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Related Experiment Video

Updated: Sep 18, 2025

WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control
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RETRACTED: Edge computing based english translation model using fuzzy semantic optimal control technique.

Na Wang1

  • 1Jiaozuo Teachers College, Jiaozuo, Henan, China.

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|June 25, 2025
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Summary
This summary is machine-generated.

This study introduces an edge computing translation model (FSRL-P2O) that enhances English translation accuracy. It uses Fuzzy Semantic properties and Reinforcement Learning with Proximal Policy Optimisation for improved machine translation quality.

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Area of Science:

  • Natural Language Processing
  • Artificial Intelligence
  • Computational Linguistics

Background:

  • Growing demand for accurate English translation necessitates advancements in machine translation.
  • Existing models face challenges with ambiguity and suboptimal word choices, impacting translation quality.
  • Edge computing offers potential for localized, efficient processing of translation tasks.

Purpose of the Study:

  • To propose an edge computing-based translation model (FSRL-P2O) for enhanced English translation accuracy.
  • To leverage Fuzzy Semantic properties and Reinforcement Learning with Proximal Policy Optimisation (PPO) for improved translation.
  • To address uncertainties in machine translation, including out-of-domain data and low-quality references.

Main Methods:

  • Corpus data preprocessing and feature extraction.
  • Fuzzy Semantic similarity measurement using Jaccard coefficient to quantify semantic resemblance.
  • Implementation of Reinforcement Learning (RL) and Proximal Policy Optimisation (PPO) as optimal control techniques.

Main Results:

  • The FSRL-P2O model demonstrated improved translation accuracy and higher semantic similarity.
  • Fuzzy Semantic analysis effectively reduced uncertainties in translation.
  • RL and PPO optimized translation policies, enhancing overall output quality.

Conclusions:

  • The proposed FSRL-P2O model significantly improves English translation quality and accuracy.
  • Integrating Fuzzy Semantic similarity and RL/PPO offers a robust approach to machine translation challenges.
  • Edge computing facilitates efficient and accurate machine translation, meeting modern demands.