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zhongnanliuhui木蟲 (著名寫手)
小木蟲
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投了Journal of Wind Engineering & Industrial Aerodynamics,兩年被拒 已有4人參與
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郁悶啊 等了2年 中間主編發(fā)過一次信 讓我不要著急 現(xiàn)在被拒 不過好像還可以修改再投 因為提出的問題雖然多 但是好像好回答 有投過該刊的牛人說說 評語： Reviewers' comments: Reviewer #1: The author's are to be commended for tackling a difficult and timely subject. However, I am afraid that I have a number of issues with the work and the way it has been presented. For example, the introduction section is too brief and although it mentions a number of other similar studies it does not discuss the relative benefits/disadvantages of these. More importantly it does not address the fundamental question of how the current approach is better than that which already exists. In addition, the first seven references are written in Chinese and as such will not be acceptable to the majority of readers. While I have no problem with the authors quoting their previous work I feel that seven examples are somewhat excessive. In addition and perhaps more importantly a number of key references have also been missed, e.g. Delaunay et al. (2006) and Ding et al. (2008). 翻譯：對作者所研究的這個困難而及時的課題表示肯定。但是我提出如下問題：摘要過于簡單，沒有比較提到文獻的優(yōu)缺點，提出方法的優(yōu)勢在哪里？此外，前面7篇參考文獻均是中文，許多讀者對這會介意的。我雖然不介意作者引用之前的工作基礎(chǔ)，但是我覺得還是有點多，這樣很容易遺失其他更加重要的參考文獻：如e.g. Delaunay et al. (2006) and Ding et al. (2008). Section 2 outlines the warning system. In my view this section is also too brief and would benefit from a more in depth discussion of local features which may or may not influence the wind speed. For example, what is the surrounding terrain near the anemometers? What height are the anemometers positioned at and what is their sampling resolution? Section 2.2 outlines the requirements of the system but no background information has been provided. For example, why is a 1 minute forecast acceptable and how does this relate to train speed/anemometer separation etc? 翻譯：關(guān)于預(yù)警系統(tǒng)，我個人認為仍然描述的過于簡單，最好能夠進一步深入討論可能影響風(fēng)速的當(dāng)?shù)氐孛睬闆r。例如，風(fēng)速計周圍的地形？風(fēng)速計安裝的位置？以及對應(yīng)的采用方案？第2.2節(jié)雖然提出了預(yù)測要求指標(biāo)，但是沒有進一步說明其提出的背景信息。例如，為什么有超前1分鐘預(yù)測？他們跟車速及行車安全有什么關(guān)系？ Section 3 considers the actual wind speed forecast. Why are the authors only concerned with wind speed and not the stream wise and lateral velocity components? Why is the data from the 51st - 220th wind speeds used to build the forecast? The discussion relating to AR vs. ARMA vs. ARIMA does satisfactory address the issue of why a ARIMA (7,1,0) model was chosen. Importantly no consideration appears to have been given as to whether the predicted wind speeds have the appropriate spectral form or whether the predicted wind speeds at different locations are appropriately correlated. The conclusions could be expanded significantly if more work has been undertaken. I would advise the authors to resubmit the paper only after the proposed future work has been taken into account. 翻譯：關(guān)于實際風(fēng)速預(yù)測。為什么作者僅僅是關(guān)心風(fēng)速，而不關(guān)心風(fēng)速的流向和側(cè)向分量呢？ 為什么建模數(shù)據(jù)取51st-220th這段樣本？文章涉及AR/MA/ARMA/ARIMA模型，但是沒有令人滿意的解釋為什么選擇ARIMA(7,1,0)? 最重要的是，作者沒有考慮預(yù)測風(fēng)速的適用區(qū)間或是說預(yù)測風(fēng)速與不同測風(fēng)點或是監(jiān)控點之間的關(guān)系。此外，作者的結(jié)論可以根據(jù)歷史研究結(jié)果進一步擴展。我個人建議作者完成上述提出的問題后重新投稿。 References quoted: Ding, Y, Sterling, M and Baker, C. J. (2008).An alternative approach to modelling train stability in high cross winds. Proceedings of the Institute of mechanical Engineers Part F: Journal of Rail and Rapid Transport. Volume 222, Number 1, 85-97. Delaunay, D., Baker, C. J. Cheli, F, Morvan, H, Beger, L., Casazza, M, Gomez, C, Cleac'j C.Le., Saffel, R, Gregoire, R and Vinuales, A (2006) Development of wind alarm systems for road and rail vehicles: Presentation of the WEATHER project. SIRWEC 13th International Road Weather Conference, Toriono (Italy). 翻譯：專家提出的相關(guān)參考文獻。 Reviewer #2: Comments to Authors: 1. The paper deals with anemological data collected along the Qinghai-Tibet railway line. Anemological data are used to derive a forecast model, but in the paper there is no explanation concerning the instrumentation nor the sampling rate of data. Which is the sampling rate of raw data? Raw data has been averaged? Collected wind speed have to be intended as mean value? In this case, on which time span? A clear explanation is necessary. 