 150-166Article in journal (Refereed) Published
Abstract [en]

We address the problem of combining independent evidences from multiple sources by utilizing the Bayesian and credal combination operators. We present measures for degree of conflict and imprecision, which we use in order to characterize the behavior of the operators through a number of examples. We introduce discounting operators that can be used whenever information about the reliability of sources is available. The credal discounting operator discounts a credal set with respect to an interval of reliability weights, hence, we allow for expressing reliability of sources imprecisely. We prove that the credal discounting operator can be computed by using the extreme points of its operands. We also perform two experiments containing different levels of risk where we compare the performance of the Bayesian and credal combination operators by using a simple score function that measures the informativeness of a reported decision set. We show that the Bayesian combination operator performed on centroids of operand credal sets outperforms the credal combination operator when no risk is involved in the decision problem. We also show that if a risk component is present in the decision problem, a simple cautious decision policy for the Bayesian combination operator can be constructed that outperforms the corresponding credal decision policy.

Place, publisher, year, edition, pages
ISIF, International Society of Information Fusion, 2011
National Category
Computer and Information Sciences
Research subject
Technology
Identifiers
urn:nbn:se:his:diva-6305 (URN)
Available from: 2012-08-21 Created: 2012-08-20 Last updated: 2018-01-12Bibliographically approved
Riveiro, M., Johansson, R. & Karlsson, A. (2011). Modeling and analysis of energy data: state-of-the-art and practical results from an application scenario. Skövde: University of Skövde
Open this publication in new window or tab >>Modeling and analysis of energy data: state-of-the-art and practical results from an application scenario
2011 (English)Report (Other academic)
Abstract [en]

This paper presents a comprehensive summary of the state-of-the-art of energy efficiency research. The literature review carried out focuses on the application of data mining and data analysis techniques to energy consumption data, as well as  descriptions  of  tools, applications and research prototypes to manage the consumption of energy. Moreover, preliminary results of the application of a clustering technique to energy consumption data illustrate the review.

Place, publisher, year, edition, pages
Skövde: University of Skövde, 2011. p. 9
Series
IKI Technical Reports ; HS-IKI-TR-11-002
Keywords
Energy efficiency, smart grid, customer behavioral models, energy management system (EMS), sustainable living
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:his:diva-5372 (URN)
Available from: 2011-12-22 Created: 2011-12-22 Last updated: 2018-01-12Bibliographically approved
Karlsson, A., Johansson, R. & Andler, S. F. (2010). An Empirical Comparison of Bayesian and Credal Combination Operators. In: FUSION 2010: 13th international Conference on Information Fusion, 26-29 July 2010, EICC, Edinburgh, UK. Paper presented at 13th international Conference on Information Fusion, 26-29 July 2010, EICC, Edinburgh, UK (pp. Article number 5711907). IEEE conference proceedings
Open this publication in new window or tab >>An Empirical Comparison of Bayesian and Credal Combination Operators
2010 (English)In: FUSION 2010: 13th international Conference on Information Fusion, 26-29 July 2010, EICC, Edinburgh, UK, IEEE conference proceedings, 2010, p. Article number 5711907-Conference paper, Published paper (Refereed)
Abstract [en]

