Approach to the Highest HXR Yield in Plasma Focus Device Using Adaptive Neurofuzzy Inference System to Optimize Anode Configuration | Zendy

M. Mahtab | Zendy; Mostafa Taghipour | Zendy; Gholam Hossein Roshani | Zendy; Morteza Habibi | Zendy

Open Access

Approach to the Highest HXR Yield in Plasma Focus Device Using Adaptive Neurofuzzy Inference System to Optimize Anode Configuration

Author(s) -

M. Mahtab,

Mostafa Taghipour,

Gholam Hossein Roshani,

Morteza Habibi

Publication year - 2014

Publication title -

journal of experimental physics

Language(s) - English

Resource type - Journals

eISSN - 2356-7368

pISSN - 2314-7849

DOI - 10.1155/2014/307403

Subject(s) - anode , adaptive neuro fuzzy inference system , dense plasma focus , focus (optics) , yield (engineering) , inference , plasma , inference system , intensity (physics) , materials science , computer science , physics , optics , artificial intelligence , composite material , electrode , nuclear physics , fuzzy control system , quantum mechanics , fuzzy logic

Adaptive neurofuzzy inference system (ANFIS) is investigated to optimize the configuration of anode shape in plasma focus devices to achieve the highest X-ray yield. Variables of discharge voltage, filling gas pressure, and angles of anode slopes (Φ1 and Φ2) are chosen as input parameters, while the output is designated to be the radiated hard X-ray intensity. The trained ANFIS has achieved good agreement with the experimental results and has mean relative error percentages (MRE%) 1.12% and 2.18% for training and testing data, respectively. The study demonstrates that adaptive neurofuzzy inference system is useful, reliable, and low-cost way to interpret the highest X-ray yield and corresponding anode configuration in plasma focus devices.

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