Hybrid wind-municipal solid waste biomass power plant location selection considering waste collection problem: a case study
Bibliographic record
Abstract
Significant increments of energy demand and the need to decarbonize the existing energy systems motivate policymakers to utilize renewable energy resources. Accordingly, this paper suggests a hybrid electricity generation system that operates with wind and municipal solid waste biomass to generate monotonous currents and protect the environment by using a portion of the urban wastes. To select a hybrid power plant location, Z-number data envelopment analysis is employed considering economic, social, environmental, and strategic factors, in addition to reliability of fuzzy data. Furthermore, a routing problem is solved by the particle swarm optimization algorithm to calculate the optimal cost of urban waste gathering. As a case study, the model is applied to thirty-one cities in Iran; Shahrbabak, Meymeh, and Birjand are three cities selected as optimal hybrid power plant locations. Finally, the sensitivity analysis results indicate the importance of globally adopting land cost and distance from power distribution network factors.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".