引导式测验 · 中等 等级

人工智能在灾难响应测验中的应用

测试洪水预报、损害图像、基于图形的天气模型、危机消息分类、基础设施依赖性和模型输出的限制。

相关引导路径人工智能在灾难应对中的应用
问题 1 的 8

What does Google's Flood Hub provide to its users?

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  1. What does Google's Flood Hub provide to its users?
    • A guarantee that every flood is predicted perfectly
    • Model-based flood forecasts and related location-specific information
    • Physical flood barriers constructed by software
    • Automatic confirmation of every social-media report
  2. 人工智能系统通常如何绘制灾难后建筑物损坏的地图？
    • 通过采访每一位居民
    • 根据新闻猜测
    • 通过计算电话数量
    • 通过变化检测比较前后图像
  3. What modeling approach is central to the GraphCast weather-forecasting study?
    • A graph neural network trained for global weather forecasting
    • A rule that no weather observations are needed
    • A speech-only transcription model
    • A guarantee of identical performance on every hazard and machine
  4. 为什么灾难响应模型无法应对新事件？
    • 灾难太常见了
    • 他们只在夏天工作
    • 根据过去事件训练的模型可能无法推广到新事件
    • 他们不需要训练数据
  5. What disaster-information function did the AIDR project demonstrate for microblog messages?
    • Guaranteed automatic verification of every message's location and truth
    • Prediction of all future earthquakes from punctuation
    • Replacement of every responder's decision with a text label
    • Supervised classification of crisis-related messages using labeled examples
  6. Why should a disaster-information workflow account for communication and power dependencies?
    • Every network is guaranteed to remain available during an event
    • Infrastructure disruptions can prevent the workflow from receiving or sharing needed data
    • Power supply never affects communication equipment
    • A model's confidence restores damaged infrastructure automatically
  7. What should a crisis-message classification label establish by itself?
    • That the claimed need is definitely current and verified
    • That every reported location has been measured precisely
    • Only the model's classification, with the post's time, location, and factual support still needing assessment
    • That the message must be genuine because it contains a disaster keyword
  8. Why is a difference between pre- and post-event satellite images not automatically proof of building damage?
    • Image timing, alignment, visibility, and other scene changes can also affect the comparison
    • Every changed pixel has exactly one possible cause
    • The image file extension establishes a physical damage class
    • No post-event image can contain any useful evidence