福建省纺织业可持续发展预警研究——基于遗传算法—支持向量机模型

社会的快速发展，给传统产业的发展带来了许多挑战，为了使传统产业能够在面临诸多不确定性下持续发展，预警是非常必要的。本文从经济发展水平、资源供应能力、科技投入力度和与社会、环境协调发展能力四个方面建立福建纺织业可持续发展指标体系，并借助灰关联分析法分析各指标与可持续发展之间的关联度。然后，利用GA优化SVM，构建GA-SVM预警模型，预测2015-2017年纺织业可持续发展能力，并将预测结果与实际相比较，发现预测结果与实际情况相符，且预测精度较高，说明所构建的预警模型具有较好的预警效果，其预警结果能够为产业可持续发展的警情监测提供有效信息。

Based on GA-SVM Model Sustainable Development Early Warning Research of Textile Industry in Fujian Province

The rapid development of society has brought many challenges to the development of traditional industries. In order to make the traditional industry sustainable development in the face of many uncertainties, early warning is very necessary. The paper establishes the sustainable development index system of Fujian textile industry from four aspects: economic development level, resource supply capacity, science and technology investment intensity, and the ability of coordinating development with society and environment, and the index system of sustainable development of textile industry is established. And Grey correlation analysis method is used to analyze the correlation degree between each index and sustainable development. Then, optimizing SVM by genetic algorithm, the GA-SVM warning model is built to predict textile industry sustainable development ability in 2015-2017. By comparing the prediction results with the actual situation, it is found that the prediction results are consistent with the actual situation and the prediction accuracy is high. It shows that the early-warning model has a good early-warning effect, and the prediction results can provide effective information for the warning monitoring of the sustainable development of the industry.