It is a versatile sequential learning algorithm because the training observations are sequentially (one-by-one or chunk-by-chunk with varying or fixed chunk length) presented to the learning algorithm.
Positional learning is assumed to dominate sequential learning.
In this paper, we follow a novel sequential learning framework to model the disease progression for AD patients׳ care.
In this paper, we present a meta-cognitive sequential learning algorithm for a neuro-fuzzy inference system, referred to as, 'Meta-Cognitive Neuro-Fuzzy Inference System' (McFIS).
The system records users' actions with associated cases and the BN models are prepared to perform sequential learning to increase its performance in diagnostics and advice.
Online Sequential Extreme Learning Machine (OS-ELM) is an online sequential learning neural network algorithm and EOS-ELM is the ensemble method of it.
In this paper, a new fast and accurate two-phase sequential learning scheme for SANN is hereby introduced to guarantee the network performance.
An online sequential learning algorithm, which can learn samples one-by-one or chunk-by-chunk, is developed for extreme learning machine with kernels.
To alleviate this problem, an online sequential learning algorithm for single hidden layer feedforward neural networks – the online sequential extreme learning machine (OSELM) – is automatically updated inexpensively as new data arrive (and the new data can then be discarded).
Sequential learning artificial neural network model proposed by Zhang and Morris (Neural Networks 11 (19981998) 65) is modified to tackle fuzzy inputs and crisp outputs and a sequential learning artificial fuzzy neural network model is developed and used in this paper.
Finally, the very nature of educational interventions involves multiple simultaneous sequential learning methods and experiences.
