Accurate Calculation of the Area of Jianghan University Based on Monte Carlo Algorithm

Abstract

The present paper presents a precise calculation of the campus area of Jianghan University using the Monte Carlo algorithm. This method is demonstrated to be both efficient and practical in estimating the area of complex irregular shapes. The Monte Carlo method is a probabilistic approach that transforms geometric area problems into models through the principles of random sampling. In the implementation stage, the vector boundary data of the campus is initially acquired via map APIs in order to define the regional judgment criteria. Subsequently, many uniformly distributed random points are generated within a bounding rectangle covering the campus. The calculation of the proportion of points falling within the campus area is achieved by meticulously enumerating the points and subsequently determining the area of the campus. This proportion is then combined with the area of the bounding rectangle to estimate the actual area of the campus. The implementation of the algorithm is undertaken using Python programming, and the positive correlation between the number of sampling points (e.g., millions) and accuracy is verified. The experimental results obtained from this study indicate a high degree of reliability in calculating the area of Jianghan University. It is further demonstrated that errors can be reduced by increasing the number of sampling points or by averaging multiple trial results.