We are interested in whether or not representing and maintaining imprecision is beneficial when combining evidences from multiple sources. We perform two experiments that contain different levels of risk and where we measure the performance of the Bayesian and credal combination operators by using a simple score function that measures the informativeness of a reported decision set. We show that the Bayesian combination operator performed on centroids of operand credal sets outperforms the credal combination operator when no risk is involved in the decision problem. We also show that if a risk component is present in the decision problem, a simple cautious decision policy for the Bayesian combination operator can be constructed that outperforms the corresponding credal decision policy.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2010
Keywords
Bayesian combination operator, credal combination operator, Imprecise probability
National Category
Computer and Information Sciences
Research subject
Technology
Identifiers
urn:nbn:se:his:diva-4655 (URN)2-s2.0-79952382065 (Scopus ID)978-0-9824438-1-1 (ISBN)
Conference
13th international Conference on Information Fusion, 26-29 July 2010, EICC, Edinburgh, UK
Available from: 2011-01-27 Created: 2011-01-27 Last updated: 2018-01-12Bibliographically approved
Karlsson, A., Johansson, R. & Andler, S. F. (2010). An Empirical Comparison of Bayesian and Credal Set Theory for Discrete State Estimation. In: Eyke Hüllermeier, Rudolf Kruse, Frank Hoffmann (Ed.), Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Methods: 13th International Conference, IPMU 2010, Dortmund, Germany, June 28–July 2, 2010. Proceedings, Part I. Paper presented at 13th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU) 2010, Dortmund, Germany, June 28–July 2, 2010 (pp. 80-89). Springer Berlin/Heidelberg
Open this publication in new window or tab >>An Empirical Comparison of Bayesian and Credal Set Theory for Discrete State Estimation
2010 (English)In: Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Methods: 13th International Conference, IPMU 2010, Dortmund, Germany, June 28–July 2, 2010. Proceedings, Part I / [ed] Eyke Hüllermeier, Rudolf Kruse, Frank Hoffmann, Springer Berlin/Heidelberg, 2010, p. 80-89Conference paper, Published paper (Refereed)
Abstract [en]

We are interested in whether or not there exist any advantages of utilizing credal set theory for the discrete state estimation problem. We present an experiment where we compare in total six different methods, three based on Bayesian theory and three on credal set theory. The results show that Bayesian updating performed on centroids of operand credal sets significantly outperforms the other methods. We analyze the result based on degree of imprecision, position of extreme points, and second-order distributions.

Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2010
Series
Communications in Computer and Information Science, ISSN 1865-0937 ; 80
Keywords
Bayesian theory, credal sets, imprecise probability
National Category
Computer and Information Sciences
Research subject
Technology
Identifiers
urn:nbn:se:his:diva-4654 (URN)10.1007/978-3-642-14055-6_9 (DOI)000290641900009 ()2-s2.0-84867610945 (Scopus ID)978-3-642-14054-9 (ISBN)978-3-642-14055-6 (ISBN)3-642-14054-8 (ISBN)
Conference
13th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU) 2010, Dortmund, Germany, June 28–July 2, 2010
Available from: 2011-01-27 Created: 2011-01-27 Last updated: 2018-01-12Bibliographically approved
Brax, C., Karlsson, A., Andler, S. F., Johansson, R. & Niklasson, L. (2010). Evaluating Precise and Imprecise State-Based Anomaly Detectors for Maritime Surveillance. In: Proceedings of the 13th International Conference on Information Fusion. Paper presented at 13th Conference on Information Fusion, Fusion 2010; Edinburgh; 26 July 2010 through 29 July 2010 (pp. Article number 5711997). IEEE conference proceedings
Open this publication in new window or tab >>Evaluating Precise and Imprecise State-Based Anomaly Detectors for Maritime Surveillance
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2010 (English)In: Proceedings of the 13th International Conference on Information Fusion, IEEE conference proceedings, 2010, p. Article number 5711997-Conference paper, Published paper (Refereed)
Abstract [en]

We extend the State-Based Anomaly Detection approach by introducing precise and imprecise anomaly detectors using the Bayesian and credal combination operators, where evidences over time are combined into a joint evidence. We use imprecision in order to represent the sensitivity of the classification regarding an object being  normal or anomalous. We evaluate the detectors on a real-world maritime dataset containing recorded AIS data and show that the anomaly detectors outperform   previously proposed detectors based on Gaussian mixture models and kernel density estimators. We also show that our introduced anomaly detectors perform slightly better than the State-Based Anomaly Detection approach with a sliding window.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2010
Keywords
Anomaly detection, maritime surveillance, Bayesian combination operator, credal combination opr
National Category
Computer and Information Sciences
Research subject
Technology
Identifiers
urn:nbn:se:his:diva-4636 (URN)2-s2.0-79952419500 (Scopus ID)978-1-9824438-1-1 (ISBN)
Conference
13th Conference on Information Fusion, Fusion 2010; Edinburgh; 26 July 2010 through 29 July 2010
Available from: 2011-01-25 Created: 2011-01-25 Last updated: 2018-01-12Bibliographically approved
Johansson, R. & Mårtenson, C. (2010). Information Acquisition Strategies for Bayesian Network-based Decision Support. In: FUSION 2010: 13th international Conference on Information Fusion, 26-29 July 2010, EICC, Edinburgh, UK. Paper presented at 13th international Conference on Information Fusion, 26-29 July 2010, EICC, Edinburgh, UK (pp. 1-8). IEEE conference proceedings, Article ID 5712030.
Open this publication in new window or tab >>Information Acquisition Strategies for Bayesian Network-based Decision Support
2010 (English)In: FUSION 2010: 13th international Conference on Information Fusion, 26-29 July 2010, EICC, Edinburgh, UK, IEEE conference proceedings, 2010, p. 1-8, article id 5712030Conference paper, Published paper (Refereed)
Abstract [en]

