Zhenwei Li

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Articles

Continuous Straw Returning Combined with Nitrogen Application Improve Soil Properties and Yield of Double Cropping Maize in Subtropical Regions

Jun 20, 2024 | mdpi.com | Zhenwei Li |Kashif Khan |Yanqiong Pan |Xunbo Zhou

All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
Dynamic Analysis of a Delayed Differential Equation for Ips subelongatus Motschulsky-Larix spp.

Apr 1, 2024 | mdpi.com | Zhenwei Li |Yuting Ding

1. IntroductionAt present, the issue of the greenhouse effect has received widespread attention worldwide. Human activities release a significant amount of greenhouse gases, with CO2 being the most crucial among them, as it increasingly traps solar heat and warms the global climate. Forests have been identified as a major leverage for climate change mitigation because of their capacity to fix atmospheric CO2 and transform it into organic carbon, in biomass and then in soils [1].
An Adaptive INS/CNS/SMN Integrated Navigation Algorithm in Sea Area

Feb 6, 2024 | mdpi.com | Shun Yao |Zhenwei Li |Zhaoxu Tian |Yongmei Cheng

1. IntroductionThe inertial navigation system (INS) is an autonomous navigation system that operates independently of external information, offering the advantages of discreet operation and robust anti-interference capabilities. However, a notable drawback of INS is the rapid accumulation of errors over time, making it challenging to rely on for prolonged and highly precise navigation [1,2,3,4,5].
A Multi Brain Tumor Region Segmentation Model Based on 3D U-Net

Aug 15, 2023 | mdpi.com | Zhenwei Li |Xiaoqin Wu |Xiaoli Yang

4.4. Results and DiscussionAll experiments in this paper were conducted in the same training environment configuration: AMD 5950X, CPU 64GB RAM, and NVIDIA GeForce RTX3090 24G GPU. PyTorch1.12 framework and Anaconda Python3.7 interpreter built the network framework. The weight decay is 1 × 10−4; the total epoch is 100 times; the initial learning rate is 3 × 10−4; the batch size is 4; and the activation function is Softmax.