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ICNC
2010
Springer
9 years 29 days ago
A hybrid intelligent early warning system for predicting economic crises: The case of China
—This paper combines artificial neural networks (ANN), fuzzy optimization and time-series econometric models in one unified framework to form a hybrid intelligent early warning...
Dongwei Su, Xingxing He
INFORMATICALT
2007
123views more  INFORMATICALT 2007»
9 years 2 months ago
Design and Implementation of Parallel Counterpropagation Networks Using MPI
The objective of this research is to construct parallel models that simulate the behavior of artificial neural networks. The type of network that is simulated in this project is t...
Athanasios Margaris, Stavros Souravlas, Efthimios ...
ENGL
2007
89views more  ENGL 2007»
9 years 2 months ago
Similarity-based Heterogeneous Neural Networks
This research introduces a general class of functions serving as generalized neuron models to be used in artificial neural networks. They are cast in the common framework of comp...
Lluís A. Belanche Muñoz, Julio Jose ...
EAAI
2007
90views more  EAAI 2007»
9 years 2 months ago
AI techniques in modelling, assignment, problem solving and optimization
This paper recapitulates the results of a long research on a family of artificial intelligence (AI) methods—relying on, e.g., artificial neural networks and search techniques...
Zsolt János Viharos, Zsolt Kemény
NIPS
1989
9 years 3 months ago
The Cascade-Correlation Learning Architecture
Cascade-Correlation is a new architecture and supervised learning algorithm for artificial neural networks. Instead of just adjusting the weights in a network of fixed topology,...
Scott E. Fahlman, Christian Lebiere
NIPS
2003
9 years 3 months ago
Reasoning about Time and Knowledge in Neural Symbolic Learning Systems
We show that temporal logic and combinations of temporal logics and modal logics of knowledge can be effectively represented in artificial neural networks. We present a Translat...
Artur S. d'Avila Garcez, Luís C. Lamb
ICML
1991
IEEE
9 years 6 months ago
Constructive Induction in Knowledge-Based Neural Networks
Artificial neural networks have proven to be a successful, general method for inductive learning from examples. However, they have not often been viewed in terms of constructive ...
Geoffrey G. Towell, Mark Craven, Jude W. Shavlik
EWLR
1999
Springer
9 years 6 months ago
Toward Seamless Transfer from Simulated to Real Worlds: A Dynamically-Rearranging Neural Network Approach
In the field of evolutionary robotics artificial neural networks are often used to construct controllers for autonomous agents, because they have useful properties such as the ab...
Peter Eggenberger, Akio Ishiguro, Seiji Tokura, To...
IJCNN
2000
IEEE
9 years 6 months ago
Probabilistic Neural Network Models for Sequential Data
It has already been shown how Artificial Neural Networks (ANNs) can be incorporated into probabilistic models. In this paper we review some of the approaches which have been prop...
Yoshua Bengio
NEUROSCIENCE
2001
Springer
9 years 7 months ago
Finite-State Computation in Analog Neural Networks: Steps towards Biologically Plausible Models?
Abstract. Finite-state machines are the most pervasive models of computation, not only in theoretical computer science, but also in all of its applications to real-life problems, a...
Mikel L. Forcada, Rafael C. Carrasco
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