Machine Learning Research

Volume 4, Issue 2, June 2019

  • Learning Algorithms Using BPNN & SFS for Prediction of Compressive Strength of Ultra-High Performance Concrete

    Deepak Choudhary

    Issue: Volume 4, Issue 2, June 2019
    Pages: 27-32
    Received: 4 April 2019
    Accepted: 23 May 2019
    Published: 25 June 2019
    Abstract: This paper presents machine learning algorithms based on back-propagation neural network (BPNN) that employs sequential feature selection (SFS) for predicting the compressive strength of Ultra-High Performance Concrete (UHPC). A database, containing 110 points and eight material constituents, was collected from the literature for the development of... Show More
  • Predicting Diabetes Mellitus Using Artificial Neural Network Through a Simulation Study

    Shehu Usman Gulumbe, Shamsuddeen Suleiman, Shehu Badamasi, Ahmad Yusuf Tambuwal, Umar Usman

    Issue: Volume 4, Issue 2, June 2019
    Pages: 33-38
    Received: 24 July 2019
    Accepted: 16 August 2019
    Published: 2 September 2019
    Abstract: Diabetes mellitus (DM) is a diverse group of metabolic disorders that is frequently associated with a high disease burden in developing countries such as Nigeria. It also needs continuous blood glucose monitoring and self-management. This research is aimed to predict diabetes mellitus using artificial neural network. In this research, 100 patients ... Show More