Artificial neural networks based optimization techniques: A review
In the last few years, intensive research has been done to enhance artificial intelligence (AI)
using optimization techniques. In this paper, we present an extensive review of artificial …
using optimization techniques. In this paper, we present an extensive review of artificial …
Machine learning methods for modelling the gasification and pyrolysis of biomass and waste
S Ascher, I Watson, S You - Renewable and Sustainable Energy Reviews, 2022 - Elsevier
Over the past two decades, the use of machine learning (ML) methods to model biomass
and waste gasification/pyrolysis has increased rapidly. Only 70 papers were published in …
and waste gasification/pyrolysis has increased rapidly. Only 70 papers were published in …
A review of deep learning with special emphasis on architectures, applications and recent trends
Deep learning (DL) has solved a problem that a few years ago was thought to be intractable—
the automatic recognition of patterns in spatial and temporal data with an accuracy superior …
the automatic recognition of patterns in spatial and temporal data with an accuracy superior …
A framework for designing the architectures of deep convolutional neural networks
Recent advances in Convolutional Neural Networks (CNNs) have obtained promising
results in difficult deep learning tasks. However, the success of a CNN depends on finding …
results in difficult deep learning tasks. However, the success of a CNN depends on finding …
Effective scheduling algorithm for load balancing in fog environment using CNN and MPSO
Fog computing (FC) designates a decentralized computing structure placed among the
devices that produce data and cloud. Such flexible structure empowers users to place …
devices that produce data and cloud. Such flexible structure empowers users to place …
A survey on particle swarm optimization with emphasis on engineering and network applications
Swarm intelligence is a kind of artificial intelligence that is based on the collective behavior
of the decentralized and self-organized systems. This work focuses on reviewing a heuristic …
of the decentralized and self-organized systems. This work focuses on reviewing a heuristic …
Automatic quality assessment of echocardiograms using convolutional neural networks: feasibility on the apical four-chamber view
AH Abdi, C Luong, T Tsang, G Allan… - IEEE transactions on …, 2017 - ieeexplore.ieee.org
Echocardiography (echo) is a skilled technical procedure that depends on the experience of
the operator. The aim of this paper is to reduce user variability in data acquisition by …
the operator. The aim of this paper is to reduce user variability in data acquisition by …
Eight years of AutoML: categorisation, review and trends
Abstract Knowledge extraction through machine learning techniques has been successfully
applied in a large number of application domains. However, apart from the required …
applied in a large number of application domains. However, apart from the required …
Hyper‐parameters optimisation of deep CNN architecture for vehicle logo recognition
The training of deep convolutional neural network (CNN) for classification purposes is
critically dependent on the expertise of hyper‐parameters tuning. This study aims to …
critically dependent on the expertise of hyper‐parameters tuning. This study aims to …
Financial time series prediction using elman recurrent random neural networks
J Wang, J Wang, W Fang, H Niu - Computational intelligence …, 2016 - Wiley Online Library
In recent years, financial market dynamics forecasting has been a focus of economic
research. To predict the price indices of stock markets, we developed an architecture which …
research. To predict the price indices of stock markets, we developed an architecture which …