Main Reference PaperAn improved robust heteroscedastic probabilistic neural network based trust prediction approach for cloud service selection, Neural Networks, 2018 [Java/Python/R]
  • An Improved Robust Heteroscedastic Probabilistic Neural Network (HCRHRPNN) is proposed to predict the trust in the cloud computing environment. It discovers the informative samples by using the dimensionality reduction on the basis of hypergraph coarsening to reduce the training time and improve the performance.

+ Description
  • An Improved Robust Heteroscedastic Probabilistic Neural Network (HCRHRPNN) is proposed to predict the trust in the cloud computing environment. It discovers the informative samples by using the dimensionality reduction on the basis of hypergraph coarsening to reduce the training time and improve the performance.

  • To forecast the trustworthiness in a cloud computing environment

  • To enhance the accuracy of prediction and mitigate run time

+ Aim & Objectives
  • To forecast the trustworthiness in a cloud computing environment

  • To enhance the accuracy of prediction and mitigate run time

  • The precise selection of the relevant historical data for the prediction will improve the accuracy.

+ Contribution
  • The precise selection of the relevant historical data for the prediction will improve the accuracy.

  • Operating system: Ubuntu / Windows

  • Java/Python/R

+ Software Tools & Technologies
  • Operating system: Ubuntu / Windows

  • Java/Python/R

  • M.E / M.Tech/ MS / Ph.D.- Customized according to the client requirements.

+ Project Recommended For
  • M.E / M.Tech/ MS / Ph.D.- Customized according to the client requirements.

  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

+ Order To Delivery
  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

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