From Serindia to Japan: A Sketch of the Buddhist Library of Ximing Monastery in the Eighth-Century Chang’an

Xiang, Wang

doi:10.1007/978-981-13-2998-2_7

Cited by 1 publication

(1 citation statement)

References 4 publications

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“…Based on the determined plane route, the elevation map of the ground line that the route passes through can be obtained, and then the initial gradient change point can be calculated using the ground line roughness algorithm proposed by Wang Haijun [8] . Roughness is the absolute value of the slope difference between the linear regression lines of a point on the ground line within a certain range of left and right sides.…”

Section: Figure 2 Mathematical Model Of Profilementioning

confidence: 99%

Corridor selection method of new highway based on NNIA genetic algorithm

Wu,

Zhu,

Wang

et al. 2024

Seventh International Conference on Traffic Engineering and Transportation System (ICTETS 2023)

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The selection of the highway corridor is very significant in the early stage of highway construction, and its rationality determines the economy, environmental protection, and safety of the whole life cycle of the construction project. Existing corridor selection methods are mainly based on the subjective experience of designers and lack intelligent corridor selection technology with strong operability. Therefore, a corridor selection method for new highways based on Nondominated Neighbor Immune Algorithm (NNIA) and Affinity Propagation (AP) clustering algorithm was proposed. Firstly, the mathematical model of the corridor was built. Secondly, considering the environmental and economic factors during the corridor selection stage, the optimization objective function was established. Lastly, the corridor was generated by using the NNIA and AP clustering algorithms. This method was applied to the project from Dezhou to Shangrao Highway from Qimen to the boundary of Anhui and Jiangxi provinces. The corridor generated was consistent with the trend of the actual route of the project, which had certain engineering feasibility.

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Section: Figure 2 Mathematical Model Of Profilementioning

confidence: 99%