Research Article
Optimal Learning Behavior Prediction System Based on Cognitive Style Using Adaptive Optimization-Based Neural Network
Algorithm 1
Grey wolf optimizer algorithm.
| Input: search population variable , solution size a, the solution from upper to lower limit | | , maximum iteration | | Output: the topmost pounce factor | (1) | Initialize the population of grey wolf solution where and | (2) | Initialize d, , , and i = 1 | (3) | Estimate every search factor fitness , and hence | (4) | = the primary best search factor | (5) | = the secondary best search factor | (6) | = the tertiary best search factor | (7) | while (i < maximum iteration) do | (8) | for every search factor do | (9) | Upgrade the current search factor location using equation (9) | (10) | end for | (11) | Upgrade d, , and | (12) | Estimate every search factor fitness | (13) | Upgrade , , and | (14) | i = i + 1 | (15) | end while | (16) | return |
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