[HTML][HTML] Application of meta-heuristic algorithms for training neural networks and deep learning architectures: A comprehensive review
M Kaveh, MS Mesgari - Neural Processing Letters, 2023 - Springer
The learning process and hyper-parameter optimization of artificial neural networks (ANNs)
and deep learning (DL) architectures is considered one of the most challenging machine …
and deep learning (DL) architectures is considered one of the most challenging machine …
Metaheuristic design of feedforward neural networks: A review of two decades of research
Over the past two decades, the feedforward neural network (FNN) optimization has been a
key interest among the researchers and practitioners of multiple disciplines. The FNN …
key interest among the researchers and practitioners of multiple disciplines. The FNN …
An improved particle swarm optimization with backtracking search optimization algorithm for solving continuous optimization problems
HRR Zaman, FS Gharehchopogh - Engineering with Computers, 2022 - Springer
The particle swarm optimization (PSO) is a population-based stochastic optimization
technique by the social behavior of bird flocking and fish schooling. The PSO has a high …
technique by the social behavior of bird flocking and fish schooling. The PSO has a high …
Building electrical energy consumption forecasting analysis using conventional and artificial intelligence methods: A review
It is important for building owners and operators to manage the electrical energy
consumption of their buildings. As electrical energy is the major form of energy consumed in …
consumption of their buildings. As electrical energy is the major form of energy consumed in …
Applications of artificial neural networks for thermal analysis of heat exchangers–a review
Artificial neural networks (ANN) have been widely used for thermal analysis of heat
exchangers during the last two decades. In this paper, the applications of ANN for thermal …
exchangers during the last two decades. In this paper, the applications of ANN for thermal …
[HTML][HTML] Prediction of flyrock distance induced by mine blasting using a novel Harris Hawks optimization-based multi-layer perceptron neural network
In mining or construction projects, for exploitation of hard rock with high strength properties,
blasting is frequently applied to breaking or moving them using high explosive energy …
blasting is frequently applied to breaking or moving them using high explosive energy …
A distributed PSO–SVM hybrid system with feature selection and parameter optimization
CL Huang, JF Dun - Applied soft computing, 2008 - Elsevier
This study proposed a novel PSO–SVM model that hybridized the particle swarm
optimization (PSO) and support vector machines (SVM) to improve the classification …
optimization (PSO) and support vector machines (SVM) to improve the classification …
A particle swarm optimization-based flexible convolutional autoencoder for image classification
Convolutional autoencoders (CAEs) have shown their remarkable performance in stacking
to deep convolutional neural networks (CNNs) for classifying image data during the past …
to deep convolutional neural networks (CNNs) for classifying image data during the past …
Multi-fault classification based on wavelet SVM with PSO algorithm to analyze vibration signals from rolling element bearings
Condition monitoring and fault diagnosis of rolling element bearings timely and accurately is
very important to ensure the reliable operation of rotating machinery. In this paper, a multi …
very important to ensure the reliable operation of rotating machinery. In this paper, a multi …
Convolutional neural network forecasting of European Union allowances futures using a novel unconstrained transformation method
This paper develops an open-high-low-close (OHLC) data forecasting framework to forecast
EUA futures price based on EU ETS data and extended exogenous variables from 2013 to …
EUA futures price based on EU ETS data and extended exogenous variables from 2013 to …