A Hybrid Model of Extreme Learning Machine Based on Bat and Cuckoo Search Algorithm for Regression and Multiclass Classification

Table 1

Steps of the bat cuckoo hybrid algorithm.

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Step 1: initialize the basic parameters and set the loop termination criteria

Step 2: initialize the location of the bird nest, calculate the fitness value of each bird nest, and obtain the optimal position and optimal value

Step 3: record the optimal position of the previous generation, update according to formula (15) to obtain a new set of positions, calculate the fitness value, and compare it with the value of the previous generation to determine the current better position

Step 4: compare the random number with ; if , update the position randomly; otherwise, it will not change

Step 5: use the new position as the initial point of the bat algorithm and use equations (9)–(14) to update the position of the bird nest

Step 6: record the position of step 5 and calculate the fitness value to determine the current optimal position and optimal value

Step 7: if the termination conditions are met, continue to the next step; otherwise, go to step 3

Step 8: output the global optimal position, and the algorithm ends

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