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06.35.61

Thiết kế giải thuật tiến hóa đa mục tiêu giải bài toán dự báo tỉ giá ngoại tệ

Designing multi-objective evolutionary algorithm: Solving the problem of exchange rate forecast

Khoa học và công nghệ (Đại học Thái Nguyên

2015

14

3-9

1859-2171

Time series forecasting is a field which paid a considerable attention of the research community. At present, in the field of machine learning, there are a lot of studies using evolutionary algorithms trained artificial neural networks to construct the model of time series forecast in general, and foreign currency exchange rates forecast, in particular. There are two issues to consider: First, the global convergence of the extreme solutions using evolutionary algorithms; Second, determine the optimal weight of the network. In this paper, the authors propose an algorithm designed multi-objective evolutionary (NSGA-II) trained neural network and application problems in forecasting exchange rates. Two objectives of the selected model include: MSE and DIY. The model proposed in the four experimental data sets monetary and compare with single-objective method which the research community did. Through MSE indicators from experimental results show that the model that the authors proposed to forecast better results some simple methods existing goals.

TTKHCNQG, CTv 178