Research Article
A Cloud-Based Machine Learning Approach to Reduce Noise in ECG Arrhythmias for Smart Healthcare Services
Algorithm 1
Pseudocode of the MCEHO algorithm.
| (1) | Set step sizes for TDEs and Doppler effects | | (2) | Assign generation counter t = 1 and value for Max Gen//maximum generations | | (3) | Assign initial population with step sizes of TDEs and Doppler effects | | (4) | Repeat | | (5) | Sort all the elephants according to their fitness via filter function | | (6) | ci is the step size for all clans | | (7) | ci do for all elephants j in the clan | | (8) | Update xci, and generate xn, cj by equation (29), generate mutation is via mutation operator | | (9) | if xci, j = xbest, ci then | | (10) | Update xci, and generate xn, cj by equation (30) via step size in TDEs and Doppler effect | | (11) | end if | | (12) | end for | | (13) | end for | | (14) | Do this for all ci clans in the population | | (15) | Get rid of the clan’s worst elephant.ci by equation (32) and apply circle map | | (16) | end for | | (17) | Assess the population in light of the newly revised positions according to step size for TDEs and Doppler effect | | (18) | until t < MaxGen | | (19) | Return the best found solution |
|
