The procedure to diagnose anemia is time-consuming and resource-intensive due to the
existence of a multitude of symptoms that can be felt physically or seen visually. Anemia also …

Abstract The Internet of Things (IoT) concept is widely used today. As IoT becomes more
widely adopted, the number of devices communicating wirelessly (using various …

Predicting consumption behavior is very important for adjusting supplier production plans
and enterprise marketing activities. Conventional statistical methods are unable to …

The incremental version of randomized neural networks provides a greedy constructive
algorithm for the shallow network, which adds new nodes through different stochastic …

Abstract Randomized-based Feedforward Neural Networks approach regression and
classification (binary and multi-class) problems by minimizing the same optimization …

The practical applicability of smart control systems suffers from the existence of uncertainty
in the physical parameters, sensor measurements and external excitations. Effective …

TfELM introduces an innovative Python framework leveraging TensorFlow for Extreme
Learning Machines (ELMs), offering a comprehensive suite for diverse machine learning …

Abstract As a new Single Layer Feedforward Network (SLFN) architecture, Broad Learning
System (BLS) has been widely used in the field of fault diagnosis because of its fast-training …

The force feedback technology has a crucial impact on the precise control of teleoperation
system. Robots in fields such as minimally invasive surgery and nuclear waste cannot …

Time series modelling is of significance to several scientific fields. Several approaches
based on statistics, machine learning or combinations have been utilized. In order to model …