Computational Intelligence in Economics and Finance, Volume by Shu-Heng Chen (Editor), Paul P. Wang (Editor), Tzu-Wen Kuo

By Shu-Heng Chen (Editor), Paul P. Wang (Editor), Tzu-Wen Kuo (Editor)

Readers will locate, during this hugely appropriate and groundbreaking booklet, study starting from functions in monetary markets and enterprise management to varied economics difficulties. not just are empirical experiences using numerous CI algorithms provided, yet so are also theoretical types according to computational equipment. as well as direct functions of computational intelligence, readers may also realize how those tools are mixed with traditional analytical tools akin to statistical and econometric versions to yield most well liked effects.

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30 Arnold F. Shapiro tive function was developed using Bayes’ criterion and the second method applied FL. Reference [49] envisioned the decision-making procedure in the selection of an optimal excess of loss retention in a reinsurance program as essentially a maximin technique, similar to the selection of an optimum strategy in noncooperative game theory. As an example, he considered four decision variables (two goals and two constraints) and their membership functions: probability of ruin, coefficient of variation, reinsurance premium as a percentage of cedent’s premium income (Rel.

Following Lemaire’s lead ([49]), [39] and [78] used FES to model the selection process in group health insurance. First single-plan underwriting was considered and then the study was extended to multiple-option plans. In the single-plan situation, Young focused on such fuzzy input features as change in the age/sex factor in the previous two years, change in the group size, proportion of employees selecting group coverage, proportion of premium for the employee and the dependent paid by the employer, claims as a proportion of total expected claims, the loss ratio, adjusted for employer size, and turnover rate.

The evaluation of projected liabilities is fundamental to the insurance and employee benefit industry, so it is not surprising that we are beginning to see SC technologies applied in this area. 3 Only a cursory review of the FL methodologies is discussed in this paper. Readers who prefer a more extensive introduction to the topic, with an insurance perspective, are referred to [56]. Those who are interested in a comprehensive introduction to the topic are referred to [90] and [32]. Readers interested in a grand tour of the first 30 years of fuzzy logic are urged to read the collection of Zadeh’s papers contained in [74] and [45].

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