Zili Xiong

ORCID: 0009-0007-9865-2849
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About
Contact & Profiles
Research Areas
  • Atmospheric and Environmental Gas Dynamics
  • Remote Sensing in Agriculture
  • Fire effects on ecosystems
  • Hydrology and Drought Analysis
  • Power Systems and Technologies
  • Environmental and Agricultural Sciences
  • Soil Moisture and Remote Sensing
  • Silicon Carbide Semiconductor Technologies
  • Software-Defined Networks and 5G
  • Rangeland and Wildlife Management
  • Ecology and Vegetation Dynamics Studies
  • Cloud Computing and Resource Management
  • Evaluation Methods in Various Fields
  • Multilevel Inverters and Converters
  • Advanced DC-DC Converters
  • Water Resources and Management
  • Plant Water Relations and Carbon Dynamics
  • Advanced Measurement and Detection Methods
  • Climate variability and models
  • Caching and Content Delivery
  • Advanced Sensor and Control Systems
  • Flood Risk Assessment and Management
  • Research studies in Vietnam
  • Cryospheric studies and observations
  • Advanced Computational Techniques and Applications

Hubei University of Technology
2024

Beijing Institute of Petrochemical Technology
2024

Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou)
2021-2023

Sun Yat-sen University
2021-2023

Huazhong Agricultural University
2023

Huazhong University of Science and Technology
2011

Changjiang Water Resources Commission
2010

It is important to accurately assess agricultural drought because of its harmful impacts on the ecosystem and economy. Soil moisture reanalysis datasets provide an way drought. In this study, ERA5-Land surface subsurface soil was used estimate water deficit index (SWDI) in four southern provinces China. The dataset evaluated with situ observations from agrometeorological stations. Agricultural assessed for three climate zones at a weekly scale 2017 2019 compared atmospheric (AWD). found that...

10.3390/agriculture11050411 article EN cc-by Agriculture 2021-05-03

Global carbon fluxes describe the exchange between land and atmosphere. However, already available global datasets have not been adjusted by site data deep learning tools. In this work, a dataset (named as GCFD) of gross primary productivity (GPP), terrestrial ecosystem respiration (RECO), net (NEE) has developed via based convolutional neural network (CNN) model. The spatial resolution 1 km at three time steps per month from January 1999 to June 2020. Flux measurements were used training...

10.3390/f14050913 article EN Forests 2023-04-28

Cloud computing is a novel pattern, and it can provide underlying hardware resource for cloud users on demand. Virtualization the key technology of computing, provides technical support computing. In platform, power management an indispensable function system administration. Based genetic algorithm, this paper proposes method based virtual cluster. The experiments Xen platform prove effectiveness our method.

10.1109/itap.2011.6006323 article EN International Conference on Internet Technology and Applications 2011-08-01

This research tackles the constraints inherent in current global carbon flux datasets and introduces a groundbreaking new dataset, Global Carbon Fluxes Dataset (GCFD), which integrates cutting-edge deep learning methodologies alongside situ measurements. GCFD delivers unprecedented high-resolution spatial temporal data on Gross Primary Productivity (GPP), Terrestrial Ecosystem Respiration (RECO), Net Exchange (NEE). The Convolutional Neural Network (CNN) model employed this study surpasses...

10.5194/egusphere-egu24-2662 preprint EN 2024-03-08

ABSTRACT With the rapid development of automotive infotainment, industrial DC‐DC motors and telecom servers, demand for buck converters with high‐input or wide‐input voltage is increased. This paper proposes a synchronous converter wide input range, utilizing simulated peak current mode. The proposed control mode removes need separate slope compensation circuit. By integrating directly into ramp generator, it eliminates subharmonic oscillation issues when duty cycle in exceeds 50%, thereby...

10.1002/cta.4410 article EN other-oa International Journal of Circuit Theory and Applications 2024-12-18

Land carbon fluxes play a critical role in ecosystems, and acquiring comprehensive global database of is essential for understanding the Earth’s cycle. The primary methods obtaining spatial distribution land include utilizing machine learning models based on situ measurements, estimating through satellite remote sensing, simulating ecosystem models. Recently, an innovative product known as Global Carbon Flux Dataset (GCFD) has been released. In this study, we assessed reliability GCFD by...

10.3390/cli11100205 article EN Climate 2023-10-11
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