Reset
Showing 20 of 817 academic articles

IWORMLF: Improved Invasive Weed Optimization With Random Mutation and Lévy Flight for Beam Pattern Optimizations of Linear and Circular Antenna Arrays

Tingting Zheng, Yanheng Liu, Geng Sun, Lin Zhang et al. • IEEE Access (2020)

The beam pattern synthesis of antenna arrays is one of the most significant optimization problems in the electromagnetics community, and it affects the performance of wireless communication systems. In this article, we formulate the beam pa...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2020.2968476

Optimal Trend Labeling in Financial Time Series

Tomislav Kovacevic, Andro Mercep, Stjepan Begusic, Zvonko Kostanjcar • IEEE Access (2023)

Predicting asset price trends is often posed as a classification problem, where trends are classified as positive or negative. Since asset price series are noisy and volatile, it is difficult to distinguish true trends from short-term fluct...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2023.3303283

Deep neural network-based prediction of tsunami wave attenuation by mangrove forests

Didit Adytia, Dede Tarwidi, Deni Saepudin, Semeidi Husrin et al. • MethodsX (2024)

The goal of this research is to develop a model employing deep neural networks (DNNs) to predict the effectiveness of mangrove forests in attenuating the impact of tsunami waves. The dataset for the DNN model is obtained by simulating tsuna...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.mex.2024.102791

Comparing Large-Eddy Simulation and Gaussian Plume Model to Sensor Measurements of an Urban Smoke Plume

Dominic Clements, Matthew Coburn, Simon J. Cox, Florentin M. J. Bulot et al. • Atmosphere (2024)

The fast prediction of the extent and impact of accidental air pollution releases is important to enable a quick and informed response, especially in cities. Despite this importance, only a small number of case studies are available studyin...

DOAJ Open Access (DOAJ) DOI: 10.3390/atmos15091089

BFLP: blockchain-based federated learning protocol with verifiable contribution proof

Xi Li, Yibei Wang, Bin Wen • Journal of King Saud University: Computer and Information Sciences (2026)

Abstract Cross-institutional federated learning suffers from centralized trust fragility, poisoning attacks, and the lack of verifiable contribution-based incentives. This paper proposes BFLP, a blockchain-based federated learning protocol ...

DOAJ Open Access (DOAJ) DOI: 10.1007/s44443-026-01162-y