Abstract. The time series data of 31 wildfires in 2012 in the US were analyzed. The fractal dimensions (FD) of the wildfires during spreading were studied and their geological features were identified. A growth model based on the cellular automata method is proposed here. Numerical study was performed and is shown to give good agreement with the fractal dimensions and scaling behaviors of the corresponding empirical data.

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Maximizing returns is always peoples investment goal. Stocks have some hedging capabilities, and their prices also fluctuate widely, making them popular in-vestments for investors. As a result, Stock prices have fluctuated wildly, leading to uncertain investments and uncertain returns. To compute and analyze the maximum returns of stocks in Hong Kong stocks, this paper takes The Hang Seng index, an important indicator of Hong Kong stock market prices as the scene. We calculate the variance of these stocks using the Fama experiment. And We examined the normal distribution and i.i.d. of the data. To test whether the hypothesis of independence and the same distribution in the data is reasonable, and then con-duct an ACF test on the five selected stocks to observe their time-series stability. Then, this paper uses Markowitz's effective frontier decision-making process to simulate stock trading and use the Sharp ratio risk analysis to select mid-risk and high-yield portfolios. The results show that: The weight of the five stocks shows an approximate trend with their average return rate. The larger the average value is, the larger the investment proportion will be. stock investment with low-risk accounts for a relatively high proportion, while stock investment with high-risk accounts for a relatively small proportion. Among the selected several representative stocks, Techtronic Industries and Long for Group have more investment value, while the investment value of bank stocks is on the low side.