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

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.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-07-30
DOI
https://doi.org/10.5281/zenodo.17224106
Primary Topic
Anaerobic Digestion and Biogas Production
Type
article
Field-Weighted Citation Impact
0.00
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article

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

Zenodo (CERN European Organization for Nuclear Research)
Anaerobic Digestion and Biogas Production
article

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

article en

Abstract

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.

Zenodo (CERN European Organization for Nuclear Research)
Anna University, Chennai (IN), Anna University Regional Campus, Coimbatore
Peace, Justice and strong institutions
Openalex Percentile: Top 49%
Anaerobic Digestion and Biogas Production
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