Determining how to utilize information acquisition resources optimally is a difficult task in the intelligence domain. Nevertheless, an intelligence analyst can expect little or no support for this from software tools today. In this paper, we describe a proof of concept implementation of a resource allocation mechanism for an intelligence analysis support system. The system uses a Bayesian network to structure intelligence requests, and the goal is to minimize the uncertainty of a variable of interest. A number of allocation strategies are discussed and evaluated through simulations.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2010
Keywords
Bayesian networks, decision support tool, information acquisition
National Category
Computer and Information Sciences
Research subject
Technology
Identifiers
urn:nbn:se:his:diva-4653 (URN)10.1109/ICIF.2010.5712030 (DOI)2-s2.0-79952386099 (Scopus ID)978-0-9824438-1-1 (ISBN)
Conference
13th international Conference on Information Fusion, 26-29 July 2010, EICC, Edinburgh, UK
Available from: 2011-01-27 Created: 2011-01-27 Last updated: 2018-01-12Bibliographically approved
Hilletofth, P., Ujvari, S. & Johansson, R. (2009). Agent-Based Simulation Fusion for Improved Decision Making for Service Operations. In: Proceedings of the 12th International Conference on Information Fusion: . Paper presented at Fusion 2009 : the 12th International Conference on Information Fusion : Grand Hyatt Seattle, Seattle, Washington, USA, 6-9 July, 2009. IEEE
Open this publication in new window or tab >>Agent-Based Simulation Fusion for Improved Decision Making for Service Operations
2009 (English)In: Proceedings of the 12th International Conference on Information Fusion, IEEE , 2009Conference paper, Published paper (Refereed)
Abstract [en]

We use agent-based modeling and simulation to fuse data from multiple sources to estimate the state of some system properties. This implies that the real system of interest is modeled and simulated using agent principles. Using Monte-Carlo simulation, we estimate the values of some decision-relevant numerical properties, such as utilization of resources and service levels, as a decision support for a Maintenance Service Provider. Our initial results indicate that this kind of fusion of information sources can improve the understanding of the problem domain (e.g. to what degree some critical properties influence service operations) and also generate a basis for decision-making.

Place, publisher, year, edition, pages
IEEE, 2009
Keywords
Agent-based simulation fusion, Service operation, Agent-based modeling and simulation, Decision support
National Category
Engineering and Technology
Research subject
Technology
Identifiers
urn:nbn:se:his:diva-3429 (URN)000273560000129 ()2-s2.0-70449363626 (Scopus ID)978-0-9824438-0-4 (ISBN)
Conference
Fusion 2009 : the 12th International Conference on Information Fusion : Grand Hyatt Seattle, Seattle, Washington, USA, 6-9 July, 2009
Available from: 2009-10-15 Created: 2009-10-15 Last updated: 2017-11-27Bibliographically approved
Ericson, S., Hedenberg, K. & Johansson, R. (2009). Information Fusion for Autonomous Robotic Weeding. In: Stefan Fischer, Erik Maehle, Rüdiger Reischuk (Ed.), INFORMATIK 2009: Im Focus das Leben. Paper presented at 39th Jahrestagung der Gesellschaft fur Informatik e.V. (GI): Im Focus das Leben, INFORMATIK 2009. 39th Annual Meeting of the German Informatics Society (GI): Focus on Life, INFORMATIK 2009, Lübeck, Germany, 28 September 2009 through 2 October 2009 (pp. 2461-2473). Köllen Druck + Verlag GmbH
Open this publication in new window or tab >>Information Fusion for Autonomous Robotic Weeding
2009 (English)In: INFORMATIK 2009: Im Focus das Leben / [ed] Stefan Fischer, Erik Maehle, Rüdiger Reischuk, Köllen Druck + Verlag GmbH , 2009, p. 2461-2473Conference paper, Published paper (Refereed)
Abstract [en]

