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Even if a company expects to be paid in its own currency, it must assess the risk that the buyer may not be able to pay the full amount due to currency fluctuations.

They also incorporate genetic algorithm as an optimizing technique for adapting parameters of ANN which is then compared with standard backpropagation and backpropagation combined with K-means clustering algorithm.

Finally, the authors find out that their suggested hybrid neural network is able to produce more accurate forecasts than the standard models and can be helpful in eliminating the risk of making the bad decision in decision-making process. Profits or losses accrue as the exchange rate of that currency fluctuates on the open market.

In order to determine which is the fixed currency when neither currency is on the above list (i.e.

both are "other"), market convention is to use the fixed currency which gives an exchange rate greater than 1.000.

The authors suggest a new hybrid neural network which is a combination of the standard RBF neural network, a genetic algorithm, and a moving average.

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