Constructive Feedforward ART Clustering Networks—Part I

Constructive Feedforward ART Clustering Networks—Part II

Part I of this paper defines the class of constructive unsupervised on-line learning simplified adaptive resonance theory (SART) clustering networks. Proposed instances of class SART are the symmetric Fuzzy ART (S-Fuzzy ART) and the Gaussian ART (GART) network. In Part II of our work, a third network belonging to class SART, termed fully self-organizing SART (FOSART), is presented and discussed...

Learning capability and storage capacity of two-hidden-layer feedforward networks

The problem of the necessary complexity of neural networks is of interest in applications. In this paper, learning capability and storage capacity of feedforward neural networks are considered. We markedly improve the recent results by introducing neural-network modularity logically. This paper rigorously proves in a constructive method that two-hidden-layer feedforward networks (TLFNs) with 2/...

Constructive algorithms for structure learning in feedforward neural networks for regression problems

In this survey paper, we review the constructive algorithms for structure learning in feedforward neural networks for regression problems. The basic idea is to start with a small network, then add hidden units and weights incrementally until a satisfactory solution is found. By formulating the whole problem as a state-space search, we first describe the general issues in constructive algorithms...

ستفاده ‎از خوشه‎بندی‌های پیاپی نقشه خودسازمانده برای بهبود پیش‌بینی پیک ‎بار الکتریکی روزانه مبتنی بر شبکه‌های عصبی پیشخوراند

Enhanced random search based incremental extreme learning machine

Recently an incremental algorithm referred to as incremental extreme learning machine (I-ELM) was proposed by Huang et al. [G.-B. Huang, L. Chen, C.-K. Siew, Universal approximation using incremental constructive feedforward networks with random hidden nodes, IEEE Trans. Neural Networks 17(4) (2006) 879–892], which randomly generates hidden nodes and then analytically determines the output weig...