In this paper neuro-fuzzy synergism is applied to implement content sequencing in adaptive hypermedia systems. The level of understanding of the learner is used to construct lesson...
Kyparisia A. Papanikolaou, George D. Magoulas, Mar...
In reinforcement learning (RL), the duality between exploitation and exploration has long been an important issue. This paper presents a new method that controls the balance betwe...
We propose a class of Bayesian networks appropriate for structured prediction problems where the Bayesian network's model structure is a function of the predicted output stru...
Bayesian networks are directed acyclic graphs that represent dependencies between variables in a probabilistic model. Many time series models, including the hidden Markov models (H...
This paper presents an adaptive neuro-fuzzy inference system (ANFIS) for USD/JPY exchange rates forecasting. Previous work often used time series techniques and neural networks (NN...
Meysam Alizadeh, Roy Rada, Akram Khaleghei Ghoshe ...