Second Degree Chance Constraints with Lognormal Random Variables - An Application to Fisher's Discriminant Function for Separation of Populations

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Summary

A transformation procedure of the second-degree chance constraints to the deterministic constraints for mathemat ical programming problems having general second degree chance constraints with lognormal random variables is discussed.

Type
article
Published
2013-01-01
Cited by
2
References
23
Access
Open access

Keywords

Degree (music), Mathematics, Linear programming, Linear discriminant analysis, Function (biology)

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