基于双目标滑模控制算法的泛化控制

VII Brazilian Symposium on Neural Networks, 2002. SBRN 2002. Proceedings. Pub Date : 2002-11-11 DOI:10.1109/SBRN.2002.1181432

M. Costa, A. Braga, B. R. Menezes, G. G. Parma, R. A. Teixeira

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引用次数: 1

摘要

本文提出了一种新的滑模控制算法，该算法能够在由训练集误差和权向量范数两个目标构成的平面内引导多层感知器的轨迹。结果表明，所得到的神经网络能够生成Pareto集，并从中选择验证误差最小的模型。

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Control of generalization with a bi-objective sliding mode control algorithm

This paper presents a new sliding mode control algorithm that is able to guide the trajectory of a multilayer perceptron within the plane formed by the two objectives: training set error and norm of the weight vectors. The results show that the neural networks obtained are able to generate the Pareto set, from which a model with the smallest validation error is selected.

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VII Brazilian Symposium on Neural Networks, 2002. SBRN 2002. Proceedings.

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