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Record W2887380491 · doi:10.23977/isspj.2017.21003

Multi-objective Planning Model of Electric Vehicle Charging Station

2017· article· en· W2887380491 on OpenAlex

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInformation Systems and Signal Processing Journal · 2017
Typearticle
Languageen
FieldEngineering
TopicOptimal Power Flow Distribution
Canadian institutionsnot available
Fundersnot available
KeywordsCharging stationElectric vehicleGenetic algorithmOperator (biology)Point (geometry)Location modelService (business)Tabu searchComputer scienceScale (ratio)SimulationOperations researchMathematical optimizationEngineeringAlgorithmMathematicsGeography

Abstract

fetched live from OpenAlex

Reasonable planning of electric vehicle charging station is of great significance for large-scale use of electric vehicles. Based on the analysis of charging station construction requirements, a multi-objective planning model for charging station location problem considering users' satisfaction and operator benefits is constructed. From the point of view of users' satisfaction, consider the electric vehicle charging station's location problem with two parts, one is minimum of driving distance, the other is shortest time of waiting for charging. From the point of view of operator benefits, is the lowest cost of construction of charging station. Then, the improved tabu-genetic algorithm is proposed to solve this model. The test results show that the model proposed in this paper can effectively determine the locations and the service regions of the recharging stations, and the algorithm is quick and effective.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.638
Threshold uncertainty score0.605

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.003
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 head0.021
GPT teacher head0.255
Teacher spread0.234 · 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