Simulation analysis of productivity variation by global positioning system (GPS) implementation in earthmoving operations
Bibliographic record
Abstract
The global positioning system (GPS) is being applied in the construction industry as a practical tool for higher productivity. The aim of this study is to estimate the productivity improvement from GPS implementation in earthmoving operations using construction simulation. The results show that the GPS-based system can increase productivity by 21.74% and cost savings by 12.92% over the conventional system in a project with a short haul distance and can increase productivity by 5.67% and cost savings by 4.79% in a project with a long haul distance. It was noted that the bulldozer and truck are critical resources for productivity in each project and that the greater the number of work activities in a project, the lower the improvement in productivity as a result of using a specific technology applied to a limited number of pieces of equipment, due to the existence of many varied factors. This study is intended to help construction planners set up optimized GPS-based earthmoving operations.Key words: earthmoving, global positioning system, simulation, productivity.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".