Bibliographic record
Abstract
The present study is to report its authors' study on the risk assessment related to dam failure all over the world,especially,in the USA,Canada,Australia,Western Europe and South Africa.As is known,dam failure tends to cause severe disastrous consequences, including human casualty and material damage in economy and pro- duction.Statistically speaking,more than 3 000 dams in China that are likely to lead to severe deficiency and dangerous break-down. Therefore,it is of great necessity to analyze and evaluate the safety status and state of dams in our country.In the paper,we have pro- posed an evaluation model and made discussions on the corresponding evaluation specifications in the field.The suggested model may intro- duce F-N method (a curve with the annual probability of an event causing fatalities F versus the number of fatalities N)proposed by the Australian Commission on Dams (ANCOLD)generally used for as- sessing dam safety.However,F-N curve takes into no account the fuzzy characteristics of various factors.To make up for the inadequa- cy,the present paper has put forward an improved evaluation model of dam failure on the basis of fuzzy analytic hierarchy process (AHP).First of all,we have classified the main influencing factors into three categories,such as human casualty,financial loss,as well as social and enviromnental impacts in addition to the rest factors a- long with the above main ones.At the same time,an index system has also been established to quantitatively ensure the influential de- gree between the main factors and the sub-ones.Secondly,we have also determined the weights of factors related to the dam failure on the basis of AHP.Here we have also introduced the membership function to define the fuzzy evaluation matrix as well as the procedures of the fuzzy AHP evaluation model.And,finally,the fussy AHP model can also be used to analyze a practical engineering example in order to validate it.The evaluation results we have gained demonstrate that the hazards caused by the dam failure tend to be extremely severe and in turn should be on close guard against.The given conclusion proves in agreement with the results based on the other currently used meth- ods.Thereby,considering fuzzy relationship of the factors,the model is feasible for assessing the hazards of dam failure.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".