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Record W2999369501 · doi:10.1155/2020/5379218

Analysis of a Flexible Transit Network in a Radial Street Pattern

2020· article· en· W2999369501 on OpenAlexvenueno aff
Hongguo Shi, Mingyao Gao

Bibliographic record

VenueJournal of Advanced Transportation · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicTransportation Planning and Optimization
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsTransit (satellite)TraverseTransit systemComputer scienceGridGrid networkService (business)HingePublic transportSimulationMathematical optimizationTopology (electrical circuits)Transport engineeringEngineeringMathematicsStructural engineeringGeography

Abstract

fetched live from OpenAlex

Traditional transit systems are usually composed of fixed routes and stops, which are suitable in densely populated areas. This paper presents a reformulation of the flexible transit model developed by Nourbakhsh and Ouyang (2012) to adapt it to many low demand cities in the world, especially those characterized by radial street patterns. Unlike traditional ones, buses of the proposed transit network are allowed to traverse in a predetermined service area and their precise trajectories hinge on the exact locations of passengers. To identify the optimal topology structure of the flexible transit system, continuous approximation approaches are developed to explore the optimal value of design parameters of the whole system, defining the optimal network layout through minimizing its objective function. To exhibit its advantages, numerical experiments are conducted to compare the flexible transit system with its two variants. The results show that the flexible transit system proposed in this paper outperforms the other two variants. The higher the access cost is, the more it would tilt towards the flexible transit system with a significant margin. Besides, the flexible transit system in a radial pattern competes more effectively than that in a grid structure. This is encouraging because the proposed transit system can be applied in a number of real-world cases.

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.

How this classification was reachedexpand

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.784
Threshold uncertainty score0.417

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
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 head0.017
GPT teacher head0.283
Teacher spread0.266 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2020
Admission routes1
Has abstractyes

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