A review on representative swarm intelligence algorithms for solving optimization problems: Applications and trends

J Tang, G Liu, Q Pan - IEEE/CAA Journal of Automatica Sinica, 2021 - ieeexplore.ieee.org
Swarm intelligence algorithms are a subset of the artificial intelligence (AI) field, which is
increasing popularity in resolving different optimization problems and has been widely …

[HTML][HTML] Nanoparticles: Taking a unique position in medicine

TM Joseph, D Kar Mahapatra, A Esmaeili, Ł Piszczyk… - Nanomaterials, 2023 - mdpi.com
The human nature of curiosity, wonder, and ingenuity date back to the age of humankind. In
parallel with our history of civilization, interest in scientific approaches to unravel …

[HTML][HTML] Coati Optimization Algorithm: A new bio-inspired metaheuristic algorithm for solving optimization problems

M Dehghani, Z Montazeri, E Trojovská… - Knowledge-Based …, 2023 - Elsevier
In this paper, a new metaheuristic algorithm called the Coati Optimization Algorithm (COA) is
introduced, which mimics coati behavior in nature. The fundamental idea of COA is the …

[PDF][PDF] POA: Puzzle Optimization Algorithm.

FA Zeidabadi, M Dehghani - … Journal of Intelligent Engineering & Systems, 2022 - inass.org
Optimization plays a key role in various disciplines of science in order to achieve the optimal
solution among all available solutions. Innovation and contribution of this paper is in …

Tasmanian devil optimization: a new bio-inspired optimization algorithm for solving optimization algorithm

M Dehghani, Š Hubálovský, P Trojovský - IEEE Access, 2022 - ieeexplore.ieee.org
In this paper, a new bio-inspired metaheuristic algorithm called Tasmanian Devil
Optimization (TDO) is designed that mimics Tasmanian devil behavior in nature. The …

[HTML][HTML] Data-driven modeling and learning in science and engineering

FJ Montáns, F Chinesta, R Gómez-Bombarelli… - Comptes Rendus …, 2019 - Elsevier
In the past, data in which science and engineering is based, was scarce and frequently
obtained by experiments proposed to verify a given hypothesis. Each experiment was able …

A comprehensive review of the load forecasting techniques using single and hybrid predictive models

A Al Mamun, M Sohel, N Mohammad… - IEEE …, 2020 - ieeexplore.ieee.org
Load forecasting is a pivotal part of the power utility companies. To provide load-shedding
free and uninterrupted power to the consumer, decision-makers in the utility sector must …

[图书][B] An introduction to agent-based modeling: modeling natural, social, and engineered complex systems with NetLogo

U Wilensky, W Rand - 2015 - books.google.com
A comprehensive and hands-on introduction to the core concepts, methods, and
applications of agent-based modeling, including detailed NetLogo examples. The advent of …

Securing the internet of things in the age of machine learning and software-defined networking

F Restuccia, S D'oro, T Melodia - IEEE Internet of Things …, 2018 - ieeexplore.ieee.org
The Internet of Things (IoT) realizes a vision where billions of interconnected devices are
deployed just about everywhere, from inside our bodies to the most remote areas of the …

[HTML][HTML] MLP-PSO hybrid algorithm for heart disease prediction

A Al Bataineh, S Manacek - Journal of Personalized Medicine, 2022 - mdpi.com
Background: Machine Learning (ML) is becoming increasingly popular in healthcare,
particularly for improving the timing and accuracy of diagnosis. ML can provide disease …