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In order to assist traders with scientific transaction strategy, this paper constructs a decision model including a prediction model and a trading model. Our predicting model is based on a BiLSTM (Bi-direction Long Short-Term Memory) neural network, and two linear layers trained by previous known data, which obtains a high accurate prediction of price. For the trading model, we construct it with several impact and quantitative artificial-selected-factors including market potential, deviation rate, risk score, etc. To use the model, we firstly uses previous known data to train the deep neural network and utilize it to make future predictions, the results of which is then imported into our trading model for decision making and better configure the portfolio.  Generally speaking, our whole decision system achieves effective prediction of price, enables timely risk assessment, and makes scientific decisions by considering these factors together.

This paper develops a method to quantify the evolution of music and understand the role of humans in the evolution of music. First, a directional music influence network was set to show the parameters of "music influence". Then, a sub-network of the direct influencer network was established to obtain influence relationships, and "musical influence" was described and stored in this sub-network. Finally, a music similarity test model is used to compare which is more similar between artists of the same genre and artists of different genres. By comparing the influence and similarity between genres, the difference and connection of genres was got. Analyze whether "influencers" can actually influence their artists and their music through the above-mentioned similarity data. Then analyze the influence of music characteristics. Identify features representing major evolutions in the development of music from the data and get influencers in the network that represent major evolutions; analyze the evolution of a musical genre over time and explain how the genre or artist has changed over time; and illustrate how the model Express the social, political or technological change at the time.