Traditional backpropagation neural networks training criterion is based on goodness-of-fit which is also the most popular criterion forecasting. How ever, in the context of financial time series forecasting, we are not only concerned at how good the forecasts fit their target. In order to increase the forecastability in terms of profit earning, we propose a profit based adjusted weight factor f...

ABSTRACT Optimization algorithms are normally influenced by metaheuristic approach. In recent years several hybrid methods for optimization are developed to find out a better solution. The proposed work using meta-heuristic Nature Inspired algorithm is applied with back-propagation method to train a feedforward neural network. Firefly algorithm is a nature inspired meta-heuristic algorithm, and...

In this study have been utilized a modified version of ant colony optimization to improve the thresholds neural networks and weights by including therank-weight approach. Furthermore, technique easily overcome drawbacks speed up convergence into minimum while training backpropagation network. The improved optimization-backpropagation neural.not only has capacity map extensively, but it also enh...