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A new Fruit Fly Optimization Algorithm: Taking the fifinancial distress model as an example
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The treatment of an optimization problem is a problem that is commonly researched and discussed by
/ M& P- S+ c8 W$ Q6 Qscholars from all kinds of fifields. If the problem cannot be optimized in dealing with things, usually lots
- d) @4 ]- j4 l& F' {of human power and capital will be wasted, and in the worst case, it could lead to failure and wasted
4 \1 j- Y& {! V" K8 o5 U0 |efforts. Therefore, in this article, a much simpler and more robust optimization algorithm compared with/ X5 _6 E$ q* ]4 @8 ^) n
the complicated optimization method proposed by past scholars is proposed; the Fruit Fly Optimization
5 y- `2 M$ u& L- OAlgorithm. In this article, throughout the process of fifinding the maximal value and minimal value of a
2 O: H/ b F* v, O3 Yfunction, the function of this algorithm is tested repeatedly, in the mean time, the population size and
1 i( o: U- h/ p$ H* @characteristic is also investigated. Moreover, the fifinancial distress data of Taiwan’s enterprise is further6 D6 E" g* T% q9 @
collected, and the fruit flfly algorithm optimized General Regression Neural Network, General Regression
8 I- N9 B! o* L; cNeural Network and Multiple Regression are adopted to construct a fifinancial distress model. It is found in Y" ]+ N6 ]% l9 p w
this article that the RMSE value of the Fruit Fly Optimization Algorithm optimized General Regression
2 v- h; `9 r1 j' S! kNeural Network model has a very good convergence, and the model also has a very good classifification
4 O- p+ h5 T# K2 l. R7 y x' K9 I2 Vand prediction capability.
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发表于 2020-11-24 17:07
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