• 关键词：城市生态系统  协调发展度  支持向量机  偏最小二乘法  主成分分析

• 基金项目：国家自然科学基金(No.60474077);华中科技大学博士后基金(No.0128184008)

• 李湘梅
• 1. 华中科技大学环境科学与工程学院, 武汉 430074; 2. 华中科技大学系统工程研究所, 武汉 430074

• 周敬宣
• 华中科技大学环境科学与工程学院, 武汉 430074

• 张娴
• 华中科技大学环境科学与工程学院, 武汉 430074

• 肖人彬
• 华中科技大学系统工程研究所, 武汉 430074

• 摘要：以武汉市为例,通过定性和定量方法建立了一套相对完整的评价指标体系,以主成分分析和协调发展度模型计量得到的武汉市1988～2004年协调发展度值作为输出,以偏最小二乘法筛选出协调发展度的重要影响因子作为输入,尝试采用支持向量机对武汉市总体规划期间(2005～2020年)的协调发展状况进行了模拟研究.研究结果表明,1988～2004年武汉市经济、社会、资源环境的耦合状态由严重失调逐渐趋向勉强协调,这期间工业固体废物排放量和基尼系数是协调发展最重要影响因子.根据预测结果,武汉市在总体规划期间城市发展呈现出良好的协调发展态势,但2010和2020年的协调发展度值均小于总体规划目标值;即按照目前的状态发展下去,武汉市到2010和2020年不能达到规划既定的目标.针对仿真结果,提出了武汉城市生态系统协调发展的对策与建议.

• Abstract：Using both qualitative and quantitative analysis, a set of relatively integrated evaluation indexes was developed to analyze the urban planning process in Wuhan. Key impact factors of coordinated development obtained from partial least squares analysis (PLS) were used as input, and the degree of coordinated development during 1988～2004 calculated by principal component analysis (PCA) and the coordinated development model were used as output. On this basis, a support vector machine (SVM) model was built to simulate the trends of coordinated development during the Wuhan general urban planning period (2005～2020). Results showed that the coupling of the economy, society and resource-environment varied gradually from severe maladjustment to partial coordination. Industrial solid waste emission and Gini coefficients were the dominant impact factors of coordinated development during this period. According to the predicted results, Wuhan urban development should show a good coordination during the general urban planning period, but the degree of coordinated development predicted for 2010 and 2020 is lower than the plan's target. That is, the set targets for 2010 and 2020 cannot be reached under this situation. In the end, a series of countermeasures to improve the development situation are proposed.

• Key words：urban ecosystem  coordinated development degree  support vector machine  partial least squares  principal component analysis

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