AIMC Topic: Altitude

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Predictive hybrid model of a grid-connected photovoltaic system with DC-DC converters under extreme altitude conditions at 3800 meters above sea level.

PloS one May 19, 2025
This study aims to develop a predictive hybrid model for a grid-connected PV system with DC-DC optimizers, designed to operate in extreme altitude conditions at 3800 m above sea level. This approach seeks to address the "curse of dimensionality" by r...
Algorithms Models, Theoretical Altitude Electric Power Supplies Bayes Theorem Solar Energy
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Understanding land degradation induced by gully erosion from the perspective of different geoenvironmental factors.

Journal of environmental management Apr 29, 2022
Complex interrelationships between landscape-level geoenvironmental factors and natural phenomena have rendered land degradation control measures ineffective. For control to be effective, this study argues that the interactions between different geoe...
ROC Curve Bayes Theorem Machine Learning Retrospective Studies Altitude
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Identifying the Branch of Kiwifruit Based on Unmanned Aerial Vehicle (UAV) Images Using Deep Learning Method.

Sensors (Basel, Switzerland) Jun 29, 2021
It is important to obtain accurate information about kiwifruit vines to monitoring their physiological states and undertake precise orchard operations. However, because vines are small and cling to trellises, and have branches laying on the ground, n...
Deep Learning Remote Sensing Technology Fruit Altitude Machine Learning
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Dual-sensor fusion based attitude holding of a fin-actuated robotic fish.

Bioinspiration & biomimetics May 13, 2020
In nature, the lateral line system (LLS) is a critical sensor organ of fish for rheotaxis in complex environments. Inspired by the LLS, numbers of artificial lateral line systems (ALLSs) have been designed to the fish-like robots for flow field perce...
Animal Fins Biomimetic Materials Equipment Design Animals Fishes Robotics Signal-To-Noise Ratio Neural Networks, Computer Altitude Computer Simulation
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Artificial intelligence reveals environmental constraints on colour diversity in insects.

Nature communications Oct 7, 2019
Explaining colour variation among animals at broad geographic scales remains challenging. Here we demonstrate how deep learning-a form of artificial intelligence-can reveal subtle but robust patterns of colour feature variation along an ecological gr...
Altitude Species Specificity Skin Pigmentation Moths Insecta Temperature Climate Animals Genetic Variation Artificial Intelligence Color Phylogeny Biodiversity Deep Learning
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Comparison of mixing layer height inversion algorithms using lidar and a pollution case study in Baoding, China.

Journal of environmental sciences (China) Nov 15, 2018
Beijing-Tianjin-Hebei area is suffering from atmospheric pollution from a long time. The understanding of the air pollution mechanism is of great importance for officials to design strategies for the environmental governance. Mixing layer height (MLH...
Remote Sensing Technology Air Pollution Air Movements Altitude Algorithms China Environmental Monitoring
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[Multi-factor Impact Analysis of Grassland Phenology Changes on the Qinghai-Xizang Plateau Based on Interpretable Machine Learning].

Huan jing ke xue= Huanjing kexue Jun 8, 2024
The vegetation phenology of the Qinghai-Xizang Plateau is changing significantly in the context of climate change. However, there are many hydrothermal factors affecting the phenology, and few studies have focused on the effects of multiple factors o...
Temperature Soil Machine Learning Grassland Seasons Rain Poaceae Climate Change Altitude Environmental Monitoring Remote Sensing Technology China
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