BP classification algorithm based on improved bat algorithm
A bat algorithm and bat technology, applied in computing, manufacturing computing systems, computer components and other directions, to achieve fast convergence speed, enhance local search capabilities, and improve classification accuracy.
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[0025] Step 1: Input the original image, perform LBP processing on the original image, extract feature vectors of information such as inclusions, plaques, cracks, pitting, rolling scale, scratches, etc., and input them to the network.
[0026] Step 2: Initialize the network, set the number of layers of the network, and the number of nodes in each layer of the network.
[0027] Step 3: assign values to the initial parameters of the present invention, including initial position, speed, loudness, frequency, maximum number of iterations, etc.
[0028] Step 4: Calculate the weight experience factor, the position of the bat is determined by X i (t+1)=X i (t)+V i (t+1), the velocity is determined by the equation V ik (t+1)=ω·V ik (t)+(X ik (t)-P k (t)) f i (t) Determine and update loudness and pulse rate.
[0029] Step 5: Record the global optimal position and local optimal position of the current population, and update the speed update using the formula, and obtain the new...
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