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A new Fruit Fly Optimization Algorithm: Taking the fifinancial distress model as an example ' d' n: m, u* p/ e& m
8 j- k: V$ n/ A7 \9 v5 sThe treatment of an optimization problem is a problem that is commonly researched and discussed by
$ l5 k2 q% O0 d! ^# uscholars from all kinds of fifields. If the problem cannot be optimized in dealing with things, usually lots- Z# p4 L, }+ {: l, I0 p; ]: J _, V
of human power and capital will be wasted, and in the worst case, it could lead to failure and wasted
$ n) X) c' l7 D) X' u L. j7 I* `efforts. Therefore, in this article, a much simpler and more robust optimization algorithm compared with3 Z6 o3 b0 m1 B! q6 b: i) G N1 @
the complicated optimization method proposed by past scholars is proposed; the Fruit Fly Optimization: F% j7 m5 ~4 m! Y" e) ]
Algorithm. In this article, throughout the process of fifinding the maximal value and minimal value of a! J$ X$ U! ^% J: Y& \, e
function, the function of this algorithm is tested repeatedly, in the mean time, the population size and
2 J% j4 Y8 p- y4 v# r: N Xcharacteristic is also investigated. Moreover, the fifinancial distress data of Taiwan’s enterprise is further. f. R6 x: y; G
collected, and the fruit flfly algorithm optimized General Regression Neural Network, General Regression% O' T- b( ]$ M$ \
Neural Network and Multiple Regression are adopted to construct a fifinancial distress model. It is found in' U3 k7 r2 q4 B$ m
this article that the RMSE value of the Fruit Fly Optimization Algorithm optimized General Regression1 c& x8 _3 N6 x( ~# V
Neural Network model has a very good convergence, and the model also has a very good classifification. w, g4 G7 Q2 j4 D
and prediction capability.
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发表于 2020-11-24 17:07
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