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- W3011330600 abstract "This paper proposes a method for parameter optimization of the interval-valued Campbell-Bennett model proposed by Utkin and Chekh using the Particle Swarm optimization (PSO) method. Campbell-Bennett model is a OneClass Classification (OCC) model, whose dual problems can be expressed as a set of simple linear programming problems. Utkin uses the triangular kernel function approximation to replace the Gaussian kernel function in the Campbell-Bennett model, and thus obtains a finite set of simple linear optimization problems for processing interval-valued data. However, the complexity of this method is too high, making it difficult to optimize model parameters. In order to avoid this high complexity, we use a special method to optimize the model parameters with PSO and verify it with numerical experiments." @default.
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- W3011330600 date "2019-10-01" @default.
- W3011330600 modified "2023-09-24" @default.
- W3011330600 title "An Improved Interval-Valued Campbell-Bennett OCC Model Based on PSO" @default.
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- W3011330600 doi "https://doi.org/10.1109/icsess47205.2019.9040786" @default.
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