Main Reference PaperA load prediction model for cloud computing using PSO-based weighted wavelet support vector machine, Applied Intelligence, 2018 [Java/Python/R]
  • To predict the load on the cloud data center, the proposed work combines the wavelet transform and support vector machine to assign the weight of the sample, which reflects the importance of different sample points and improves the accuracy of load prediction. To reduce the time complexity, the PSO algorithm is proposed to find the optimal combination of the parameters of the prediction algorithm.

+ Description
  • To predict the load on the cloud data center, the proposed work combines the wavelet transform and support vector machine to assign the weight of the sample, which reflects the importance of different sample points and improves the accuracy of load prediction. To reduce the time complexity, the PSO algorithm is proposed to find the optimal combination of the parameters of the prediction algorithm.

  • To predict the load on cloud data.

  • Reduces the time complexity.

+ Aim & Objectives
  • To predict the load on cloud data.

  • Reduces the time complexity.

  • The proposed scheme can be tested on any real-time datasets.

+ Contribution
  • The proposed scheme can be tested on any real-time datasets.

  • OS: Ubuntu 12.04 LTS 64bit

  • Language: Java/Python/R

+ Software Tools & Technologies
  • OS: Ubuntu 12.04 LTS 64bit

  • Language: 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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