A method for extracting spatial agglomeration features of inbound logistics clusters
A feature extraction and logistics technology, applied in the field of logistics analysis, can solve the problems of logistics flow, flow direction, and time-space characteristic data acquisition difficulties, lack of spatial agglomeration characteristics of logistics enterprises, etc., and achieve the effect of improving the level of punctual and lean management
Active Publication Date: 2022-04-15
JILIN UNIV +1
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[0002] The feature extraction of traditional logistics clusters, because it is very difficult to obtain data on logistics flow, flow direction, and time-space characteristics, focuses on extracting industrial scale and intensification characteristics from the perspective of macro-industrial layout, but lacks scientific and effective methods to extract logistics enterprises from the perspective of logistics clusters. spatial agglomeration features
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[0031] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only It is a part of embodiments of the present invention, but not all embodiments. The components of the embodiments of the invention generally described and illustrated in the figures herein may be arranged and designed in a variety of different configurations. Accordingly, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making...
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The invention discloses a method for extracting spatial agglomeration features of inbound logistics clusters, comprising the following steps: S1: collecting and standardizing spatio-temporal data, S2: extracting spatial distribution features of logistics enterprises, S3: extracting spatial agglomeration features of logistics enterprises, S4: Feature extraction of logistics enterprise road network dependency, S5: Discrimination of spatial agglomeration characteristics of logistics clusters, S6: Discrimination of agglomeration road sections and agglomeration areas according to the core mode and axis distribution characteristics, and finally determine the axis core pattern. The application of spatial analysis method in the field of logistics cluster characteristic analysis, aiming at the particularity that it is difficult to extract, judge and deduce the characteristics of logistics cluster groups in practice, extracts from the three dimensions of spatial distribution characteristics, spatial concentration characteristics and road network dependence characteristics. Spatial agglomeration characteristics of logistics clusters.
Description
technical field [0001] The invention relates to a logistics analysis method, in particular to a method for extracting spatial agglomeration features of inbound logistics clusters. Background technique [0002] The feature extraction of traditional logistics clusters, because it is very difficult to obtain data on logistics flow, flow direction, and time-space characteristics, focuses on extracting industrial scale and intensification characteristics from the perspective of macro-industrial layout, but lacks scientific and effective methods to extract logistics enterprises from the perspective of logistics clusters. Spatial agglomeration features. With the recognition of the important position of the logistics industry in the national economy, a nationwide logistics infrastructure network has basically formed, and the research on logistics clusters is in a period of rapid growth, focusing on the research on the characteristics of logistics cluster operations and management, s...
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IPC IPC(8): G06Q10/08G06K9/62
CPCG06Q10/083G06F18/2132G06F18/24323
Inventor 孙宝凤吕傲李春峰陈雨琦谢成杨成延孙禹丁同强孟凡运
Owner JILIN UNIV