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Record W1966520186 · doi:10.1061/9780784413159.168

Planning of Dynamic Routing of Logistics in Urban Public Sports Facilities Based on MAS

2013· article· en· W1966520186 on OpenAlex
Jixue Yuan, Jun Song, Yuwen Zhang, Chaozhe Jiang, Fang Xu

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicE-commerce and Technology Innovations
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsBusinessUrbanizationTransport engineeringUrban planningGovernment (linguistics)Public transportGeographic information systemEnvironmental planningEnvironmental economicsEconomic growthCivil engineeringGeographyEngineeringEconomics

Abstract

fetched live from OpenAlex

Urban public sports facilities are an important carrier of comprehensive function in a city. So the government should develop urban public sports facilities to satisfy the civic requirements to improve public health by sports activities. However, China has the largest population in the world. Especially, China has entered an accelerating period of urbanization at present, and the city has become increasingly crowded. So, it will be a crucial problem how to use the urban public sports facilities efficiently to develop public health, and there are many factors to affect the efficiency to use urban public sports facilities such as spare time, space location, the number of urban public sports facilities, and so on. This paper will only discuss planning on dynamic routing of logistics in urban public sports facilities based on MAS and Dijkstra algorithm theory. Actually, intellectual traffic system (ITS) has been noticed and researched gradually with the development and demand of high technology and traffic transportation. Currently, intellectual traffic system has also become one of the most important studying hotspot, which is tested extensively including for logistics transportation. Meanwhile, geography information system (GIS) has to apply to the traffic transportation if the cost of logistics transportation is to be lowest. With the development of GIS, it is further applied to prediction, planning, and decision making in logistics. In fact, urban community sports depend on development of urban public sports facilities in a way, and it is necessary to use urban public sports facilities thoroughly. So, this paper studies dynamic routing planning in logistics of urban public sports facilities and analyzes the algorithm of the shortest path through the calculation on the basis of GIS and MAS in the region of logistics to the urban public sports facilities. It also draws a conclusion that GIS and MAS can improve efficiency and quality promptly of transportation in the logistics of urban public sports facilities. Furthermore, it also amends algorithm of logistics transportation routing net in urban public sports facilities and provides some valuable suggestions for development of urban public sports facilities based on MAS and Dijkstra algorithm theory.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.268
Threshold uncertainty score0.458

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.029
GPT teacher head0.233
Teacher spread0.204 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Quick stats

Citations2
Published2013
Admission routes1
Has abstractyes

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