This project aims to develop algorithmic development of Scalable Fuzzy Neural Network. The goal is to answer the data stream challenges which arrives continuously and contains drift.

Principal investigator

Choiru Za'in
Magnifying glass

Area of science

Computer Science

Systems used


Applications used

Jupyter notebook, Spark, Rstudio Server
Partner Institution: La Trobe University| Project Code: 62db76545a9242d89a4e1c04618ab13f

The Challenge

While there have been some approaches have been developed, other challenges such as high volumes of data and minimum labeling problem have not been discovered.

The Solution

We built a novel approach namely Scalable teacher forcing network for weakly supervised learning using distributed learning and weakly supervised method respectively.

The Outcome

We have submitted to the Q1 Journal. It is under review.