Global optimization over unbounded domains
SIAM Journal on Control and Optimization
An interval algorithm for constrained global optimization
ICCAM'92 Proceedings of the fifth international conference on Computational and applied mathematics
An interval maximum entropy method for a discrete minimax problem
Applied Mathematics and Computation
Experiments with a new selection criterion in a fast interval optimization algorithm
Journal of Global Optimization
Training Product Unit Neural Networks with Genetic Algorithms
IEEE Expert: Intelligent Systems and Their Applications
Methods and Applications of Interval Analysis (SIAM Studies in Applied and Numerical Mathematics) (Siam Studies in Applied Mathematics, 2.)
Neural network output optimization using interval analysis
IEEE Transactions on Neural Networks
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A global optimal algorithm based on novel interval analysis was proposed for Feedforward neural networks (FNN). When FNN are trained with BP algorithm, there exists some local minimal points in error function, which make FNN training failed. In that case, interval analysis was took into FNN to work out the global minimal point. For interval FNN algorithm, an interval extension model was presented, which creates a narrower interval domain. And more, in the FNN training, hybrid strategy was employed in discard methods to accelerate the algorithm's convergence. In the proposed algorithm, the objective function gradient was utilized sufficiently to reduce the training time in both interval extension and discard methods procedure. At last, simulation experiments show the new interval FNN algorithm's availability.