Extreme learning machine (ELM) has gained increasing interest from various research fields
recently. In this review, we aim to report the current state of the theoretical research and …

In this paper, a prediction system has been developed using machine learning techniques to
obtain the conduction emission levels ensure they remain below the limit values specified in …

A key issue within the emissions trading system is how tradable emissions permits (TEPs)
are initially allocated among a set of entities. This study proposes an approach based on the …

This paper presents a novel artificial neural network (ANN) model estimating vehicle-level
radiated magnetic emissions of an electric car as a function of the corresponding driving …

This article comprises a review of various sequential algorithms. The review represents the
working nature of the learning methods. It also includes the methods such as Minimal …

Firmalar, ürettikleri elektronik cihazlara, bu alandaki yetkin laboratuvar ortamlarından
yararlanarak sivil ve askeri standartlar kapsamında EMI/EMC testleri uygulamaktadır. Bu …

The increment of the use of electric vehicles leads to a worry about measuring its principal
source of environmental pollution: electromagnetic emissions. Given the complexity of …

Aiming at the problem of the existing fault monitoring method such as intensive computation,
dependence on the length of data, and difficult of finding out the abnormal situation, a fast …

The increment of the use of electric vehicles leads to a worry about measuring its principal
source of environmental pollution: electromagnetic emissions. Given the complexity of …

Background: Radio Frequency (RF) emission of electrical equipment has become a major
concern with regard to electromagnetic compatibility (EMC) and its relevant international …