9 Papers
Dong Yan is an academic researcher from Penn State College of Communications. The author has contributed to research in topics: Fitness function & Band-stop filter. The author has an hindex of 1, co-authored 2 publications.
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Papers
HDGS bandstop filter design by FGA
Dong Yan,Xiaoping Zeng,Kai Zhang +2 more
- 01 Nov 2010
TL;DR: A new fuzzy genetic algorithm (FGA) is developed to optimize Hilbert fractal defected ground structure (HDGS), designed bandstop filter, with large stop-band insertion loss and return loss, flat pass-band characteristics.
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Exploring Indoor and Outdoor Residential Factors of High-Density Communities for Promoting the Housing Development
Kai Zhang,Dong Yan +1 more
TL;DR: Wang et al. as mentioned in this paper surveyed the citizens' residential environment and satisfaction in dense urban residential areas to understand the factors impacting residential satisfaction in high-population metropolitan areas and found that 13 environmental factors significantly impact residential evaluation.
Enhancing the Community Environment in Populous Residential Districts: Neighborhood Amenities and Residents’ Daily Needs
Kai Zhang,Dong Yan +1 more
TL;DR: The accessibility, availability, and appropriateness of amenities in densely populated neighborhoods are crucial for sustainable development and residents’ well-being. The study finds a high density of amenities in populous areas and their effectiveness in meeting residents' daily needs.
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Optimization and Tradeoff of DC Bus Voltage Ripple and DAB Current Stress in Two-Stage Single-Phase Converter by Double-Line-Frequency Power Control
Fei Xiong,Peng Wu,Hongyu. Yang,Kai Bi Zhang,Dong Yan +4 more
TL;DR: The proposed double-line-frequency power control method optimizes and trades off the DC bus voltage ripple and DAB current stress in two-stage single-phase converters by finding the optimal double-line-frequency power.
3
Design of Charging Station Load Forecasting Model Based on Image Classification
Dong Yan,Chuangliang Zhao,Bin Zhu,Kai Zhang,Jiuyuan Zhan +4 more
- 17 Nov 2023
TL;DR: Design of a charging station load forecasting model based on image classification accurately predicts charging station load by combining RF-BIRCH, CNN-LSTM, and Bi-LSTM.
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