Genetic Algorithm-based Fuzzy Optimization Neural Network Model for WSNs Performance Evaluation
Fawang Han · International Journal of Future Generation Communication and Networking · 2014
In recent years, wireless sensor network is becoming the hottest research fields, which opens up a wealth of opportunities for many application domains.Comprehensive performance of WSNs is important for planning and management of a construction network.In order to deal with the deficiency of existing evaluation methods for WSNs performance, an intelligent evaluation model based on fuzzy optimization neural network model is proposed, which introduces genetic algorithm to optimize the connection weight of the neural network model to achieve approximate optimal solution.The weights are to be regarded as initial values for the next step that a neural network is tuned finely further.Fuzzy optimization model is as activation function of the neural network, therefore the model has explicit physical meanings.This model is applied to evaluate WSNs performance of some samples, and the comparative analysis with other models shows that the model improves evaluation precision and efficiency and is practical.The first part is the research status and related problems.The second part is the establishment of evaluation model.The last part is the experimental analysis and conclusion.