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We propose in this paper the K-means-Greedy Algorithm (KGA) model to automate the process of finding the optimal value of the number of neurons in the hidden layer. The premise is that a backpropagation (BP) network which has this optimal number of neurons in its hidden layer would be able to produce accurate predictions of unknown values of a time series that it is trained with. We show that the...
In order to reduce muzzle disturbance of gun, establish virtual prototype of a type of howitzer based on complex factors such as mass eccentricity of recoil parts, soil stiffness and damping, clearance of elevating mechanism, stiffness and damping of papilionaceous spring. Use velocity and angular velocity to reflect muzzle disturbance, then examine, simulate and analyze the virtual prototype. According...
Providing a soft-sensing modeling method of vinyl acetate (VAC) polymerization rate based on BP neural network. Solving the current problem that the VAC polymerization rate in the polyvinyl alcohol (PVA) producing process is hard to real-time measuring. Using the data samples collected from the scene to train the network. In the network learning process, using the Levenberg-Marquardt optimization...
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