翻譯：文章是研究如何對青藏鐵路沿線實測氣象數(shù)據(jù)建立預(yù)測模型以保障行車的問題。但是文章沒有介紹所選用的測試系統(tǒng)（儀器）以及對于的采樣頻率等設(shè)置。原如始數(shù)據(jù)的采樣頻率是多少？原始數(shù)據(jù)是否經(jīng)過平均化處理？實測數(shù)據(jù)是否不得不經(jīng)過平均化處理？處理的時間長度？這些問題都必須清楚地交代。 2. The data is analysed by means of a time-series approach based on Box-Jenkins model, but the explanations about the derivation of the method are not detailed. The forecast of wind speed is carried out 1, 3 and 5 minutes ahead, but there's no indication concerning the number of steps corresponding to such time intervals. 翻譯：數(shù)據(jù)建模方法是使用時間序列分析理論中的詹金斯建模方案，但是缺少對這種建模方法的詳細描述。預(yù)測是針對超前1、3、5分鐘進行的，但是沒有進一步指出采用數(shù)據(jù)的處理間隔以及超前預(yù)測的步數(shù)。 3. ARIMA(7,1,0) model is initially chosen to forecast wind speeds 1, 3 and 5 minutes ahead, and for all the meteorological station. It is stated that the model is calibrated on the data of the "27th meteorological station" (page 2-3), and that the model is requested to have an accuracy such that the mean absolute percentage error is less than given thresholds. The estimation of the error with the ARIMA(7,1,0) model (Table 1) is based to a whole time series of a single anemometer? It refers to a single anemological station (station 27?) or is the averaged value from different stations? This is not clear. The same considerations can be applied to Table 2. Moreover, the mean percentage error is not a clear estimator of the goodness of the forecast, since underestimations and overestimations of the actual values tend to cancel each other. The RMSE is a better estimator, but since it is dimensional it should be referred to velocity ranges. Percentage error (mean value and confidence bounds, as standard deviation) is preferable. 翻譯：作者提到所見的模型ARIMA(7,1,0)將運用到全部測風(fēng)站預(yù)測，并且預(yù)測精度必須滿足門檻要求。那么有如下疑問：模型的精度評價是僅僅使用27號冊封站的全部樣本數(shù)據(jù)，還是全部測風(fēng)站樣本數(shù)據(jù)的平均處理后的樣本？這個問題沒有交代清楚。此外，百分比誤差指標(biāo)不是一個清楚的考核精度指標(biāo)，因為欠預(yù)測和過預(yù)測精度容易相互抵消。而RMSE指標(biāo)更加理想，但是其涉及速度范圍，不好計算。因此，平均值加上置信區(qū)間的誤差指標(biāo)更加受歡迎。 4. Since strong winds are responsible of safety issues, a clear indication of the error in the estimation of strong events could be a clear indicator of the performance of the model. Moreover, a comparison of the performance of adopted models with a persistent model could be helpful to understand the effective performance: the errors of the proposed model are smaller or larger than those of a persistent one? 翻譯：強風(fēng)將影響列車行車安全，因此模型的預(yù)測性能是強風(fēng)評價考核的重要因素。建議將采用模型和現(xiàn)有模型的預(yù)測性能進行進一步比較分析，看到底采用模型的誤差比現(xiàn)有模型大還是小? 5. Equation 4 does not correspond to a percentage value. 6. The so called "modified method" seems to be based on the ARIMA(7,1,0) that updates the estimation of the model parameter based on forecasted value. In this case, it should not be intended as an effective "improvement" of the method, but a recursive estimation algorithm. 翻譯：作者將提出的方法命名為改進算法，實際上是基于模型參數(shù)估計的實時刷新。我個人認為這應(yīng)該稱為迭代優(yōu)化算法更加合適。 7. Figures 6-10 show real time wind speeds and forecasted values. The predicted time series' seem to be similar to the actual values, but shifted in time. The time shifting increases as the forecast horizon increases, and in this case the similarity of actual and forecasted time series decreases. Do the authors have any explanation for this phenomenon? 翻譯：文章圖6-10指出，預(yù)測風(fēng)速與實測風(fēng)速較為接近，但是存在明顯的預(yù)測延時現(xiàn)象。延時主要出現(xiàn)在風(fēng)速階躍點，這種現(xiàn)象將降低風(fēng)速預(yù)測精度，作者能對這個現(xiàn)象進行解釋嗎？ 8. References 11 and 12 are not cited within the text. The style used for references is not uniform and need to be revised. The inclusion of references to articles and book related to Box-Jenkins model and its applications to wind forecast is strongly suggested. 9. There are many grammar and spelling errors: the text need to be revised carefully. 10. The text style (e.g. indentation) is not uniform. 翻譯：參考文獻11和12沒有在文中標(biāo)注。參考文祥的格式不統(tǒng)一，需要修改。此外，建議參考文獻補充關(guān)于詹金斯預(yù)測的書和文章。文章許多拼寫和語法錯誤，請作者認真修改。 不知道還有沒有勝算？還是換一個刊物？ |
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