使用人工智能来预测地震.docx

本文格式为Word版，下载可任意编辑使用人工智能来预测地震 毛新红 在科技迅猛發展的今天，人工智能技术被广泛应用在各个领域越来越多的科学家表示，在人工智能技术的扶助下，他们分析地震数据的方式发生了变化，这可以扶助他们更好地了解地震并供给更快速、更切实的预警 An earthquake early warning system that uses artificial intelligence（AI） to predict how the ground will move during an earthquake can give several seconds advance notice that the shaking is coming. A similar system that uses more traditional computing power is called ShakeAlert， and it works by detecting the first waves of earthquake motion and then calculating when the set of waves that cause most of the shaking will arrive. The new system in development is called DeepShake， which is intended to provide a few seconds advance warning once an earthquake has started. However， DeepShake uses a deep neural network， a type of AI learning， to identify patterns from past earthquakes in order to predict how the shaking from a new quake will travel. This could lead to faster processing across different regions. “When we set out on this project， our main goal was to beat the ground motion prediction equations that are currently used to program ShakeAlert system，” said Avoy Datta， who developed DeepShake. “They tend to be very slow because they need numerical solvers， running on supercomputers， and they can take minutes and even hours to process.” Despite the fact that DeepShake is given no information about the earthquakes location or type， it is able to give warnings between 3 and 13 seconds before the earthquake happens. This is similar to the amount of advance notice with ShakeAlert. Researchers view this system as a competitor to make progress because DeepShake technology can be used to make up for ShakeAlert. The researchers hope to expand the testing to other faults. Ground shaking at any given spot can be tricky to predict. For example， ShakeAlert once failed to send out warnings during the largest quakes in the Ridgecrest earthquake sequence in 2022 because the shaking was expected to not reach the programs threshold of “light shaking” in some areas that did indeed experience light shaking. The advantage of deeplearning networks， is that they can automatically collect information， because they are based on past experiences of shaking in that location. Unlike ShakeAlert， which uses more universal equations with assumptions built in， DeepShake will have to be retrained in each individual region where it is used. This training， however， will catch patterns that traditional equations may not. 1. How does ShakeAlert predict earthquakes according to the text？ A. By figuring out where most waves are. B. By finding out most of the large waves. C. By discovering when the waves will arrive. D. By detecting the first waves of earthquakes. 2. Whats the aim of DeepShake？ A. To improve ShakeAlert. B. To improve the predicting speed. C. To prevent the terrible earthquakes. D. To change the traditional methods. 3. What does the underlined word “tricky” in the last paragraph mean？ A. Interesting. B. Difficult. C. Impossible. D. Important. 4. Which section of the newspaper is the text probably taken from？ A. Science. B. Society. C. Environment. D. Geography. Ⅰ. Difficult sentence in the text Despite the fact that DeepShake is given no information about the earthquakes location or type， it is able to give warnings between 3 and 13 seconds before the earthquake happens.尽管DeepShake没有得到地震位置或类型的信息，但它能够在地震发生前3到13秒发出警告。

【点石成金】在本句中，DeepShake is given no information about the earthquakes location or type為that引导的同位语从句，解释说明fact的内容 Ⅱ. Textcentered chunks be intended to 计划…… identify patterns 识别模式 lead to 导致 set out 开头工作;开展任务 tend to 往往;趋向 be similar to 和……类似 view...as 把……视为 send out warnings 发出警告 猜你热爱同位语趋向点石成金创意条形码少年文艺·开心阅读作文(2021年8期)2021-09-05实用趋向小资CHIC！ELEGANCE(2021年28期)2021-08-18Exploring the link between education and climate change 教导和气候变化之间有何联系疯狂英语·新阅版(2021年1期)2021-03-03全球治理趋向扁平China International Studies(2021年5期)2021-01-03A secret plan 机要筹划疯狂英语·读写版(2022年10期)2022-11-06同位语用法小结中学课程·高考版(2022年10期)2022-12-06雾霾治理立法：趋向与反思人民论坛(2022年14期)2022-06-21点石成金故事作文·低年级(2022年3期)2022-04-08现在举行时海外英语(2022年5期)2022-08-27— 5 —。