Main Reference PaperNeural-fuzzy with representative sets for prediction of student performance, Applied Intelligence, 2018 [Java/Python/R]
  • A proposed method MIMO-SAPP aims to predict the future performance of a student. It uses multiple parameter sets and a special learning strategy to improve the performance of prediction accuracy. The unique learning strategy is to use global and local training. In global training, a random parameter set is trained from the first to the last record of the database. In local training, the dataset is trained by the gradient descent and Particle Swarm Optimization.

+ Description
  • A proposed method MIMO-SAPP aims to predict the future performance of a student. It uses multiple parameter sets and a special learning strategy to improve the performance of prediction accuracy. The unique learning strategy is to use global and local training. In global training, a random parameter set is trained from the first to the last record of the database. In local training, the dataset is trained by the gradient descent and Particle Swarm Optimization.

  • To improve the prediction accuracy.

  • To predict the future performance of a student.

+ Aim & Objectives
  • To improve the prediction accuracy.

  • To predict the future performance of a student.

  • To improve the prediction accuracy, this work investigates the dynamic neuro-fuzzy models and examines the convergence rate analysis.

+ Contribution
  • To improve the prediction accuracy, this work investigates the dynamic neuro-fuzzy models and examines the convergence rate analysis.

  • 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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