Neural networks cartridges for data mining on time series

Neural networks is one of the techniques used for time series analysis. The performance of neural networks is affected by some parameters such as neural network structure and the quality of data preprocessing. These parameters need to be explored in order to obtain an optimal neural network. However, the manual establishment of different neural networks configurations for selecting the best ones may be error-prone and time-consuming. This paper proposes the creation of neural networks cartridges to systematically empower neural network performance by means of data mining activities, which obtain an optimal neural network structure. The experiments conducted in this paper use stock market and exchange rate series, and show that the usage of neural network cartridges can lead to configurations that double the performance of some ad-hoc neural network configuration.