Station Layout Optimization and Route Selection of Urban Rail Transit Planning: A Case Study of Shanghai Pudong International Airport

Yin, Pei; Peng, Miaojuan

doi:10.3390/math11061539

Cited by 2 publications

(2 citation statements)

References 52 publications

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“…Feature attributes are used to construct the attraction clustering algorithm, while the spatial attributes are used to calculate the hotel's spatial accessibility. By constructing the urban cells and the cellular space, the spatial clustering relationship between the tourist attractions and the hotel is confirmed [16][17][18]. Definition 1.…”

Section: Methodsmentioning

confidence: 99%

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Tourism Hotel Accommodation Recommendation Algorithm Based on the Cellular Space-Improved Divisive Analysis (CS-IDIANA) Clustering Model

Zhou,

Peng,

Wen

et al. 2023

Electronics

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On the basis of analyzing the problems concerning hotel accommodation recommendation (HAR), this paper constructs a tourism HAR algorithm based on the CS-IDIANA clustering model (cellular space-improved divisive analysis). The algorithm integrates the cellular space model with DIANA, and takes the tourist attractions and the travel route costs as the research background and constraint conditions. Considering the feature attributes and spatial attributes of the tourist attractions, the tourist attraction recommendation algorithm based on the CS-IDIANA clustering model is established, then the HAR algorithm based on the spatial accessibility and route cost is constructed, with the constraints of the spatial accessibility field strength (SAFS) between the hotels and attractions and the travel route costs between the hotels and attractions. The experiment selects the tourism city Zhengzhou as the research object, and the experimental results are analyzed in four dimensions: the clustering results, the recommendation field strength of the tourist attractions, the hotel SAFS and the HAR results. The experiment proves that the proposed algorithm can find the best matched tourist attractions for tourists and the hotels with the lowest tour route cost based on the constraint conditions. Compared to the suboptimal hotels, the route costs are reduced by 5.67% and 9.63%, respectively. Compared to the hotel with the highest route cost, it reduces the travel costs by 29.23%. Compared with the two commonly used recommendation methods, the UCFR (user-based collaborative filtering recommendation) and ICFR (item-based collaborative filtering recommendation), the proposed CSIDR (CS-IDIANA recommendation) has a higher accuracy and recall rate.

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Section: Methodsmentioning

confidence: 99%

“…Formula ( 17) is the calculation method for evaluating the precision of recommendation algorithms, which is a critical factor to calculate the F 1 value. Formula (18) is the model of the F 1 metric for the recommendation algorithm.…”

Section: Comparison On Recommendation Algorithmsmentioning

confidence: 99%

Tourism Hotel Accommodation Recommendation Algorithm Based on the Cellular Space-Improved Divisive Analysis (CS-IDIANA) Clustering Model

Zhou,

Peng,

Wen

et al. 2023

Electronics

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Optimization Algorithms and Their Applications and Prospects in Manufacturing Engineering

Song,

Wang,

Hao

2024

Materials

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In modern manufacturing, optimization algorithms have become a key tool for improving the efficiency and quality of machining technology. As computing technology advances and artificial intelligence evolves, these algorithms are assuming an increasingly vital role in the parameter optimization of machining processes. Currently, the development of the response surface method, genetic algorithm, Taguchi method, and particle swarm optimization algorithm is relatively mature, and their applications in process parameter optimization are quite extensive. They are increasingly used as optimization objectives for surface roughness, subsurface damage, cutting forces, and mechanical properties, both for machining and special machining. This article provides a systematic review of the application and developmental trends of optimization algorithms within the realm of practical engineering production. It delves into the classification, definition, and current state of research concerning process parameter optimization algorithms in engineering manufacturing processes, both domestically and internationally. Furthermore, it offers a detailed exploration of the specific applications of these optimization algorithms in real-world scenarios. The evolution of optimization algorithms is geared towards bolstering the competitiveness of the future manufacturing industry and fostering the advancement of manufacturing technology towards greater efficiency, sustainability, and customization.

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Station Layout Optimization and Route Selection of Urban Rail Transit Planning: A Case Study of Shanghai Pudong International Airport

Cited by 2 publications

References 52 publications

Tourism Hotel Accommodation Recommendation Algorithm Based on the Cellular Space-Improved Divisive Analysis (CS-IDIANA) Clustering Model

Tourism Hotel Accommodation Recommendation Algorithm Based on the Cellular Space-Improved Divisive Analysis (CS-IDIANA) Clustering Model

Optimization Algorithms and Their Applications and Prospects in Manufacturing Engineering

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