International Journal For Multidisciplinary Research
E-ISSN: 2582-2160
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A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal
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Volume 8 Issue 3
May-June 2026
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Designing a prototype for the multisensory system in the Generative AI with dynamics on a Multi Layer Perception (MLP) of a real-time uncertainty protocol for Humanoid Robotic Control System
| Author(s) | Ashok Kumar Ramadoss |
|---|---|
| Country | India |
| Abstract | In this research an extensive description of the experimental AI perception in the neural network with layer in nodes in the perception has been provided. The GenAI manipulator has been designed, built, and tested in the Robotic Automation Laboratory. It is a crucial problem which is overcome in this present research by introducing the palletization in the correction factor which is explained in this Comprehensive multilayer perception in fuzzy expert robotic system using nonlinear regression. Dynamic fitting movement into the humanoid robot’s microcontroller through the methodology of concurrency which was achieved after several experiments and evidenced, thus enhancing communication from Gen AI with a dynamics to decision makers by making recommendations more credible, understandable, compelling and persuasive. Here Transactions were executed simultaneously from a wide array of input sources. Each of these transactions had the potential to interfere with other running transactions within the datasets, so, the approach handled with a good practice was isolated with the transactions from each other within the multi sensory environment. A way was established for collating the transaction data so that the data was executed with aggregated reports are explained in detail in this scenario which has automatic prediction AI. |
| Keywords | MLP, GENAI, AI, NLC dynamic fit, NW, NS, SF, HF, PA |
| Field | Computer Applications |
| Published In | Volume 7, Issue 1, January-February 2025 |
| Published On | 2025-02-16 |
| DOI | https://doi.org/10.36948/ijfmr.2025.v07i01.37150 |
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E-ISSN 2582-2160
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