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A new Fruit Fly Optimization Algorithm: Taking the fifinancial distress model as an example 6 o! z7 }1 S, v
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The treatment of an optimization problem is a problem that is commonly researched and discussed by
1 e, D6 S6 B* [& j( escholars from all kinds of fifields. If the problem cannot be optimized in dealing with things, usually lots* x, v5 Z# B7 K% q$ `
of human power and capital will be wasted, and in the worst case, it could lead to failure and wasted
2 r% z e+ H. m6 n/ {. E1 iefforts. Therefore, in this article, a much simpler and more robust optimization algorithm compared with& Q6 G* k! W. z+ \
the complicated optimization method proposed by past scholars is proposed; the Fruit Fly Optimization
1 D; }- w* {2 m! m& `. `. Y2 XAlgorithm. In this article, throughout the process of fifinding the maximal value and minimal value of a0 M) H& U' j8 q5 Y& z- i% Z
function, the function of this algorithm is tested repeatedly, in the mean time, the population size and, S- n0 q5 S3 M* _
characteristic is also investigated. Moreover, the fifinancial distress data of Taiwan’s enterprise is further4 |! _9 k" u( `# M* u% I! x, \ D
collected, and the fruit flfly algorithm optimized General Regression Neural Network, General Regression
7 q3 }: G. s9 Y$ h% C& P; {Neural Network and Multiple Regression are adopted to construct a fifinancial distress model. It is found in
5 ~/ L* P) [/ Y# |" tthis article that the RMSE value of the Fruit Fly Optimization Algorithm optimized General Regression
9 p/ h" i& N+ Q# M$ p" x) V9 vNeural Network model has a very good convergence, and the model also has a very good classifification
B2 G% z& J; U/ h! ] Qand prediction capability.
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发表于 2020-11-24 17:07
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