基于Python的历史文化景区用电特征可视化预测研究
Research on Visual Prediction of Electricity Consumption Characteristics in Historical and Cultural Scenic Spots Based on Python

随着黑龙江特色文旅产业的快速发展，如何使历史文化景区具备绿色安全的运营方式开始变得备受关注。使用基于Python语言等技术对文化景区用电特征进行预测，可以行之有效地解决景区运营统筹管理问题，并为今后特色文旅产业规划提供有力依据。使用Python编程语言在TensorFlow框架的基础上，实现对景区能耗方面数据的分析，包括数据集内的数据分布、用电稳定性和用电量损失函数曲线等情况进行快速清晰的展示，科学准确地对此类特定文旅的用电特征进行判断，并对未来短时间内的用电量进行快速准确的预测等功能。
With the rapid development of Heilongjiang’s characteristic cultural and tourism industry, how to make historical and cultural scenic spots have green and safe operation methods has become a concern. Using technologies such as Python to predict the electricity consumption characteristics of cultural scenic spots can effectively solve the problem of overall operation and management of scenic spots, and provide strong basis for future planning of characteristic cultural and tourism industries. Using Python programming language on the basis of TensorFlow framework, the analysis of energy consumption data in scenic spots is implemented, including the rapid and clear display of data distribution, electricity stability, and electricity loss function curve in the dataset. Scientific and accurate judgment of the electricity consumption characteristics of such specific cultural tourism is made, and the future electricity consumption in a short period of time is predicted quickly and accurately.