Predicting Seminal Quality Using Back-Propagation Neural Networks with Optimal Feature Subsets

摘要: Many studies have shown that there is a decline in seminal quality during the past two decades. Seminal may be affected by environmental factors and health status, as well life habits. Artificial intelligence (AI) technology has been recently applied to recognize this effect. However, conventional AI algorithms are not prepared cope with class-imbalanced fertility dataset. To end, back-propagation neural network (BPNN) used predict profile of an individual from A neural-genetic algorithm (N-GA) employed select optimal feature subsets optimize parameters network. Results indicate proposed method outperforms other methods on prediction terms precision accuracy.