Granular Computing

Bargieła, Andrzej; Pedrycz, Witold

doi:10.1007/978-1-4615-1033-8

Cited by 338 publications

(55 citation statements)

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“…Different techniques may be used to estimate this unknown but bounded error, [Mil96], [Nor86], [Kur97]. We use a variant of the so-called sensitivity matrix analysis, [Bar03], which uses the state estimator presented above.…”

Section: Error Limit Analysismentioning

confidence: 99%

Estimation of Fuzzy Anomalies in Water Distribution Systems

Izquierdo¹,

Tung

Pérez³

et al. 2008

Progress in Industrial Mathematics at ECMI 2006

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State estimation is necessary in diagnosing anomalies in Water Demand Systems (WDS). In this paper we present a neural network performing such a task. State estimation is performed by using optimization, which tries to reconcile all the available information. Quantification of the uncertainty of the input data (telemetry measures and demand predictions) can be achieved by means of robust estate estimation. Using a mathematical model of the network, fuzzy estimated states for anomalous states of the network can be obtained. They are used to train a neural network capable of assessing WDS anomalies associated with particular sets of measurements.

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Section: Error Limit Analysismentioning

confidence: 99%

Estimation of Fuzzy Anomalies in Water Distribution Systems

Izquierdo¹,

Tung

Pérez³

et al. 2008

Progress in Industrial Mathematics at ECMI 2006

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“…In this study, we have approached the problem of costeffective scheduling of nurses using the domain transformation method introduced in [Baskaran et al 2009[Baskaran et al , 2012 as a practical illustration of the information granulation methodology [Bargiela et al 2002[Bargiela et al , 2008. Based on this solution we investigate the optimum balance between the staffing levels of the ward and the ability to achieve good quality schedules.…”

Section: Introductionmentioning

confidence: 99%

A Study Of Cost Effective Scheduling Of Nurses Based On The Domain Transformation Method

Baskaran¹,

Bargieła²,

Qu³

2013

ECMS 2013 Proceedings Edited By: Webjorn Rekdalsbakken, Robin T. Bye, Houxiang Zhang

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This paper discusses and analyses the tradeoff between the flexibility afforded with greater number of staff and the implied cost of employing extra staff in the context of the nurse-scheduling problem. If the number of staff is constant, our study allows quantification of the degree of pressure put on the staff resulting from the schedules that do not satisfy their preferences for shift allocation. We present a practical approach, based on our domain transformation methodology that achieves good quality schedules without high computational requirements.

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“…Granularity of information [1-6, 21, 28, 29] becomes of paramount importance, both from the conceptual as well as algorithmic perspective, in the realization of granular fuzzy models. Subsequently, processing realized at the level of information granules gives rise to the discipline of Granular Computing [2]. We envision here a vast suite of formal approaches of fuzzy sets [15], rough sets [10][11][12][13][14], shadowed sets [16,18,19], probabilistic sets [9] and alike.…”

Section: Introductionmentioning

confidence: 99%

The Principle of Justifiable Granularity and an Optimization of Information Granularity Allocation as Fundamentals of Granular Computing

Pedrycz¹

2011

Journal of Information Processing Systems

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Abstract-GranularComputing has emerged as a unified and coherent framework of designing, processing, and interpretation of information granules. Information granules are formalized within various frameworks such as sets (interval mathematics), fuzzy sets, rough sets, shadowed sets, probabilities (probability density functions), to name several the most visible approaches. In spite of the apparent diversity of the existing formalisms, there are some underlying commonalities articulated in terms of the fundamentals, algorithmic developments and ensuing application domains. In this study, we introduce two pivotal concepts: a principle of justifiable granularity and a method of an optimal information allocation where information granularity is regarded as an important design asset. We show that these two concepts are relevant to various formal setups of information granularity and offer constructs supporting the design of information granules and their processing. A suite of applied studies is focused on knowledge management in which case we identify several key categories of schemes present there.

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Granular Computing

Cited by 338 publications

References 0 publications

Estimation of Fuzzy Anomalies in Water Distribution Systems

Estimation of Fuzzy Anomalies in Water Distribution Systems

A Study Of Cost Effective Scheduling Of Nurses Based On The Domain Transformation Method

The Principle of Justifiable Granularity and an Optimization of Information Granularity Allocation as Fundamentals of Granular Computing

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