Prediction of Optimum Design of Anode Shape for Obtaining Highest Soft X-Ray Yield in plasma Focus Device Using Adaptive Neuro-Fuzzy Inference System
Abolfazl Salehizadeh, Mostafa Taghipour, Ehsan Nazemi, Gholam Hossein Roshani, Seyed Amir, Hossein Feghhi · Global perspectives on artificial intelligence · 2014
The computational intelligences such as artificial neural network (ANN) and fuzzy inference system (FIS) are strong tools for prediction and simulation in engineering applications. In this study, adaptive neuro-fuzzy inference system (ANFIS) was used to optimize design of anode shape in order to achieve highest soft X-ray yield in plasma focus devices. The predicted soft X-ray values using the proposed ANFIS model were compared with the experimental data. The proposed ANFIS model achieved good agreement with the experimental results with mean relative error percentage (MRE%) less than 1.14% and 2% for training and testing data, respectively. Moreover, the obtained results showed that the proposed ANFIS model is a useful, reliable, fast and cheap tool to optimize design of anode shape in order to achieve highest soft X-ray yield in plasma focus devices.