Application of Hybrid Genetic Algorithm-BP Neural Networks to Diagnosis of Lung Cancer

Lung cancer is a material cause of cancer death. To forecast CT diagnosis of lung cancer, this paper proposes a hybrid genetic algorithm-BP neural networks (GA-BP algorithm), which introduces multi-species co-evolution genetic algorithm (MCGA) and simulated annealing algorithm (SA), to solve the problem of traditional GA-BP algorithm and avoid trapping in a local minimum. Experiments indicate that the hybrid GA-BP algorithm can accelerate convergence to the optimal solution and provides an effective method for the early diagnosis of lung cancer.