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P1: Originated from EL's findings, Chaos Theory actually has little to do with randomness.Key Words: same input but different output, rounding, despite, randomness
same inputs, but different outputs resulted. Despite its name, little to do with randomness. (出题:关于chaos theory怎么发现的?第一自然段最后一句话作用?...)
P2: Use an example of poppy seeds to better understand unpredicatability from deterministic equations.
Poppy seeds in round bowl...; Then if flipped over...(出题:举例的目的?提出initial difference in position。)
P3: Explain fundamental equations with another example-a machine mixing bread dough.
Key Words: illusory, in fact
Characteristics of chaotic systems: attraction and repulsion. Dough..., seed.... In fact, seeds captured by...., but are in fact determined by...fundamental equations. (出题:实验细节比如 illusory; technically chaotic...)
P4: Doughs, seeds and weather forecast together to explain such error is not true randomness.
Key Words: eventually, amplified, until unpredictable, not true randomness, popular, better understanding
两颗种子最终各自生长自己的。任何早期的分歧和误差都会在混合的过程中被重复放大直至最终不可预测。导致不可预测性的其实不是真正的随机,而是早期阶段的sensitive dependence。天气预报也是一个例子。比起常规认为蝴蝶效应是说蝴蝶煽动翅膀就能导致飓风,一个更好的理解应该是蝴蝶导致了空气状态的不稳定。这样微观的不确定性被持续放大,甚至超过飓风。就像几乎没人能预测几年之后某一天是晴天还是雨天一样。(出题:最后一段的作用?提到蝴蝶效应的意义?)
Main Idea: Explain Chaos Theory with multiple example and point out "sensitive dependence" actually generates unpredictablity.
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