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IJCAI
1997
15 years 17 days ago
Extracting Propositions from Trained Neural Networks
This paper presents an algorithm for extract­ ing propositions from trained neural networks. The algorithm is a decompositional approach which can be applied to any neural networ...
Hiroshi Tsukimoto
OL
2011
332views Neural Networks» more  OL 2011»
14 years 6 months ago
A robust implementation of a sequential quadratic programming algorithm with successive error restoration
We consider sequential quadratic programming (SQP) methods for solving constrained nonlinear programming problems. It is generally believed that SQP methods are sensitive to the a...
Klaus Schittkowski
GECCO
2006
Springer
132views Optimization» more  GECCO 2006»
15 years 2 months ago
A neural evolutionary approach to financial modeling
This paper presents an approach to the joint optimization of neural network structure and weights which can take advantage of backpropagation as a specialized decoder. The approac...
Antonia Azzini, Andrea Tettamanzi
IJON
2000
80views more  IJON 2000»
14 years 11 months ago
Synthesis approach for bidirectional associative memories based on the perceptron training algorithm
Bidirectional associative memories are being used extensively for solving a variety of problems related to pattern recognition. In the present paper, a new synthesis approach is d...
Ismail Salih, Stanley H. Smith, Derong Liu
AMC
2007
154views more  AMC 2007»
14 years 11 months ago
A hybrid particle swarm optimization-back-propagation algorithm for feedforward neural network training
The particle swarm optimization algorithm was showed to converge rapidly during the initial stages of a global search, but around global optimum, the search process will become ve...
Jing-Ru Zhang, Jun Zhang, Tat-Ming Lok, Michael R....