Aggregation Operator for Ordered Fuzzy Numbers Concerning the Direction

Prokopowicz, Piotr; Golsefid, Samira Malek Mohamadi

doi:10.1007/978-3-319-07173-2_24

Cited by 13 publications

(14 citation statements)

References 23 publications

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“…We can read from them, the actual trend of the process. The papers [16], [27], [8], [21] describes the research of the methods of processing of KFNs where a direction is considered -Direction Sensitive Fuzzy Information Processing. So, instead ignoring orientation we can use full information and process it in a more effective way.…”

Section: Discussionmentioning

confidence: 99%

Analysis of the Changes in Processes Using the Kosinski's Fuzzy Numbers

Prokopowicz¹

2016

Annals of Computer Science and Information Systems

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Abstract-This paper presents the analysis of potential of the Kosinski's Fuzzy Number (KFN) idea in the modeling trends of the processes which are described imprecisely. KFNs conception is an alternative for the classical fuzzy numbers ideas as model to represent of the imprecise quantitative data. They introduces new feature into vagueness of the information -a direction. It is base for good arithmetical properties of calculations. Furthermore, a direction also extends a potential in the modeling of information by the additional interpretation, what is a subject of this article. This new potential is presented and explained basing on the example of modeling of quantity of liquid in a reservoir. The environment is changing dynamically what is described as the changes in inflow and outflow. Proposed example explains how to interpret the direction of KFN and how to understand the results of calculations and its influence.

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Section: Discussionmentioning

confidence: 99%

Analysis of the Changes in Processes Using the Kosinski's Fuzzy Numbers

Prokopowicz¹

2016

Annals of Computer Science and Information Systems

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“…We can include into the fuzzy value additional interpretations apart from the membership value. The new feature of processing is called 'sensitivity for the direction' (see [43,44,46] and Chap. 5) and makes it possible to involve in a model such expressions as, 'The temperature is about 20…”

Section: Ofn As An Alternative Approach To Fuzzinessmentioning

confidence: 99%

“…In the case of the OFN model and processing methods that can be called 'arithmetic' (see [40,41,43,44]), at each stage of the fuzzy system process we deal with the quantitative aspect of the data. Thus we consistently obtain fuzzy numbers at each step: the aggregation of premises, the inference and the accumulation-aggregation of the rules answers.…”

Section: Ofn As An Alternative Approach To Fuzzinessmentioning

confidence: 99%

OFN-Based Brain Function Modeling

Prokopowicz

Mikołajewski

2017

Theory and Applications of Ordered Fuzzy Numbers

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A modeling approach may significantly help to explore the problem of weak understanding of the physiological and pathological central nervous system function in the most noninvasive and comprehensive way. The aim of this chapter is to assess and discuss the extent to which possible opportunities concerning computational brain models based on fuzzy logic techniques may be exploited. IntroductionStructured networks and functional connections of interacting neural populations underlying both physiological and pathological central nervous system (CNS) function are still poorly understood. Interdisciplinarity and independence of research provide a variety of scientific approaches, used tools, and wide coverage and even overlapping of the research fields, especially as regards human research, including neuroscience [1]. The modeling approach may significantly help to explore the aforementioned problem in the most noninvasive way. The aim of this chapter is to assess and discuss the extent to which possible opportunities concerning computational brain models based on fuzzy logic techniques may be exploited.

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“…Because we deal with additional information, there is a need for the new methods which benefit the full potential of OFNs in modeling of linguistic data. The papers [10,[17][18][19][20] describe the research of the OFN processing methods that consider the direction.…”

Section: Main Ideas Of the Ofn Modelmentioning

confidence: 99%

Analysis of Temporospatial Gait Parameters

Prokopowicz

Mikołajewska

Mikołajewski

et al. 2017

Theory and Applications of Ordered Fuzzy Numbers

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Locomotion in post-stroke patients may be severely compromised. Assessment and treatment of gait disorders after stroke are crucial. Scientists and clinicians still look for more effective diagnostic and therapeutic tools. The aim of the study was to assess a new fuzzy-based tool for measurement of observed gait parameters (velocity, cadence, and stride length, and their normalized values), both in healthy people and post-stroke patients.

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Aggregation Operator for Ordered Fuzzy Numbers Concerning the Direction

Cited by 13 publications

References 23 publications

Analysis of the Changes in Processes Using the Kosinski's Fuzzy Numbers

Analysis of the Changes in Processes Using the Kosinski's Fuzzy Numbers

OFN-Based Brain Function Modeling

Analysis of Temporospatial Gait Parameters

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