An Efficient Information Retrieval Method for Brownfield Assessment with Sparse Data*

Özdamar, Linet; Demirhan, Melek

doi:10.1007/10966518_25

Cited by 1 publication

(2 citation statements)

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“…The function given in (8) aims to simulate polluted sites with randomly generated pollution profiles. It is able to produce disjunctive nonconvex surfaces whose topologies are expected to challenge FTs performance (8) Here, the summation is taken over a random number of functions where is uniformly distributed over [3], [13]. The coefficients are also uniform random numbers satisfying, for .…”

Section: A Results On Hypothetical Sitesmentioning

confidence: 99%

“…Experiments with numerous sets of real data indicate that the logarithmic function defined in (7) is appropriate for classification [13]. The membership and potential functions selected here are also reported to work well in early imaging applications [14] ( 7) where is the number of samples that fall within and is a normalizing constant.…”

Section: B Assessment Schemementioning

confidence: 94%

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Fuzzy Tessellation Approach for Environmental Site Characterization

Özdamar

Demirhan

2005

IEEE Trans. Syst., Man, Cybern. C

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Environmental site investigations are carried out prior to the reclamation of industrially contaminated sites. It is required to take samples and analyze the laboratory reports to find out the distribution of contaminants over the site. In this study, an algorithm based on fuzzy assessment and overlapped partitioning is proposed to identify the topology of polluted areas in a given industrial site. The primary objective is to locate contaminated zones accurately with sparse data in a preliminary investigation and the second is to reduce the size of the area that is resubjected to expensive sampling methods (such as deep drilling) in the detailed phase of the investigation. If these objectives are achieved, a considerable cost reduction occurs in the process of site characterization.

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