Lake water temperature modeling in an era of climate change: Data sources, models, and future prospects

S Piccolroaz, S Zhu, R Ladwig, L Carrea… - Reviews of …, 2024‏ - Wiley Online Library
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 …

A comprehensive review of bio-inspired optimization algorithms including applications in microelectronics and nanophotonics

Z Jakšić, S Devi, O Jakšić, K Guha - Biomimetics, 2023‏ - mdpi.com
The application of artificial intelligence in everyday life is becoming all-pervasive and
unavoidable. Within that vast field, a special place belongs to biomimetic/bio-inspired …

Review on ensemble meta-heuristics and reinforcement learning for manufacturing scheduling problems

Y Fu, Y Wang, K Gao, M Huang - Computers and Electrical Engineering, 2024‏ - Elsevier
With the development of Artificial Intelligence, Internet of Things and Big Data, intelligent
manufacturing has become a new and popular trend in manufacturing industries …

MGSFformer: A multi-granularity spatiotemporal fusion transformer for air quality prediction

C Yu, F Wang, Y Wang, Z Shao, T Sun, D Yao, Y Xu - Information Fusion, 2025‏ - Elsevier
Air quality spatiotemporal prediction can provide technical support for environmental
governance and sustainable city development. As a classic multi-source spatiotemporal …

A memory-guided Jaya algorithm to solve multi-objective optimal power flow integrating renewable energy sources.

M Ahmadipour, Z Ali, VK Ramachandaramurthy… - Applied Soft …, 2024‏ - Elsevier
The traditional optimal power flow problem (OPF) usually centers on thermal generators,
which have limited fuel for power generation, while emissions from the network system are …

A novel adaptive algorithm of particle swarm optimization based on the human social learning intelligence

E Jiyue, J Liu, Z Wan - Swarm and Evolutionary Computation, 2023‏ - Elsevier
A novel adaptive algorithm of particle swarm optimization is proposed in this paper, where
the learning strategy is designed by simulating features of human social learning …

Dam**-assisted evolutionary swarm intelligence for industrial iot task scheduling in cloud computing

AG Gad, EH Houssein, MC Zhou… - IEEE Internet of …, 2023‏ - ieeexplore.ieee.org
Advancements in the Industrial Internet of Things (IIoT) have yielded massive volumes of
data, taxing the capabilities of cloud computing infrastructure. Allocating limited computing …

Choice of benchmark optimization problems does matter

AP Piotrowski, JJ Napiorkowski… - Swarm and Evolutionary …, 2023‏ - Elsevier
Various benchmark sets have already been proposed to facilitate comparison between
metaheuristics, or Evolutionary Algorithms. During the competition, typically algorithms are …

[HTML][HTML] A comparative analysis of global optimization algorithms for surface electromyographic signal onset detection

S Alam, X Zhao, IK Niazi, MS Ayub, MA Khan - Decision Analytics Journal, 2023‏ - Elsevier
Surface Electromyography (sEMG) is a technique for measuring muscle activity by recording
electrical signals from the surface of the body. It is widely used in fields such as medical …

Metaheuristics should be tested on large benchmark set with various numbers of function evaluations

AP Piotrowski, JJ Napiorkowski… - Swarm and Evolutionary …, 2025‏ - Elsevier
Numerical metaheuristics are often tested on mathematical problems collected into a
benchmark set. There are many benchmark sets, but the number of problems in a particular …