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35results about How to "Maximize weight" patented technology

Horizontal automatic filling device and method for large pressure-resistant structure model

A horizontal automatic filling device for a large pressure-resistant structure model comprises an equipment foundation, a plurality of foundation embedded plates are embedded in the upper surface of the equipment foundation through foundation bolts, an automatic filling device body is installed on the foundation embedded plates through fasteners, and the automatic filling device body is in butt joint with a horizontal type pressure cylinder body. A pressure-resistant structure model is placed on the automatic filling device, a cylinder cap supporting vehicle is further installed on the upper surface of the equipment foundation through a sliding mechanism, and a cylinder cap is installed on the cylinder cap supporting vehicle. The device further comprises a hoop opening and closing mechanism, the hoop opening and closing mechanism is installed at the end of the horizontal pressure cylinder body, and the hoop opening and closing mechanism controls the cylinder cap to be attached to or separated from the horizontal pressure cylinder body. The characteristics of large size, heavy weight and long transfer distance of a large-scale pressure-resistant structure test model are met, and meanwhile, the automatic degree is relatively high and the working reliability is good.
Owner:CHINA SHIP SCIENTIFIC RESEARCH CENTER (THE 702 INSTITUTE OF CHINA SHIPBUILDING INDUSTRY CORPORATION)

Novel reinforcement learning method based on grid user position automatic antenna parameter adjustment

The invention discloses a novel reinforcement learning method based on grid user position automatic antenna parameter adjustment. The method is used for a double-layer heterogeneous cellular network comprising a plurality of macro base stations, micro base stations and a plurality of macro users. In order to enable a plurality of users moving at a high speed in a complex network environment to always maintain a high weighted sum rate, the invention provides the novel reinforcement learning method based on grid user position automatic antenna parameter adjustment. The method comprises the following two steps: (1) in an offline modeling stage, achieving the biggest advantage that the time overhead and the calculation complexity during online learning can be reduced; and (2) in an online learning stage, based on the real-time SINR value fed back by a user, providing antenna parameter configuration capable of maximizing the weighted sum rate R of the user by using the provided novel reinforcement learning method. Compared with a traditional method, the method provided by the invention has the advantages that the applicable scene is closer to the current network condition and the reinforced learning has a good effect on time sequence prediction, and meanwhile, the method based on the grid user position has better expansibility.
Owner:BEIJING UNIV OF POSTS & TELECOMM
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