Neural networks and natural intelligence
Neural networks and natural intelligence
Component software: beyond object-oriented programming
Component software: beyond object-oriented programming
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
SEI's Software Product Line Tenets
IEEE Software
On Plug-ins and Extensible Architectures
Queue - Patching and Deployment
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Statistical analysis of simulation output: state of the art
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Chaotic Time Series Prediction Using a Neuro-Fuzzy System with Time-Delay Coordinates
IEEE Transactions on Knowledge and Data Engineering
Surveying stock market forecasting techniques - Part II: Soft computing methods
Expert Systems with Applications: An International Journal
Workflows and e-Science: An overview of workflow system features and capabilities
Future Generation Computer Systems
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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.