Main Reference PaperLearning Customer Behaviors for Effective Load Forecasting, IEEE transactions on knowledge and data engineering, 2018.
  • The proposed Sparse Continuous Conditional Random Fields (sCCRF) method accumulates the customers based on their energy consumption to forecast the load for every customer using the hierarchical clustering. It mitigates the computational cost of the prediction system.

+ Description
  • The proposed Sparse Continuous Conditional Random Fields (sCCRF) method accumulates the customers based on their energy consumption to forecast the load for every customer using the hierarchical clustering. It mitigates the computational cost of the prediction system.

  • To perform load forecasting based on energy consumption

  • To enhance the accuracy of load forecasting

+ Aim & Objectives
  • To perform load forecasting based on energy consumption

  • To enhance the accuracy of load forecasting

  • To explore the proposed system in various market domains

+ Contribution
  • To explore the proposed system in various market domains

  • 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.

Professional Ethics: We S-Logix would appreciate the students those who willingly contribute with atleast a line of thinking of their own while preparing the project with us. It is advised that the project given by us be considered only as a model project and be applied with confidence to contribute your own ideas through our expert guidance and enrich your knowledge.

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