This time we are looking on the crossword clue for: Hurricane dir..
it’s A 14 letters crossword puzzle definition. See the possibilities below.
Did you find what you needed?
We hope you did!. If you are still unsure with some definitions, don’t hesitate to search them here with our crossword solver.
Possible Answers: NNE, NNW.
Random information on the term “NNE”:
In navigation bearing may refer, depending on the context, to any of: (A) the direction or course of motion itself; (B) the direction of a distant object relative to the current course (or the “change” in course that would be needed to get to that distant object); or (C), the angle away from North of a distant point as observed at the current point.[citation needed]
Absolute bearing refers to the angle between the magnetic North (magnetic bearing) or true North (true bearing) and an object. For example, an object to the East would have an absolute bearing of 90 degrees. Relative bearing refers to the angle between the craft’s forward direction, and the location of another object. For example, an object relative bearing of 0 degrees would be dead ahead; an object relative bearing 180 degrees would be behind. Bearings can be measured in mils or degrees.
The US Army defines the bearing from Point A to Point B as the angle between a ray in the direction of north or south, whose origin is Point A, and Ray AB, the ray whose origin is Point A and which contains Point B. The bearing consists of 2 characters and 1 number: first, the character is either N or S. Next is the angle value. Third, the character representing the direction of the angle away from the reference ray – thus, either E, or W. The 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.
Random information on the term “NNW”:
Artificial neural networks (ANNs) or connectionist systems are a computational model used in machine learning, computer science and other research disciplines, which is based on a large collection of connected simple units called artificial neurons, loosely analogous to axons in a biological brain. Connections between neurons carry an activation signal of varying strength.[further explanation needed] If the combined incoming signals are strong enough, the neuron becomes activated and the signal travels to other neurons connected to it. Such systems can be trained from examples, rather than explicitly programmed, and excel in areas where the solution or feature detection is difficult to express in a traditional computer program. Like other machine learning methods, neural networks have been used to solve a wide variety of tasks, like computer vision and speech recognition, that are difficult to solve using ordinary rule-based programming.
Typically, neurons are connected in layers, and signals travel from the first (input), to the last (output) layer. Modern neural network projects typically have a few thousand to a few million neural units and millions of connections; their computing power is similar to a worm brain, several orders of magnitude simpler than a human brain. The signals and state of artificial neurons are real numbers, typically between 0 and 1. There may be a threshold function or limiting function on each connection and on the unit itself, such that the signal must surpass the limit before propagating. Back propagation is the use of forward stimulation to modify connection weights, and is sometimes done to train the network using known correct outputs.[further explanation needed] However, the success is unpredictable: after training, some systems are good at solving problems while others are not. Training typically requires several thousand cycles of interaction.[citation needed]