Dynamic Analysis of User Requirements Based on Natural Language Processing DOI

Minglong Song,

Ke Zhang, Xuan Wu

et al.

Published: Aug. 16, 2024

Language: Английский

Kansei engineering for the intelligent connected vehicle functions: An online and offline data mining approach DOI
Xinjun Lai,

Shenhe Lin,

Jingkai Zou

et al.

Advanced Engineering Informatics, Journal Year: 2024, Volume and Issue: 61, P. 102467 - 102467

Published: March 13, 2024

Language: Английский

Citations

14
MOX-NET: Multi-stage deep hybrid feature fusion and selection framework for monkeypox classification DOI
Sarmad Maqsood, Robertas Damaševičius, Sana Shahid

et al.

Expert Systems with Applications, Journal Year: 2024, Volume and Issue: 255, P. 124584 - 124584

Published: June 26, 2024

Language: Английский

Citations

13
Towards smart product-service systems 2.0: A retrospect and prospect DOI
Mengyang Ren, Pai Zheng

Advanced Engineering Informatics, Journal Year: 2024, Volume and Issue: 61, P. 102466 - 102466

Published: March 11, 2024

Language: Английский

Citations

11
UNISON framework of data-driven tripartite evolutionary game-based knowledge sharing decision for digital servitization DOI
Kuo‐Yi Lin, Li Hu, Ke Zhang

et al.

Computers & Industrial Engineering, Journal Year: 2024, Volume and Issue: 189, P. 109935 - 109935

Published: Feb. 2, 2024

Language: Английский

Citations

9
Research on multimodal generative design of product appearance based on emotional and functional constraints DOI
Zeng Wang, Jiangshan Li,

Hui-ru Pan

et al.

Advanced Engineering Informatics, Journal Year: 2025, Volume and Issue: 65, P. 103106 - 103106

Published: Jan. 15, 2025

Language: Английский

Citations

1
A data-driven design parameter recommendation approach based on personalized requirements for product conceptual design DOI
Haoran Cui, Lin Gong, Yan Yan

et al.

Computers & Industrial Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 110885 - 110885

Published: Jan. 1, 2025

Language: Английский

Citations

1
A Method for the Front-End Design of Electric SUVs Integrating Kansei Engineering and the Seagull Optimization Algorithm DOI Open Access
Yutong Zhang,

Jiantao Wu,

Li Sun

et al.

Electronics, Journal Year: 2025, Volume and Issue: 14(8), P. 1641 - 1641

Published: April 18, 2025

With the rapid expansion of Electric Sport Utility Vehicle (ESUV) market, capturing consumer aesthetic preferences and emotional needs through front-end styling has become a key issue in automotive design. However, traditional Kansei Engineering (KE) approaches suffer from limited timeliness, subjectivity, low predictive accuracy when extracting affective vocabulary modeling nonlinear relationship between product form imagery. To address these challenges, this study proposes an improved KE-based ESUV framework that integrates data mining, machine learning, generative AI. First, real reviews samples are collected via Python-based web scraping. Next, Biterm Topic Model (BTM) Analytic Hierarchy Process (AHP) used to extract representative vocabulary. Subsequently, Back Propagation Neural Network (BPNN) Support Vector Regression (SVR) models constructed optimized using Seagull Optimization Algorithm (SOA) Particle Swarm (PSO). Experimental results show SOA-BPNN achieves superior accuracy. Finally, Stable Diffusion is applied generate design schemes, optimal model employed evaluate their The proposed offers systematic data-driven approach for predicting responses conceptual stage, effectively addressing limitations conventional experience-based Thus, both methodological innovation practical guidance integrating into

Language: Английский

Citations

1
Quantifying risk of service failure in customer complaints: A textual analysis-based approach DOI
Wenyan Song, Rong Wan,

Yuqi Tang

et al.

Advanced Engineering Informatics, Journal Year: 2024, Volume and Issue: 60, P. 102377 - 102377

Published: Feb. 1, 2024

Language: Английский

Citations

8
Identifying pharmaceutical technology opportunities from the perspective of adverse drug reactions: Machine learning in multilayer networks DOI
Weiyu Zhao, Lijie Feng, Yicheng Feng

et al.

Technological Forecasting and Social Change, Journal Year: 2024, Volume and Issue: 201, P. 123232 - 123232

Published: Feb. 10, 2024

Language: Английский

Citations

8
Tracking and predicting technological knowledge interactions between artificial intelligence and wind power: Multimethod patent analysis DOI
Jinfeng Wang, Lu Cheng, Lijie Feng

et al.

Advanced Engineering Informatics, Journal Year: 2023, Volume and Issue: 58, P. 102177 - 102177

Published: Sept. 27, 2023

Language: Английский

Citations

16