Prediction Of International Market Price Of U₃O₈ Based On Neural Network

The artificial neural networks is a newly developed interdisciplinary. It is a non-linear information processing system to imitate the structure and function of human brain.It possesses learning ability, parallelism, robustness and easiness for hardware implementation. It mainly applies to pattern classification, function approximation and date compression. Neural networks have developed rapidly in the past twenty years and have got a wide application in the fields of price prediction.Uranium price market is a highly complicate nonlinear system, whose variation does not have its own regulation, but also is influenced by many other factors, such as politics and economy. The tradition prediction techniques based on statistics face difficulties in uranium price research. Neural network have the virtue of self-organization and adaptability and can excavate the valuable information from historical data. So it is suitable to solve the problem in uranium price prediction.However, by now, researches did not established the relevant prediction models for uranium price at present. The paper mainly includes the following works:(1)The paper briefy introduces some basic knowledge on neural network and effected factors of uranium price. Using single hidden layer and multiple output system, a BP network model was built up to forecast the trend of uranium price in the next five months;(2)The paper briefy introduces how to realize BP neural network in MATLAB,how to create, initiate, train and simulate a network and some functions usually used in MATLAB.And a program is written to realize the BP network;(3)The paper does a experiment on the uranium price in the recent twenty years.,proves that the model and research method is effective.Compared with the prediction results, the results is briefly accepted, demonstrating that the forecasting model based on BP network has a good ability to forecast and generalize.