The cascade-correlation learning architecture
Advances in neural information processing systems 2
A Divide-and-Conquer Learning Approach to Radial Basis Function Networks
Neural Processing Letters
Neural modeling of relative air humidity
Computers and Electronics in Agriculture
Interactive mining and semantic retrieval of videos
Proceedings of the 8th international workshop on Multimedia data mining: (associated with the ACM SIGKDD 2007)
Neural network ensembles for time series forecasting
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
A human-centered multiple instance learning framework for semantic video retrieval
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Intelligent agents for real time data mining in telecommunications networks
AIS-ADM'07 Proceedings of the 2nd international conference on Autonomous intelligent systems: agents and data mining
Modeling POMDPs for generating and simulating stock investment policies
Proceedings of the 2010 ACM Symposium on Applied Computing
Learning approaches for developing successful seller strategies in dynamic supply chain management
Information Sciences: an International Journal
Fault Detection, Diagnosis and Prediction in Electrical Valves Using Self-Organizing Maps
Journal of Electronic Testing: Theory and Applications
Data stream forecasting for system fault prediction
Computers and Industrial Engineering
Expert Systems with Applications: An International Journal
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Neural Network approaches to time series prediction are briefly discussed, and the need to find the appropriate sample rate and an appropriately sized input window identified. Relevant theoretical results from dynamic systems theory are briefly introduced, and heuristics for finding the appropriate sampling rate and embedding dimension, and thence window size, are discussed. The method is applied to several time series and the resulting generalisation performance of the trained feed-forward neural network predictors is analysed. It is shown that the heuristics can provide useful information in defining the appropriate network architecture.