The modified immune diversity algorithm used in function optimization

The immune system has many characteristics to solve engineering and science problems.An artificial immune system is a novel intelligence system based on the characteristics of a real-life immune system.By using clone selection and clone suppression,the modified immune clone diversity algorithm in accordance with diversity,an algorithm used to solve the function optimization is presented to obtain a simplified algorithm for complex functions.The diversity algorithm is a developed algorithm based on the diversity of antibodies in the immune system.The concrete steps are presented,and the main differences between them are identified.The dependence principles of immune systems are also pointed out and the complexity of computation is analyzed.The paper shows that the modified immune clone diversity algorithm can optimize the complex functions by using fewer candidate solution colonies.