<span>The medium in which it travels through</span>
Source localization in ocean acoustics is posed as a machine learning problem in which data-driven methods learn source ranges directly from observed acoustic data: True.
<h3>What is machine learning?</h3>
Machine learning (ML) is also known as artificial intelligence (AI) and it can be defined as a subfield in computer science which typically focuses on the use of computer algorithms, data-driven techniques (methods) and technologies to develop a smart computer-controlled robot that has the ability to automatically perform and manage tasks that are exclusively meant for humans or solved by using human intelligence.
In Machine learning (ML), data-driven techniques (methods) are used to learn source ranges directly from observed acoustic data in a bid to proffer solutions to source localization in ocean acoustics.
In conclusion, a normalized sample covariance matrix (SCM) is constructed and used as the input, especially after pre-processing the pressure that's received by a vertical linear array in Machine learning (ML).
Read more on machine learning here: brainly.com/question/25523571
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Answer:
250,000
Explanation:
<h2> </h2>
<h2>formula = ( F=ma </h2>
- F=1500N
- a=6m/s^2
- F= ma
- m=?
- 1500/6 = m
- m=250 kg
- 1kg =1000gm so 250kg =250,000gm
- m =250×10^3 gm
<span>A major characteristic of both volcanoes and earthquakes is that they are located in the same geographic area. Most earthquakes are along the edges of tectonic plates. This is where most volcanoes are too. Most earthquakes directly beneath a volcano are caused by the movement of magma.</span>
