Assessment of groundwater quality monitoring network based on information theory

Kucharek, Marta; Treichel, Wiktor

doi:10.1142/9789812709691_0075

Cited by 1 publication

(3 citation statements)

References 4 publications

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“…. , N) is equally likely to take place with a probability of p n = 1/N, the entropy reaches its maximum value equal to log N [42].…”

Section: Rating the Value Of Informationmentioning

confidence: 99%

“…The marginal entropy value is in the range from 0 to log N [42]. If we assume that the variable X represents a decision variable in the monitoring network, thus the marginal entropy H(X) defines the uncertainty associated with this variable.…”

Section: Rating the Value Of Informationmentioning

confidence: 99%

“…Moreover, using Equations (6) and (7), the entropy for observations regarding checking the condition of a building was calculated as: It should be underlined that the symptom that gives the largest reduction in entropy is more efficient from the standpoint of minimizing the diagnostic variable uncertainty [42].…”

Section: Rating the Value Of Informationmentioning

confidence: 99%

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The Idea of Using Bayesian Networks in Forecasting Impact of Traffic-Induced Vibrations Transmitted through the Ground on Residential Buildings

2019

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Traffic–induced vibrations may constitute a considerable load to buildings. In this paper, vibrations transmitted through the ground caused by wheeled vehicles are considered. This phenomenon may cause cracking of plaster, cracks in load-bearing elements or even, in extreme cases, collapse of the whole structure. Measurements of vibrations of real structures are costly and laborious. Therefore, the aim of the present paper is to propose a method of using Bayesian networks combined with implementation of geoscience for assessment of impact of traffic–induced vibrations on residential buildings. Firstly, the experimental tests were performed on different buildings using specialized equipment taking into account five factors: Distance from the building to the edge of the road, condition of road surface, condition of the building, the absorption of soil and the type of vehicle. Then, probabilistic analyses applying Bayesian networks were conducted and two methods of assessing the information value (EVSI method and entropy method) were compared. Finally, the developed diagnostic–decision support model was tested, so as to verify the most important parameter, affecting the possibility of structural vibrations to occur. The results of the study clearly showed that the use of Bayesian networks was a very effective approach to assess the impact of traffic-induced vibrations. The developed algorithm could be successfully applied both to existing and planned buildings, for which the source of vibration is already present or may appear in the future.

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“…. , N) is equally likely to take place with a probability of p n = 1/N, the entropy reaches its maximum value equal to log N [42].…”

Section: Rating the Value Of Informationmentioning

confidence: 99%

Section: Rating the Value Of Informationmentioning

confidence: 99%

See 1 more Smart Citation

The Idea of Using Bayesian Networks in Forecasting Impact of Traffic-Induced Vibrations Transmitted through the Ground on Residential Buildings

2019

View full text Add to dashboard Cite

show abstract

Assessment of groundwater quality monitoring network based on information theory

Cited by 1 publication

References 4 publications

The Idea of Using Bayesian Networks in Forecasting Impact of Traffic-Induced Vibrations Transmitted through the Ground on Residential Buildings

The Idea of Using Bayesian Networks in Forecasting Impact of Traffic-Induced Vibrations Transmitted through the Ground on Residential Buildings

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