Application of meta-heuristic algorithms for training neural networks and deep learning architectures: A comprehensive review
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 …
Application of swarm intelligence optimization algorithms in image processing: A comprehensive review of analysis, synthesis, and optimization
M Xu, L Cao, D Lu, Z Hu, Y Yue - Biomimetics, 2023 - mdpi.com
Image processing technology has always been a hot and difficult topic in the field of artificial
intelligence. With the rise and development of machine learning and deep learning …
intelligence. With the rise and development of machine learning and deep learning …
IWOA: An improved whale optimization algorithm for optimization problems
The whale optimization algorithm (WOA) is a new bio-inspired meta-heuristic algorithm
which is presented based on the social hunting behavior of humpback whales. WOA suffers …
which is presented based on the social hunting behavior of humpback whales. WOA suffers …
Optimizing biodiesel production from abundant waste oils through empirical method and grey wolf optimizer
The failure of classical techniques and algorithms have triggered researchers to search for
stochastic tools capably of exploring the search space with constant convergence speed …
stochastic tools capably of exploring the search space with constant convergence speed …
Fuzzy-ChOA: an improved chimp optimization algorithm for marine mammal classification using artificial neural network
Chimp optimization algorithm (ChOA) is a robust nature-inspired technique, which was
recently proposed for addressing real-world challenging engineering problems. Due to the …
recently proposed for addressing real-world challenging engineering problems. Due to the …
Soil moisture simulation using hybrid artificial intelligent model: Hybridization of adaptive neuro fuzzy inference system with grey wolf optimizer algorithm
Accurate estimation of soil moisture content is necessary for optimal management of water
and soil resources. Soil moisture is an important variable in the hydrologic cycle, which …
and soil resources. Soil moisture is an important variable in the hydrologic cycle, which …
Reference evapotranspiration estimating based on optimal input combination and hybrid artificial intelligent model: Hybridization of artificial neural network with grey …
Reference Evapotranspiration (ET o) is one of the key components of the hydrological cycle
that is effective in water resources planning, irrigation and agricultural management and …
that is effective in water resources planning, irrigation and agricultural management and …
[HTML][HTML] Multi-objective sustainable location-districting for the collection of municipal solid waste: Two case studies
SM Darmian, S Moazzeni, LM Hvattum - Computers & Industrial …, 2020 - Elsevier
This paper presents a multi-objective location-districting optimization model for sustainable
collection of municipal solid waste, motivated by strategic waste management decisions in …
collection of municipal solid waste, motivated by strategic waste management decisions in …
Artificial neural network-assisted theoretical model to predict the viscoelastic–plastic tensile behavior of polyamide-6 multi-ply yarns
Multi-ply yarns have been used as the main structure to form strands, braids, and fabrics.
Thus, various strategies including experimental, numerical, and analytical models have …
Thus, various strategies including experimental, numerical, and analytical models have …
[HTML][HTML] Predictive model of energy consumption for office building by using improved GWO-BP
Y Tian, J Yu, A Zhao - Energy Reports, 2020 - Elsevier
Building energy data analysis is a major branch of smart city development research. The
usual back propagation neural network model for building energy prediction has problems …
usual back propagation neural network model for building energy prediction has problems …