A new Fruit Fly Optimization Algorithm: Taking the financial distress model a...

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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
; S  w% [( S  a# P9 e8 m3 fscholars from all kinds of fifields. If the problem cannot be optimized in dealing with things, usually lots
of human power and capital will be wasted, and in the worst case, it could lead to failure and wasted
efforts. Therefore, in this article, a much simpler and more robust optimization algorithm compared with
the complicated optimization method proposed by past scholars is proposed; the Fruit Fly Optimization
Algorithm. In this article, throughout the process of fifinding the maximal value and minimal value of a
7 F3 U7 Y! ?1 }) A: |function, the function of this algorithm is tested repeatedly, in the mean time, the population size and
) D# h; b7 C; Z1 Echaracteristic is also investigated. Moreover, the fifinancial distress data of Taiwan’s enterprise is further
collected, and the fruit flfly algorithm optimized General Regression Neural Network, General Regression
Neural Network and Multiple Regression are adopted to construct a fifinancial distress model. It is found in
this article that the RMSE value of the Fruit Fly Optimization Algorithm optimized General Regression
* d9 B0 ^+ U% x! L9 [6 T% ]) SNeural Network model has a very good convergence, and the model also has a very good classifification
5 q( e1 O, I/ n- dand prediction capability.
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NNNei256

哎呀呀，上英文 了