Techniques for Data Analysis and Primary Mass Reconstruction in the ENDA Experiment

As a part of the high-altitude LHAASO project, ENDA (Electron Neutron Detector Array) is being created in China. The ENDA concept consists in simultaneous registration of the electromagnetic and thermal neutron components (being a part of hadronic component) of the EAS. The article provides a brief overview of analytical and ML (Machine Learning) methods for shower and primary particle parameters’ reconstruction for simulation of the data. Also, methods for estimation the uncertainty of such reconstruction are presented.