Under the background of large data, demand forecasting of rural tourism based on intelligent algorithm is a new direction to promote the development of rural tourism industry. This paper mainly studies the application of neural network intelligent algorithm in rural tourism. Firstly, from the perspective of inbound tourism demand, the influencing factors of inbound tourism demand are clarified. Considering the influence degree and quantification difficulty of each factor, seven influencing factors are extracted to construct the inbound tourism feature vector. Then taking Yangjiang inbound tourism as an example, we use the neural network model to forecast the number of inbound tourists in Yangjiang from 2018 to 2019. The mean square error of the network is 0.011695 and the coefficient R² is 0.94744; the results of the model are acceptable. Finally, from the perspectives of changing marketing strategy and pricing strategy, this paper puts forward some suggestions for the improvement of rural tourism.

中文翻译：

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基于BP神经网络挖掘算法的旅游文化与需求预测。

在大数据的背景下，基于智能算法的乡村旅游需求预测是推动乡村旅游产业发展的新方向。本文主要研究神经网络智能算法在乡村旅游中的应用。首先，从入境旅游需求的角度，明确了入境旅游需求的影响因素。考虑到每个因素的影响程度和量化难度，提取了七个影响因素以构建入境旅游特征向量。然后以阳江入境旅游为例，利用神经网络模型预测阳江市2018年至2019年入境旅游人数。网络均方误差为0.011695，系数R ²是0.94744; 模型的结果是可以接受的。最后，从改变营销策略和定价策略的角度出发，对乡村旅游的发展提出了一些建议。