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Possible Answers:
NNW.
Last seen on: –Wall Street Journal Crossword – February 12 2023 – In the Drink
Wall Street Journal Crossword – February 12 2023 – In the Drink
Random information on the term “Compass heading”:
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In navigation, bearing or azimuth is the horizontal angle between the direction of an object and north or another object. The angle value can be specified in various angular units, such as degrees, mils, or grad. More specifically:
Alternatively, the US Army defines the bearing from point A to point B as the smallest angle between the ray AB and either north or south, whichever is closest. The bearing is expressed in terms of 2 characters and 1 number: first, the character is either N or S; next is the angle numerical value; third, the character representing the perpendicular direction, either E or W. The bearing angle value will always be less than 90 degrees. For example, if Point B is located exactly southeast of Point A, the bearing from Point A to Point B is “S 45° E”. For example, if the bearing between Point A and Point B is S 45° E, the azimuth between Point A and Point B is 135°.
Random information on the term “NNW”:
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A neural network is a network or circuit of biological neurons, or, in a modern sense, an artificial neural network, composed of artificial neurons or nodes. Thus, a neural network is either a biological neural network, made up of biological neurons, or an artificial neural network, used for solving artificial intelligence (AI) problems. The connections of the biological neuron are modeled in artificial neural networks as weights between nodes. A positive weight reflects an excitatory connection, while negative values mean inhibitory connections. All inputs are modified by a weight and summed. This activity is referred to as a linear combination. Finally, an activation function controls the amplitude of the output. For example, an acceptable range of output is usually between 0 and 1, or it could be −1 and 1.
These artificial networks may be used for predictive modeling, adaptive control and applications where they can be trained via a dataset. Self-learning resulting from experience can occur within networks, which can derive conclusions from a complex and seemingly unrelated set of information.