Integrated applications of building information modeling and artificial intelligence techniques in the AEC/FM industry
Informatization and automatization are considered mainstream trends in the future
architecture-engineering-construction/facility management (AEC/FM) industry. Building …
architecture-engineering-construction/facility management (AEC/FM) industry. Building …
Lake water temperature modeling in an era of climate change: Data sources, models, and future prospects
Lake thermal dynamics have been considerably impacted by climate change, with potential
adverse effects on aquatic ecosystems. To better understand the potential impacts of future …
adverse effects on aquatic ecosystems. To better understand the potential impacts of future …
Golden eagle optimizer: A nature-inspired metaheuristic algorithm
This paper proposes a nature-inspired swarm-based metaheuristic for solving global
optimization problems called Golden Eagle Optimizer (GEO). The core inspiration of GEO is …
optimization problems called Golden Eagle Optimizer (GEO). The core inspiration of GEO is …
An ensemble of differential evolution and Adam for training feed-forward neural networks
Adam is an adaptive gradient descent approach that is commonly used in back-propagation
(BP) algorithms for training feed-forward neural networks (FFNNs). However, it has the …
(BP) algorithms for training feed-forward neural networks (FFNNs). However, it has the …
Bio-inspired computation: Where we stand and what's next
In recent years, the research community has witnessed an explosion of literature dealing
with the mimicking of behavioral patterns and social phenomena observed in nature towards …
with the mimicking of behavioral patterns and social phenomena observed in nature towards …
A survey on swarm intelligence approaches to feature selection in data mining
One of the major problems in Big Data is a large number of features or dimensions, which
causes the issue of “the curse of dimensionality” when applying machine learning …
causes the issue of “the curse of dimensionality” when applying machine learning …
[HTML][HTML] Population size in particle swarm optimization
AP Piotrowski, JJ Napiorkowski… - Swarm and Evolutionary …, 2020 - Elsevier
Abstract Particle Swarm Optimization (PSO) is among the most universally applied
population-based metaheuristic optimization algorithms. PSO has been successfully used in …
population-based metaheuristic optimization algorithms. PSO has been successfully used in …
Comprehensive taxonomies of nature-and bio-inspired optimization: Inspiration versus algorithmic behavior, critical analysis recommendations
In recent algorithmic family simulates different biological processes observed in Nature in
order to efficiently address complex optimization problems. In the last years the number of …
order to efficiently address complex optimization problems. In the last years the number of …
Hybrid MPSO-CNN: Multi-level particle swarm optimized hyperparameters of convolutional neural network
P Singh, S Chaudhury, BK Panigrahi - Swarm and Evolutionary …, 2021 - Elsevier
Recent advances in swarm inspired optimization algorithms have shown its extensive
acceptance in solving a wide range of different real-world problems. Particle Swarm …
acceptance in solving a wide range of different real-world problems. Particle Swarm …
Particle swarm optimization or differential evolution—A comparison
AP Piotrowski, JJ Napiorkowski… - Engineering Applications of …, 2023 - Elsevier
In the mid 1990s two landmark metaheuristics have been proposed: Particle Swarm
Optimization and Differential Evolution. Their initial versions were very simple, but rapidly …
Optimization and Differential Evolution. Their initial versions were very simple, but rapidly …