基于地理探测器和GWR模型的中国重点镇布局定量归因
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韩静, 芮旸, 杨坤, 刘薇, 马滕
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Quantitative attribution of national key town layout based on geodetector and the geographically weighted regression model
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HAN Jing, RUI Yang, YANG Kun, LIU Wei, MA Teng
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表4 影响因子交互作用探测结果
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Tab.4 Interaction detection results of influencing factors
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| q=A∩B | A+B | 比较结果 | 交互作用产生效应的类型 | 交互作用后的解释力排序 | | S1∩S2=0.536 | S1(0.506)+S2(0.038)=0.544 | A+B>q>A, B | 双因子增强 | 3 | | S1∩S3=0.629 | S1(0.506)+S3(0.082)=0.588 | q>A+B | 非线性增强 | 2 | | S1∩S4=0.646 | S1(0.506)+S4(0.139)=0.645 | q>A+B | 非线性增强 | 1 | | S1∩S5=0.527 | S1(0.506)+S5(0.028)=0.534 | A+B>q>A, B | 双因子增强 | 4 | | S2∩S3=0.096 | S2(0.038)+S3(0.082)=0.120 | A+B>q>A, B | 双因子增强 | 9 | | S2∩S4=0.184 | S2(0.038)+S4(0.139)=0.177 | q>A+B | 非线性增强 | 8 | | S2∩S5=0.060 | S2(0.038)+S5(0.028)=0.066 | A+B>q>A, B | 双因子增强 | 10 | | S3∩S4=0.278 | S3(0.082)+S4(0.139)=0.221 | q>A+B | 非线性增强 | 5 | | S3∩S5=0.197 | S3(0.082)+S5(0.028)=0.110 | q>A+B | 非线性增强 | 7 | | S4∩S5=0.252 | S4(0.139)+S5(0.028)=0.167 | q>A+B | 非线性增强 | 6 |
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