Cell Viability Prediction Based on Improved Fuzzy Neural Network
Aiming at the prediction of cell viability,a fuzzy neural network based on adaptive differential evolution(ADE-FNN)prediction model is proposed,which is optimized by adaptive differential evolution algorithm.Firstly,a variety of influencing factors in the process of cell culture,such as medium composition,temperature,pH value and so on,are fuzzified,and these factors are used as the input of fuzzy neural network.Then,the existing cell activity data are used to train the model and optimize the network parameters.After many iterations and adjustments,the model gradually learned the complex mapping relationship between input and output.Finally,the performance of the proposed ADE-FNN algorithm is verified by cell viability simulation experiments.The results show that the cell activity prediction model based on fuzzy neural network has high prediction accuracy and generalization ability.Compared with the traditional statistical methods,this model can better deal with the uncertainty and noise in the data,so as to provide more accurate prediction results.In addition,the model also has good interpretability,which is helpful to understand the influencing factors of cell activity and its mechanism.
万方数据
维普
