KEYWORDS: Data centers, Cooling systems, Information technology, Data modeling, Energy efficiency, Power consumption, Mathematical optimization, Control systems, Systems modeling, Education and training
As an essential support for technology applications such as cloud computing and artificial intelligence, data centers face a pressing need to balance their demand with their own high energy consumption. Since the energy consumption of the Information Technology (IT) systems and cooling systems accounts for the majority of total energy consumption in data centers, a collaborative optimization framework called COHPPO based on a Hybrid Proximal Policy Optimization algorithm (HPPO) is proposed, which controls IT system and cooling system in a coordinated manner, fully compressing the resource redundancy of the IT system and cooling redundancy of the cooling system. The HPPO algorithm is trained and verified using a task dataset and a simulation platform that simulates the environmental state inside the data center. The experimental results demonstrate that the COHPPO collaborative optimization framework proposed in this paper can effectively improve the energy efficiency of the data center and the stability of its internal environment.
This paper presents a novel approach that utilizes airborne LiDAR point cloud data to reconstruct the growth of individual eucalyptus trees in a forest. Firstly, the point cloud data is preprocessed using specialized software to separate the land and eucalyptus forest vegetation canopy surfaces. Next, a single tree feature matching algorithm is employed to isolate a single eucalyptus tree. The single tree forest is then segmented on an elevation projection image, which enables accurate calculation of the plane coordinates, tree height, and crown diameter, ultimately resulting in the position modeling of each tree. Using the single tree model, the biomass of each tree is estimated through its growth equation. This method provides a visual simulation of the laser point clouds of single tree morphology to the overall forest, which allows for the estimation of the aboveground biomass of eucalyptus forests. The research results are expected to provide technical support for estimating the carbon storage of eucalyptus forests in the region. Overall, this approach offers a valuable tool for forest management and carbon accounting, which can help to promote sustainable forestry practices.
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