Research Article
A Method for Parameters Estimation in a Dynamical Model of Ebola Virus Transmission in Sierra Leone
Algorithm 1
Parameter estimation of GA.
(1) | Parameter length is determined according to parameter range. | (2) | Each parameter is represented by a chromosome of length to get a complete parameters set . | (3) | Initialize all parameters set, . | (4) | Evaluate the fitness of each using . | (5) | for Constant do | (6) | ifdo | (7) | Sort allocation fitness in an ascending order. | (8) | . | (9) | . | (10) | end if | (11) | Randomly add an initialization parameter to replace one of the | (12) | if max close to average do | (13) | Mutation probability | (14) | end if | (15) | Randomly select . | (16) | Cross over and according to , . | (17) | Perform mutation on and according to . | (18) | . | (19) | Evaluate fitness . | (20) | ifdo | (21) | . | (22) | end if | (23) | ifdo | (24) | Multiple crossover and variation. | (25) | end if | (26) | Find the best parameters set in this generation that satisfies . | (27) | end for | (28) | Find the best parameters set that satisfies . |
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