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A new Fruit Fly Optimization Algorithm: Taking the fifinancial distress model as an example
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# n7 D* |8 Q/ F# x7 ~3 Z A! ]; uThe treatment of an optimization problem is a problem that is commonly researched and discussed by0 N" H9 _7 B5 N ]( Q
scholars from all kinds of fifields. If the problem cannot be optimized in dealing with things, usually lots- w$ g, q( ^/ k& r( ~
of human power and capital will be wasted, and in the worst case, it could lead to failure and wasted
8 ~8 h: S! S) V: mefforts. Therefore, in this article, a much simpler and more robust optimization algorithm compared with8 U, P$ v' n C9 p% a% D4 z8 P
the complicated optimization method proposed by past scholars is proposed; the Fruit Fly Optimization
( ^% R( \7 h E/ H: l/ S8 J/ hAlgorithm. In this article, throughout the process of fifinding the maximal value and minimal value of a
- V/ P6 I- U0 g; h' ?function, the function of this algorithm is tested repeatedly, in the mean time, the population size and
5 r ?. q9 M: |7 |characteristic is also investigated. Moreover, the fifinancial distress data of Taiwan’s enterprise is further
; Z e2 u0 D& c2 \ }. gcollected, and the fruit flfly algorithm optimized General Regression Neural Network, General Regression6 A$ L+ L* [5 P! }' {# z! C
Neural Network and Multiple Regression are adopted to construct a fifinancial distress model. It is found in
) h- I1 C, g0 T X+ q' Kthis article that the RMSE value of the Fruit Fly Optimization Algorithm optimized General Regression, y( B" T$ W8 R8 p
Neural Network model has a very good convergence, and the model also has a very good classifification
3 A" |! u5 J6 u7 n* ?- Gand prediction capability.
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发表于 2020-11-24 17:07
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