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BJTerry新蟲 (小有名氣)
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論文返修后被拒，求幫忙看看拒信 已有16人參與
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論文投稿比較波折，時(shí)間至今已有半年了。文章負(fù)責(zé)人是副主編（在美國(guó)的華人），一審意見沖突，副主編要求增加審稿人審稿，增加后一審?fù)ㄟ^，但需要修改 本月3號(hào)提交的修改稿，昨天收到主編（印度人，不清楚為什么他來(lái)負(fù)責(zé)我的文章了）的被拒郵件。被拒所附的審稿內(nèi)容居然和修改給的審稿意見一樣，沒有清楚寫明被拒理由，我不知道是不是其中出現(xiàn)了什么問題，特附拒信，麻煩大家?guī)臀铱纯�，是不是編輯自己做出的決定拒搞了，謝謝。 ------------------------------------------------------------------------------------------------------ Dear author(s) Ref: Submission "*****" Your above mentioned submitted article has been read through several rounds of peer review. Unfortunately, the recommendation is that the article be rejected. We have come to the conclusion after a careful evaluation of your work. Articles submitted to the International Journal of *** are judged on their timeliness and novelty; significance to the field and potential impact on the course of future work in the area. I would not advise you to revise the article in anything like its present form. I am enclosing part of the referee's reports. However, I do thank you for your interest in the International Journal of ***. Best Wishes, ------------------------------------- COMMENTS MADE BY REFEREES: ------------------------- First Review: ------------- The experiments conducted are based on only synthetic datasets - this might not be convincing enough to claim the superiority of the algorithm. Data from the real world (possibly multidimensional data) are recommended. Second Review: ------------- No One major concern is the experimental settings, which should be depicted more detailed. Since the fault matrix A is generated randomly, the results are untrusted unless they are averaged by many runs. Similarly, since evolutionary algorithms are randomized algorithms in nature, i.e., their results may be unaccepted sometimes, the author(s) should state clearly whether the results is attained by one run or best of many runs, i.e., how much the variance of results is. Another concern is that the paper fails to describe the IGA in detail. In line 5 of Algorithm 1, how the V is computed by matrix A? Since there are some techniques for crossover and mutation, what technique does the IGA use for crossover and mutation and why? In the abstract, the authors said appropriate termination criterion can improve the accuracy and efficiency of the algorithm, but they did not point out it clearly in this paper. The third concern is the feasibility of two vaccines V_1 and V_2. Since LB is the lower bound of the solution and the author(s) did not prove LB is the tight lower bound, it may be not helpful or good to make the individual consisting of LB '1' in some cases. So the authors need to deal with this problem in order to make the paper more rigorous logically. The grammar is generally acceptable, but more attention needs to be paid to raise the quality of polish. And there are some statements that need citations. For example, 'It has been proven that the minimal hitting set problem is NP-hard', 'Numerous studies show that it is far from enough for relying solely on evolutionary algorithm (such as genetic algorithm) to simulate human intelligence to deal with things' and so on. I think the sentence below the equation (2) maybe wrong. If not, why the author(s) give a different definition of 2-norm of vectors? |
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