基于BP神经网络的太白山生态旅游研究

发布时间：2018-05-01 05:14

本文选题：旅游需求 + 神经网络　；参考：《西北农林科技大学》2013年硕士论文

【摘要】：旅游市场需求预测常见的方法有：时间序列预测法和因果模型预测法。然而旅游市场往往受到许多因素的影响，这些因素之间关系错综复杂，而且有很多不可预知的因素，常见的方法难以得到可靠的预测结果。人工神经网络是模拟大脑的神经网络结构和功能的数学模型，它是由大量处理单元组成的自适应动态系统，用来处理数据样本中的非线性关系，具有良好的自适应性、自组织及很强的学习、容错和抗干扰能力，可以对复杂系统进行灵活方便的建模，使得它在实际应用中成为一种很好的分类和预测工具。一般来说，旅游市场是受到许多不可预知因素的影响，所以在进行旅游市场需求预测时用神经网络模型分析是比较优越的。本文分析、研究了人工神经网络的基本理论、预测方法，对预测指标、预测模型的选择、建模流程和方法进行了初步探讨。本文用BP神经网络模型对太白山自然保护区生态旅游需求进行了预测分析。结果证实了该模型的有效性。在太白山自然保护区生态旅游需求预测中，采用2-8-1神经网络结构，预测了太白山自然保护区2011～2020年旅游人数，，将实验数据与实际数据作对比，表明该模型有良好预测能力，网络泛化能力良好。
[Abstract]:The common methods of tourism market demand prediction are: time series forecasting and causality model forecasting. However, the tourism market is often affected by many factors, these factors are intricate, and there are many unpredictable factors, common methods are difficult to obtain reliable prediction results. Artificial neural network is a mathematical model that simulates the neural network structure and function of the brain. It is an adaptive dynamic system composed of a large number of processing units, which is used to deal with nonlinear relationships in data samples and has good adaptability. Self-organization and strong learning, fault-tolerant and anti-interference ability, can be used for flexible and convenient modeling of complex systems, which makes it a good tool for classification and prediction in practical applications. Generally speaking, the tourism market is affected by many unpredictable factors, so it is better to use neural network model to forecast the demand of tourism market. In this paper, the basic theory and prediction method of artificial neural network are analyzed and studied. The prediction index, the selection of prediction model, the modeling process and method are discussed preliminarily. In this paper, the demand for ecotourism in Taibai Mountain Nature Reserve is predicted by BP neural network model. The results show that the model is effective. In the prediction of ecotourism demand in Taibai Mountain Nature Reserve, 2-8-1 neural network structure was used to predict the tourism population in Taibai Mountain Nature Reserve from 2011 to 2020. The comparison between experimental data and actual data shows that the model has good predictive ability. Network generalization ability is good.
【学位授予单位】：西北农林科技大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：F592.7;TP183

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