期刊名：Wind

期刊主页: https://www.mdpi.com/journal/wind

1. A Survey of Numerical Simulation Tools for Offshore Wind Turbine Systems

海上风力涡轮机系统数值模拟工具综述

https://www.mdpi.com/2674-032X/4/1/1

Fadaei, S.; Afagh, F.F.; Langlois, R.G. A Survey of Numerical Simulation Tools for Offshore Wind Turbine Systems. Wind 2024, 4, 1-24.

2. An Ensemble Approach to Short-Term Wind Speed Predictions Using Stochastic Methods, Wavelets and Gradient Boosting Decision Trees

基于随机方法、小波分析与梯度提升决策树的短期风速预测集成方法

https://www.mdpi.com/2674-032X/4/1/3

Sivhugwana, K.S.; Ranganai, E. An Ensemble Approach to Short-Term Wind Speed Predictions Using Stochastic Methods, Wavelets and Gradient Boosting Decision Trees. Wind 2024, 4, 44-67.

3. Maximizing Wind Turbine Power Generation Through Adaptive Fuzzy Logic Control for Optimal Efficiency and Performance

通过自适应模糊逻辑控制最大化风力涡轮机发电量，以实现最佳效率和性能

https://www.mdpi.com/2674-032X/5/1/4

Aranizadeh, A.; Mirmozaffari, M.; Khalatabadi Farahani, B. Maximizing Wind Turbine Power Generation Through Adaptive Fuzzy Logic Control for Optimal Efficiency and Performance. Wind 2025, 5, 4.

4. High-Resolution Wind Speed Estimates for the Eastern Mediterranean Basin: A Statistical Comparison Against Coastal Meteorological Observations

东地中海盆地高分辨率风速估算：与沿海气象观测数据的统计比较

https://www.mdpi.com/2674-032X/4/4/16

Hadjipetrou, S.; Kyriakidis, P. High-Resolution Wind Speed Estimates for the Eastern Mediterranean Basin: A Statistical Comparison Against Coastal Meteorological Observations. Wind 2024, 4, 311-341.

5. A Systematic Review of Wind Energy Forecasting Models Based on Deep Neural Networks

基于深度神经网络的风能预测模型的系统综述

https://www.mdpi.com/2674-032X/5/4/29

Manzano, E.A.; Nogales, R.E.; Rios, A. A Systematic Review of Wind Energy Forecasting Models Based on Deep Neural Networks. Wind 2025, 5, 29.

6. Floater Assembly and Turbine Integration Strategy for Floating Offshore Wind Energy: Considerations and Recommendations

浮式海上风能发电系统的浮体组件与涡轮机集成策略：相关考虑与建议

https://www.mdpi.com/2674-032X/4/4/19

Ivanov, G.; Ma, K.-T. Floater Assembly and Turbine Integration Strategy for Floating Offshore Wind Energy: Considerations and Recommendations. Wind 2024, 4, 376-394.

7. Review of Artificial Intelligence-Based Design Optimization of Wind Power Systems

基于人工智能的风力发电系统设计优化综述

https://www.mdpi.com/2674-032X/5/3/18

Jiang, Z.; Li, H.; Yang, H.; Wu, H.; Liu, W.; Chen, Z. Review of Artificial Intelligence-Based Design Optimization of Wind Power Systems. Wind 2025, 5, 18.

8. Green Hydrogen Driven by Wind and Solar—An Australian Case Study

风能与太阳能驱动的绿色氢能——澳大利亚案例研究

https://www.mdpi.com/2674-032X/4/2/6

Currie, G.; Behrens, E.; Bolitho, S.; Coen, M.; Wilson, T. Green Hydrogen Driven by Wind and Solar—An Australian Case Study. Wind 2024, 4, 111-134.

9. Current Status and Sustainable Utilization of Wind Energy Resources in Mexico: A Systematic Review

墨西哥风能资源的现状及可持续利用情况：系统综述

https://www.mdpi.com/2674-032X/5/4/22

Batun, U.C.; Zayed, M.E.; Ghazy, M.; Rehman, S. Current Status and Sustainable Utilization of Wind Energy Resources in Mexico: A Systematic Review. Wind 2025, 5, 22.

10. An Overview of Natural Cooling and Ventilation in Vernacular Architectures

传统建筑中的自然通风与降温概述

https://www.mdpi.com/2674-032X/5/3/21

Salimi, A.; Yurtyapan, A.; Ouria, M.; Turkan, Z.; Pilehvarian, N.K. An Overview of Natural Cooling and Ventilation in Vernacular Architectures. Wind 2025, 5, 21.

Wind 期刊介绍

主编

Prof. Dr. Horia Hangan

安大略理工大學

研究领域：流体力学；湍流；风工程；大气流动；空气动力学；流量控制

Wind (ISSN 2674-032X) 是开放获取期刊，专注于风相关领域的科学研究。期刊目标是为展示与风相关的跨学科领域的最新研究成果提供一个动态的平台，涵盖概念开发、设计工具、工程技术、能源市场、经济学、政策、社会和环境影响以及生态等方面。近日，2025年CiteScore与IF正式发布，期刊最新CiteScore为4.5，IF为2.7，两项核心指标较上一年度均实现稳步提升，反映出期刊在风相关领域的学术关注度与影响力正持续增强。