Time series data is common in many settings including scientific and financial applications. In these applications, the amount of data is often very large. We seek to support pred...
Effort to evolve and maintain a software system is likely to vary depending on the amount and frequency of change requests. This paper proposes to model change requests as time se...
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 ...
TheexactlikelihoodfunctionofaGaussianvectorautoregressive-movingaverage(VARMA)model is evaluated in two nonstandard cases: (a) a parsimonious structured form, such as obtained in ...
In this study, a hybrid intelligent data mining methodology, genetic algorithm based support vector machine (GASVM) model, is proposed to explore stock market tendency. In this hyb...