Fuzzy Decision-Making Analysis of Quantitative Stock Selection in VR Industry Based on Random Forest Model

Abstract

Since Professor L.A. Zadeh published “Fuzzy Set Theory” in the 1960s, the theory of fuzzy mathematics has been formally established and developed and has been gradually introduced into work in all walks of life. At the same time, fuzzy mathematics theory has also been widely used in VR industry selection. In the stock strategy, the advantages of improving unit classification accuracy, screening high-quality stocks, and constructing near-perfect investment portfolios continue to emerge. On the other hand, with the increasing maturity and continuous development of China’s computer and Internet technologies, the VR industry has gained a new round of development space, and its own investment value and the investable space between related industries have been gradually tapped. Different from the analysis of quantitative stock selection by constructing a logistics multifactor stock selection model in the existing research, the research mainly adopts the random forest algorithm based on fuzzy mathematics to construct the initial investment strategy portfolio. Secondly, different from the single effective frontier algorithm, the research is based on the random forest algorithm, calculates the average AUC of the index, and continuously checks and tests the results to obtain the optimal investment portfolio. Finally, select appropriate risk indicators and performance indicators to evaluate the performance of the strategy portfolio. The study concludes that the portfolios selected by the random forest model are highly investable and have good stability.

Intelligent Application of Raw Material Supply Chain Planning System Based on Genetic Algorithm

“…As shown in Figures 7 and 8, we can see the distribution of chromosomes, orange represents 1, and white represents 0. Under the optimization model of the genetic algorithm we designed, we provide suitable raw material suppliers and forwarders for each cycle according to the needs of enterprises, reducing the impact of subjective factors, which is conducive to enterprises to quickly lock in upstream supply chain partners, reduce costs and costs, and meet the raw material needs of enterprises in various periods [38,39]. As shown in Figure 9, the genetic algebra used in the multiobjective genetic algorithm model we constructed is very small, with a maximum of no more than 50 generations.…”

Analysis of Digital Life Effect of Residents’ Trust Based on Multivariate Discrete Choice Model

“…Considering the household and individual questionnaire data of the CHFS published in 2013, 2015, and 2017 as research samples, this study uses the O-probit model to gauge the trust of residents in digital life while conducting a marginal effect analysis. The results show that digital life has a positive impact on residents' trust [35].…”

Prediction and Risk Assessment of Extreme Weather Events Based on Gumbel Copula Function

“…For the accuracy of the model, we should modify the fixed bandwidth in the model by using smaller bandwidths in regions with dense data points and larger bandwidths in regions with data point coefficients and by adding Bayesian information to the model measurements. Thus, the accuracy of the model will be further improved [34][35][36]. For outliers in the results, we should add the local Moran index, compare the global and local Moran index results, and eliminate outliers.…”