DCS-ELM: a novel method for extreme learning machine for

Extreme learning machine (ELM) algorithm is widely used in regression and classification problems due to its advantages such as speed and high-performance rate. Different artificial intelligence-based optimization methods and chaotic systems have been proposed for the development of the ELM. However, a generalized solution method and success rate at the desired level could not be obtained. In this study, a new method is proposed as a result of developing the ELM algorithm used in regression problems with discrete-time chaotic systems. ELM algorithm has been improved by testing five different chaotic maps (Chebyshev, iterative, logistic, piecewise, tent) from chaotic systems. The proposed discrete-time chaotic systems based ELM (DCS-ELM) algorithm has been tested in steel fiber reinforced self-compacting concrete data sets and public four different datasets, and a result of its performance compared with the basic ELM algorithm, linear regression, support vector regression, kernel ELM algorithm and weighted ELM algorithm. It has been observed that it gives a better performance than other algorithms.

DCS-ELM: a novel method for extreme learning machine for regression problems and a new approach for the SFRSCC [PeerJ]

Applied Sciences, Free Full-Text

PDF) A novel hybrid teaching-learning-based optimization algorithm for the classification of data by using extreme learning machines

Robustified extreme learning machine regression with applications in outlier-blended wind-speed forecasting - ScienceDirect

A novel adaptive weighted kernel extreme learning machine

PDF) Comparison of activation function on extreme learning machine (ELM) performance for classifying the active compound

Extreme Learning Machine - an overview

Full article: Extreme learning machine – radial basis function (ELM-RBF) networks for diagnosing faults in a steam turbine

A novel online sequential extreme learning machine with L2,1-norm regularization for prediction problems

PeerJ - Just published in PeerJ Computer Science - DCS-ELM: a novel method for extreme learning machine for regression problems and a new approach for the SFRSCC Read the full article #

The graphic description of BAS searching process

A new non-monotonic infeasible simplex-type algorithm for Linear Programming [PeerJ]

10-k cross-validation simple representation.

Frontiers Functional extreme learning machine