Prophecies using Physics Involved Neural Networks (PINNs) for achieving the accuracy using AI Models in discrete Kinematics

Ramadoss, Ashok Kumar (2025) Prophecies using Physics Involved Neural Networks (PINNs) for achieving the accuracy using AI Models in discrete Kinematics. International Journal of Science and Research Archive, 16 (1). pp. 444-453. ISSN 2582-8185

Artificial Nonmonotonic Neural schema or Networks (ANNNs), a kind of hybrid learning systems that are capable of nonmonotonic reasoning. Nonmonotonic reasoning plays an important role in the development of artificial intelligent systems that try to mimic common sense reasoning, as exhibited by humans in slow and steady but the error is minimized unlike in monotonic where the decision is fast but with more errors. on the other hand, a hybrid learning system provides an explanation capability to trained Neural Networks through acquiring symbolic knowledge of a domain, refining it using a set of classified examples along with Connectionist learning techniques and, finally, extracting comprehensible symbolic information.