Information fusion has a potential applicability to a multitude of differentapplications. Still, the JDL model is mostly used to describe defense applications.This paper describes the information fusion process for a robot removing weed ina field. We analyze the robotic system by relating it to the JDL model functions.The civilian application we consider here has some properties which differ from thetypical defense applications: (1) indifferent environment and (2) a predictable andstructured process to achieve its objectives. As a consequence, situation estimatestend to deal with internal properties of the robot and its mission progress (throughmission state transition) rather than external entities and their relations. Nevertheless, the JDL model appears useful for describing the fusion activities of the weeding robot system. We provide an example of how state transitions may be detected and exploited using information fusion and report on some initial results. An additional finding is that process refinement for this type of application can be expressed in terms of a finite state machine.

Place, publisher, year, edition, pages
Köllen Druck + Verlag GmbH, 2009
Series
Lecture Notes in Informatics, ISSN 1617-5468 ; Vol. P-154
National Category
Computer and Information Sciences
Research subject
Technology
Identifiers
urn:nbn:se:his:diva-3525 (URN)2-s2.0-84874333160 (Scopus ID)978-3-88579-248-2 (ISBN)
Conference
39th Jahrestagung der Gesellschaft fur Informatik e.V. (GI): Im Focus das Leben, INFORMATIK 2009. 39th Annual Meeting of the German Informatics Society (GI): Focus on Life, INFORMATIK 2009, Lübeck, Germany, 28 September 2009 through 2 October 2009
Available from: 2009-12-08 Created: 2009-12-08 Last updated: 2018-01-12Bibliographically approved
Karlsson, A., Johansson, R. & Andler, S. F. (2009). On the Behavior of the Robust Bayesian Combination Operator and the Significance of Discounting. In: Thomas Augustin, Frank P. A. Coolen, Serafin Moral, Matthias C. M. Troffaes (Ed.), ISIPTA ’09: Proceedings of the Sixth International Symposium on Imprecise Probability: Theories and Applications. Paper presented at 6th International Symposium on Imprecise Probability: Theories and Applications, Durham University, United Kingdom, 14-18 July 2009 (pp. 259-268). Society for Imprecise Probability
Open this publication in new window or tab >>On the Behavior of the Robust Bayesian Combination Operator and the Significance of Discounting
2009 (English)In: ISIPTA ’09: Proceedings of the Sixth International Symposium on Imprecise Probability: Theories and Applications / [ed] Thomas Augustin, Frank P. A. Coolen, Serafin Moral, Matthias C. M. Troffaes, Society for Imprecise Probability , 2009, p. 259-268Conference paper, Published paper (Refereed)
Abstract [en]

We study the combination problem for credal sets via the robust Bayesian combination operator. We extend Walley's notion of degree of imprecision and introduce a measure for degree of conflict between two credal sets. Several examples are presented in order to explore the behavior of the robust Bayesian combination operator in terms of imprecision and conflict. We further propose a discounting operator that suppresses a source given an interval of reliability weights, and highlight the importance of using such weights whenever additional information about the reliability of a source is available.

Place, publisher, year, edition, pages
Society for Imprecise Probability, 2009
Keywords
Imprecise probabilities, robust Bayesian combination, credal set, discounting, information fusion
National Category
Computer and Information Sciences
Research subject
Technology
Identifiers
urn:nbn:se:his:diva-3450 (URN)000280248700027 ()2-s2.0-84870766621 (Scopus ID)
Conference
6th International Symposium on Imprecise Probability: Theories and Applications, Durham University, United Kingdom, 14-18 July 2009
Available from: 2009-10-20 Created: 2009-10-20 Last updated: 2018-01-12Bibliographically approved
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