## 8 Conclusions and Recommendations  
### Conclusions  
With the evolution analysis of the four-year passenger transport network spatial pattern, we can see that the central area of passenger transport network diffuses from Chengdu and Chongqing to Chengdu Chongqing urban agglomeration. With the enhancement of the Central Guizho and Guanzhong urban agglomeration, it has finally realized the evolution of the spatial pattern of the passenger transport network from \"two main cities and multiple auxiliary cities\" (Chengdu and Chongqing as the main cities, Xi 'an, Guiyang, Zunyi, Meishan, and Deyang as the sub-centers) to \"three main cities and three auxiliary cities\" (Chengdu, Chongqing, and Guiyang as the centers, Chengdu-Chongqing urban agglomeration, Central Guizhou urban agglomeration, and Guanzhong urban agglomeration as the sub-centers). Through the study on the spatial pattern evolution of the freight transport network during the four-year period, we find that the central area of the freight transport network gradually shifts from Chengdu and Chongqing to Chengdu-Chongqing urban agglomeration, and the sub-central area gradually expands from Xi'an to Kunming, Hezhou, and Ordos. As the intensity of the urban node association between Nanning and Guiyang becomes more prominent, it has realized the evolution of the spatial pattern of the freight network from \"two principal and one deputy\" (with Chengdu and Chongqing as the center and Xi'an as the sub-center) to \"one principal and multiple deputy\" (with Chengdu-Chongqing urban agglomeration as the center and Guiyang, Xi 'an, Kunming, Nanning, and Ordos as the sub-centers). The resilience of the whole network varies in different periods. The node degree value-based strategy has the most obvious influence on the whole network, and as for the influence, the whole passenger transport network is relatively larger. The influence of the two random strategies on the whole network of passenger transport and freight transport is relatively stable, and their influence is similar. The static betweenness disturbance strategy has the most unstable impact on the network and has the largest impact on the passenger and freight transport networks in 2018. When the number of nodes removed is larger, the impact on the passenger transport network is smaller than that of the two random strategies, but the impact on the freight transport network is basically the same as that of the two random strategies. The influence of the dynamic betweenness disturbance strategy on the four-year network is also relatively stable, and the influence degree is the least among the five strategies, but its influence on the freight transport network is greater than that of the passenger transport network. The resilience of the key passenger and freight network is also different in different periods, and the resilience of the key network is less than that of the whole network. The strategy based on node degree value has the largest shock to the key network. The two random strategies are relatively stable and have the least influence in the key network, but have a greater impact in the passenger key network. In 2000 and 2006, the influence of the two betweenness disturbance strategies on the key networks is not stable. Except for the freight transport network in 2006, the influence of the static betweenness disturbance strategy on the other key networks is greater. In the key networks in 2016, the influence degree of the two betweenness disturbance strategies is basically the same. When the number of nodes removed is small, the static betweenness disturbance strategy has a greater impact on the 2018 passenger transport key network, and the two betweenness disturbance strategies have basically the same impact on the 2018 freight key network. The nodes of urban passenger and freight network with different periods have strong network expansion ability.