Analysis of the Intelligent Tourism Route Planning Scheme Based on the Cluster Analysis Algorithm

Lou, Na

doi:10.1155/2022/3310676

Cited by 7 publications

(5 citation statements)

References 25 publications

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“…The K-means cluster is a more powerful method when dealing with massive data, which is becoming popularly used in big data-driven transportation pattern classification studies. We can see the typical applications in air passenger grouping [47], tourist pattern grouping [48], or travel purpose classification [49] based on traffic big data. Despite the obvious advantages, one of the inherent challenges is the need to specify the number of K clusters in advance.…”

Section: Identifying Mobility Patterns: Indicators and Methodsmentioning

confidence: 99%

Revealing Daily Mobility Pattern Disparities of Monomodal and Multimodal Travelers through a Multi-Layer Cluster Analysis: Insights from a Combined Big Dataset

Zhao,

Zhang,

Gao

et al. 2024

Sustainability

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More detailed and precise mobility patterns are needed for policies to reduce monomodal automotive dependency and promote multimodality in travel behaviors. Yet, empirical evidence from an integrated view of a complete door-to-door trip mode chain with daily mobility for pattern identification is still lacking. As an improvement and a solution on this issue, a multi-layer cluster model was designed and proposed for distinguishing 20 mobility pattern clusters, including six monomodal traveler groups, two non-transit multimodal traveler groups, and 12 transit multimodal based on big data mining. Statistical analysis with seven indicator measurements and a spatial distribution analysis with the Kernel density GIS maps of travelers’ residential location were carried out to reveal significant disparities across pattern clusters concerning spatial, social, and trip characteristics, based on which more precise and target policies for each group were discussed. This research may help provide more detailed information in establishing traveler mobility pattern profiles and solutions in filling the planning–implementation gap from the perspective of planners, policymakers, and travelers.

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Section: Identifying Mobility Patterns: Indicators and Methodsmentioning

confidence: 99%

Revealing Daily Mobility Pattern Disparities of Monomodal and Multimodal Travelers through a Multi-Layer Cluster Analysis: Insights from a Combined Big Dataset

Zhao,

Zhang,

Gao

et al. 2024

Sustainability

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“…For route flight simulation, the 3D route POS data (including latitude, longitude, height, altitude, flight direction, and flight attitude) is used to simulate drone aerial survey operations, perform simulation verification, and further optimize the 3D planning of drone tilt photography acquisition. Route, and output the planned route [9,10]. As shown in Fig.…”

Section: Simulate Drone Aerial Survey Operationsmentioning

confidence: 99%

Route planning based on 3D single model and power grid GISPlatform

Zhang,

Lin,

Jiang

et al. 2023

Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023)

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The route planning of mapping Unmanned Aerial Vehicles (UAVs) such as image-oriented and tilt photography is not adjusted and optimized in combination with the current situation of acquisition objects, which may cause the risk of collision between UAVs and higher objects. At present, the general design is based on cesium tilt photography 3D model monomer, which does not solve the automatic regular 3D model contour. For the spatial information matching of distribution network equipment, due to the nonlinear coordinate offset adopted by the power grid GIS platform, there is an offset between the collected coordinates and the GIS storage coordinates, which cannot be matched. Therefore, it is very urgent to realize the automatic association between the collected information and the PMS account information. This paper analyzes, designs, and implements the route planning method and the three-dimensional model monomer system. In order to solve the problems of unreasonable route planning of UAV in distribution network grid, collision between UAV and higher objects, incomplete collected data and so on, the route planning method is designed. This method optimizes the route by using the existing three-dimensional data, spatial analysis, and collision detection on the GIS platform. The system is analyzed and verified in a real city.

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“…Researchers (Ferreira et al, 2020;Horina, 2017;Korcsmáros et al 2016;Lou, 2022) try to solve this problem by grouping individual territories, industries or other objects into homogeneous groups with similar parameters in order to further evaluate and improve their development within the selected groups. Creation of classification groups based on effective economic criteria is interesting both from the point of view of combining objects into homogeneous groups, and from the point of view of applying specific methods of analysis to identify special characteristics within these groups.…”

Section: Analysis Of the Territorial Unevenness Of The Tourism Market...mentioning

confidence: 99%

“…The problem of quality and stability of division into groups remains relevant in cluster analysis (Khvalynska, 2018;Prokopenko et al, 2020). Another problem of the traditional algorithm of cluster analysis is strong dependence of the distance of objects from an initial center of a cluster (Lou, 2022). To eliminate this problem, scientists Ma, Z., & Liu, X.…”

Section: сLuster Analysis In Tourismmentioning

confidence: 99%

Clusterization in Tourism Development Level's Assessment of Regions: Example of Ukraine

Шпак

Kulyniak

Novakivskyi

et al. 2023

JoTS

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Tourism development is uneven, which is related to the level of socio-economic development of territories, peculiarities of historical and cultural processes, resource provision, etc., which determines the need to study the structure of the tourist market based on spatial polarization based on statistical methods. The study aims to identify disparities in tourism development in Ukraine's regions and to group them according to indicators that characterize tourism's development level. To solve the problem, the authors used a modified cluster analysis method. The article presents the author's approach, which, unlike the existing ones, allows taking into account clarifying weighting factors and corrective penalty functions for each indicator to minimize probabilistic influences when determining the distance between objects. The uneven development of the tourism sector in the regions of Ukraine was revealed. As a result, six clusters were distinguished based on indicators of tourism development in the regions of Ukraine as of 2020, and the peculiarities within each cluster were found. State authorities can use the research results to ensure the comprehensive development of territories by forming effective regional tourism strategies and promoting the development of the most promising tourism destinations and products.

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Analysis of the Intelligent Tourism Route Planning Scheme Based on the Cluster Analysis Algorithm

Cited by 7 publications

References 25 publications

Revealing Daily Mobility Pattern Disparities of Monomodal and Multimodal Travelers through a Multi-Layer Cluster Analysis: Insights from a Combined Big Dataset

Revealing Daily Mobility Pattern Disparities of Monomodal and Multimodal Travelers through a Multi-Layer Cluster Analysis: Insights from a Combined Big Dataset

Route planning based on 3D single model and power grid GISPlatform

Clusterization in Tourism Development Level's Assessment of Regions: Example of Ukraine

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