Model Based Anytime Soft Computing Approaches in Engineering Applications

Várkonyi-Kóczy, Annamária R.

doi:10.1007/978-3-642-00448-3_4

Cited by 17 publications

(12 citation statements)

References 21 publications

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“…During the reduction the matrices can be partitioned into two parts, with "r" denoting the remaining while "d" the discarded submatrices, respectively. n r ≤n SVD is always held [4]. The approximation error of the reduced matrix is also an important factor, because the result after the reduction shall meet certain accuracy requirements.…”

Section: The Measurementmentioning

confidence: 99%

“…The approximation error of the reduced matrix is also an important factor, because the result after the reduction shall meet certain accuracy requirements. The reduction error of the SVD-based matrix can be estimated from the error matrix by (9),(10) [4].…”

Section: The Measurementmentioning

confidence: 99%

“…Thus the alarm can be done in time if it is necessary. The studied subsystem is a product-sum-gravity fuzzy inference with non-singleton consequences (PSGN) [4] where the antecedent fuzzy sets are in Ruspini partition and the consequences are fuzzy sets. The system can be represented by (1) where there are three input parameters (j=3), for all the groups which participate in the real-time evaluation.…”

Section: ) the Anytime Fuzzy Modelmentioning

confidence: 99%

“…An important advantage of these methods is that they offer a formal measure to filter out the redundancy and also the weakly contributing parts thereby reducing the computational complexity and making the evaluation faster. The reduction degree can be adjusted to the current circumstances according to the acceptable error level with using iterative models [4].…”

Section: Introductionmentioning

confidence: 99%

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Anytime sport activity risk level calculation using HOSVD based hierarchical fuzzy models

Tóth-Laufer

Várkonyi-Kóczy

2013

2013 IEEE International Symposium on Medical Measurements and Applications (MeMeA)

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In this paper a fuzzy logic-based risk calculation model is introduced, which is used to assess the risk level of sport activity in real-time. In these kinds of systems the computational complexity is a key factor, because the sufficiently accurate results should be available in time. The aim is to find the balance between the computational complexity and the accuracy. Anytime techniques are well-suited for these types of problems, because the combination of the soft computing and anytime algorithms can cope with the dynamically changing and possible insufficient amount of resources and reaction time and it is able to adaptively work with the available information which is usually imperfect or even missing. In this study the Singular Value Decomposition (SVD)-based algorithm is used to reduce the basic fuzzy model complexity.

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Section: The Measurementmentioning

confidence: 99%

Section: The Measurementmentioning

confidence: 99%

Section: ) the Anytime Fuzzy Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Anytime sport activity risk level calculation using HOSVD based hierarchical fuzzy models

Tóth-Laufer

Várkonyi-Kóczy

2013

2013 IEEE International Symposium on Medical Measurements and Applications (MeMeA)

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“…The SVD is a useful tool for approximating strongly nonlinear systems' behavior as well [21]. Furthermore, the degree of reduction can be adjusted to the current circumstances according to the acceptable error level using iterative models [22]. We used this method to create an anytime model, which is able to detect unexpected situations.…”

mentioning

confidence: 99%

A Soft Computing-Based Hierarchical Sport Activity Risk Level Calculation Model for Supporting Home Exercises

Tóth-Laufer

Várkonyi-Kóczy

2014

IEEE Trans. Instrum. Meas.

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With the spread of active styles of living, regular health monitoring and risk estimation of exercises became an essential part of everyday life. In this paper, a fuzzy logic-based hierarchical, classified risk calculation model is introduced, which can be used to assess the risk level of sport activity in realtime. The model considers the current physical status and the preliminary assessed medical conditions of the person, the activity load of the exercise, as well as the environmental conditions. Based on this information, a hierarchical fuzzy decision making system evaluates the risk level and sends warning (to the person to stop the activity) or alerting (to a medical doctor/hospital) or both if necessary. By this, serious health problems/crisis situations can be avoided. The complexity of the model is optimized by the application of the singular value decomposition-based complexity reduction algorithm. In critical situations [when the available (dynamically changing) amount of time, resources, and data become insufficient], the anytime mode of operation helps to cope with the temporal conditions and to find a tradeoff between the computational complexity of the evaluations and the accuracy of the results. The system can be operated real-time at home, thus making more comfortable and safer the active (preventive) life and rehabilitation processes of conscious people.

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Fuzzy Approaches in Anytime Systems

Várkonyi-Kóczy

2013

On Fuzziness

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Model Based Anytime Soft Computing Approaches in Engineering Applications

Cited by 17 publications

References 21 publications

Anytime sport activity risk level calculation using HOSVD based hierarchical fuzzy models

Anytime sport activity risk level calculation using HOSVD based hierarchical fuzzy models

A Soft Computing-Based Hierarchical Sport Activity Risk Level Calculation Model for Supporting Home Exercises

Fuzzy Approaches in Anytime Systems

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