Fusion k-means clustering and multi-head self-attention mechanism for a multivariate time prediction model with feature selection DOI
Mingwei Cai, Xueling Ma, Chao Zhang

и другие.

International Journal of Machine Learning and Cybernetics, Год журнала: 2024, Номер unknown

Опубликована: Дек. 12, 2024

Язык: Английский

Specific surface area (SSA) of perovskites with uncertainty estimation approach DOI Creative Commons
Zied Hosni, Sofiene Achour,

Fatma Saâdi

и другие.

Computational Materials Science, Год журнала: 2025, Номер 249, С. 113668 - 113668

Опубликована: Янв. 9, 2025

Язык: Английский

Процитировано

1
A new multivariate decomposition-ensemble approach with denoised neighborhood rough set for stock price forecasting over time-series information system DOI
Juncheng Bai, Bingzhen Sun,

Yuqi Guo

и другие.

Applied Intelligence, Год журнала: 2025, Номер 55(4)

Опубликована: Янв. 9, 2025

Язык: Английский

Процитировано

0
Hybrid experimental design methodology for non-destructive transfer of industrial-scale frozen sand molds: an improved response surface approach with engineering validation DOI

Benfengnian Dong,

Hu Wu,

Wu Binglin

и другие.

The International Journal of Advanced Manufacturing Technology, Год журнала: 2025, Номер unknown

Опубликована: Март 15, 2025

Язык: Английский

Процитировано

0
Short-term multi-site solar irradiance prediction with dynamic-graph-convolution-based spatial-temporal correlation capturing DOI
Haixiang Zang, Wentao Li, Lilin Cheng

и другие.

Renewable Energy, Год журнала: 2025, Номер unknown, С. 122945 - 122945

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

0
An Enhanced Tunicate Swarm Algorithm with Symmetric Cooperative Swarms for Training Feedforward Neural Networks DOI Open Access

Chengtao Du,

Jinzhong Zhang

Symmetry, Год журнала: 2024, Номер 16(7), С. 866 - 866

Опубликована: Июль 8, 2024

The input layer, hidden and output layer are three models of neural processors that comprise feedforward networks. In this paper, an enhanced tunicate swarm algorithm based on a differential sequencing alteration operator (ETSA) with symmetric cooperative swarms is presented to train objective accomplish minimum classification errors the most appropriate network layout by regulating layers’ connection weights neurons’ deviation thresholds according transmission error between anticipated authentic output. TSA mimics jet motorization scavenging mitigate directional collisions maintain greatest solution customized regional. However, exhibits disadvantages low computational accuracy, slow convergence speed, easy search stagnation. has adaptable localized extraction screening broaden identification scope, enrich population creativity, expedite computation productivity, avoid ETSA integrates exploration exploitation stagnation, which sufficient stability flexibility acquire finest solution. was distinguished from ETTAO, EPSA, SABO, SAO, EWWPA, YDSE, monitoring seventeen alternative datasets. experimental results confirm maintains profound sustainability durability exaggerated convergence, locate acceptable error, equalize prospection yield faster superior calculation greater categorization accuracy.

Язык: Английский

Процитировано

2
Fuzzy Neural Network Applications in Biomass Gasification and Pyrolysis for Biofuel Production: A Review DOI Creative Commons
V V Bukhtoyarov, В С Тынченко, K A Bashmur

и другие.

Energies, Год журнала: 2024, Номер 18(1), С. 16 - 16

Опубликована: Дек. 24, 2024

The increasing demand for sustainable energy has spurred interest in biofuels as a renewable alternative to fossil fuels. Biomass gasification and pyrolysis are two prominent thermochemical conversion processes biofuel production. While these effective, they often influenced by complex, nonlinear, uncertain factors, making optimization prediction challenging. This study highlights the application of fuzzy neural networks (FNNs)—a hybrid approach that integrates strengths logic networks—as novel tool address challenges. Unlike traditional methods, FNNs offer enhanced adaptability accuracy modeling nonlinear systems, them uniquely suited biomass processes. review not only ability optimize predict performance but also identifies their role advancing decision-making frameworks. Key challenges, benefits, future research opportunities explored, showcasing transformative potential

Язык: Английский

Процитировано

1
DSGN: Log-Based Anomaly Diagnosis with Dynamic Semantic Gate Networks DOI

Haitian Yang,

Degang Sun,

Yan Wang

и другие.

Information Sciences, Год журнала: 2024, Номер 680, С. 121174 - 121174

Опубликована: Июль 11, 2024

Язык: Английский

Процитировано

0
Optimization of the cruising speed for high-speed trains to reduce energy consumed by motion resistances DOI

Fang-Ru Zhou,

Kai Zhou, Duo Zhang

и другие.

Applied Energy, Год журнала: 2024, Номер 374, С. 124039 - 124039

Опубликована: Авг. 1, 2024

Язык: Английский

Процитировано

0
VTNet: A multi-domain information fusion model for long-term multi-variate time series forecasting with application in irrigation water level DOI
Rui Dai, Zheng Wang, Wanliang Wang

и другие.

Applied Soft Computing, Год журнала: 2024, Номер 167, С. 112251 - 112251

Опубликована: Сен. 17, 2024

Язык: Английский

Процитировано

0
Fusion k-means clustering and multi-head self-attention mechanism for a multivariate time prediction model with feature selection DOI
Mingwei Cai, Xueling Ma, Chao Zhang

и другие.

International Journal of Machine Learning and Cybernetics, Год журнала: 2024, Номер unknown

Опубликована: Дек. 12, 2024

Язык: Английский

Процитировано

0