ARGUMENT 7 选新市长解决环保问题

本文分析了一封写给Clearview报纸编辑的信中所提出的观点:即候选人Ann Green比Frank Braun更适合解决该市日益严重的环境问题。文章指出了这一论点中存在的几个逻辑漏洞,并探讨了这些漏洞对结论的影响。

TOPIC: ARGUMENT7 - The following appeared in a letter to the editor of the Clearview newspaper.

"In the next mayoral election, residents of Clearview should vote for Ann Green, who is a member of the Good Earth Coalition, rather than for Frank Braun, a member of the Clearview town council, because the current members are not protecting our environment. For example, during the past year the number of factories in Clearview has doubled, air pollution levels have increased, and the local hospital has treated 25 percent more patients with respiratory illnesses. If we elect Ann Green, the environmental problems in Clearview will certainly be solved."

WORDS: 481 TIME: 00:40:00 DATE: 2011-4-10 0:19:42

In this argument, the author concludes that residents of Clearview should vote for Ann Green who is a member of the Good Earth Coalition to solve the environmental problems in Clearview. At first glance, this argument seems to be convincing, but further reflection reveals that these evidences neither constitute a logical statement in support of its conclusion nor providing compelling support making this argument sound and invulnerable.

The threshold problem with this argument is that the author assumes that the current members of the Clearview town council are not protecting the environment. Although this is entirely possible, the argument lacks evidence to confirm this assumption. For example, the increase number of factories will not definitely lead to the pollution of the environment if some measures have been taken. The air pollution maybe brought by the neighboring city. More patients with respiratory illnesses can not attribute to the air pollution. Until the author provides further evidence to exclude all these concerns, it is unfounded to reach the conclusion involved in the argument.

The second flaw that weakens the logic of this argument is that the author assumes that Frank is not concerned about and should be responsible for the environment problems. Nevertheless , there is no guarantee that it is necessarily case and it is quite possible that Frank is vary concerned about the environment and the real causes of the environment problem are other people such as some businessman who want to make money through opening a lot of factory. In short, without better evidence ruling out these and other alternative explanations, it is reasonable to cast considerable doubt on this assumption.

The last but not the least important, even if the author can substantiate all of the foregoing assumptions, his assumption that all the problems will be solved with the election of Ann Green as mayor of the city is totally unfounded because just concerning about the environment is not enough. If they want to solve the environment problems, a lot of work has to be done. It is much more possible that Ann Green doesn’t have the time and ability to lead the government to solve the environment problems although he concern about the environment because the responsibility of a mayor is not only regarding environmental protecting but also other fairs. Only by the work of all the people in Clearview can they hope to solve the problems. The new Mayor has to come up a blueprint of the benefit of protecting the environment and lead his residents of Clearview to work together. This is a long process and if it failed, the environment problems can’t be solved.

To sum up, the conclusion lacks credibility because the evidence cited in the analysis does not lend strong support to what the arguer maintains. Therefore, if the author had considered the given factors discussed above, the argument would have been more through and logically acceptable.

基于数据驱动的 Koopman 算子的递归神经网络模型线性化,用于纳米定位系统的预测控制研究(Matlab代码实现)内容概要:本文围绕“基于数据驱动的Koopman算子的递归神经网络模型线性化”展开,旨在研究纳米定位系统的预测控制问题,并提供完整的Matlab代码实现。文章结合数据驱动方法与Koopman算子理论,利用递归神经网络(RNN)对非线性系统进行建模与线性化处理,从而提升纳米级定位系统的精度与动态响应性能。该方法通过提取系统隐含动态特征,构建近似线性模型,便于后续模型预测控制(MPC)的设计与优化,适用于高精度自动化控制场景。文中还展示了相关实验验证与仿真结果,证明了该方法的有效性和先进性。; 适合人群:具备一定控制理论基础和Matlab编程能力,从事精密控制、智能制造、自动化或相关领域研究的研究生、科研人员及工程技术人员。; 使用场景及目标:①应用于纳米级精密定位系统(如原子力显微镜、半导体制造设备)中的高性能控制设计;②为非线性系统建模与线性化提供一种结合深度学习与现代控制理论的思路;③帮助读者掌握Koopman算子、RNN建模与模型预测控制的综合应用。; 阅读建议:建议读者结合提供的Matlab代码逐段理解算法实现流程,重点关注数据预处理、RNN结构设计、Koopman观测矩阵构建及MPC控制器集成等关键环节,并可通过更换实际系统数据进行迁移验证,深化对方法泛化能力的理解。
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