A Novel Approach to Improve the Performance of HMI Model Using Bilateral Data Prediction with Neural Network Data Mining From Social Network Using Neural Network

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@article{1705385,
      author = {Jayapal P},
      title = {A Novel Approach to Improve the Performance of HMI Model Using Bilateral Data Prediction with Neural Network Data Mining From Social Network Using Neural Network},
      journal = {Iconic Research And Engineering Journals},
      year = {2024},
      volume = {7},
      number = {7},
      pages = {249-257},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/17053851.pdf},
      abstract = {In this, the data pattern from the sensor can be extracted by using the Equalized Distribution Pattern (EDP) model to find the relevancy between the feature of query data and from the entire dataset and form as the cluster of combination. To enhance the HMI model, the virtual management process are takes care based on the prediction of sensor parameters and to identify the range of parameters with supervised data learning. This type of data learning can be achieved by the improved bilateral neural network technique. To find the matching feature, the Bilateral Data Prediction with Neural Network (BDP-NN). With this system, first the pre-processed feature is matched with the pattern by using BDP-NN to find the type of data without directly passed into the whole dataset. From that type identified result, the similarity between the matched result and overall dataset is retrieved by using the EDP method to display all matched result from the bulk dataset with better classification result.},
      keywords = {Clustering, Database management, Data prediction, Feature extraction, Neural network},
      month = {January},
  }