3results about How to "Reduce delay" patented technology

The application discloses a kind of ship in and out port scheduling method considering tidal constraint, which comprises the following steps: 1) according to the real-time water depth of channel and the draft of ship, the tidal window of ship is obtained, to ensure that the bottom of ship keeps a safe gap from the bottom of channel;2) obtain the berthing time window and the departure time window of ship;3) establish scheduling optimization model;4) set constraint condition to model;5) model solution, and scheduling is carried out according to the solution result.This application considers tidal constraint and tidal current constraint simultaneously, proposes a mixed linear integer programming model, which considers the change of tidal level and the specific influence of tidal current on ship berthing and departure, and the proposed model and constraint can obtain scheduling scheme under the premise of meeting safety requirements, reduce the overall delay time of ship, and effectively improve the efficiency of port scheduling.

The invention discloses a traffic signal control method based on machine visual perception and space-time sequence prediction, and relates to the technical field of intelligent traffic signal control. The traffic signal control method based on machine vision perception and time-space sequence prediction comprises the following steps: S1, machine vision perception: acquiring real-time image data of a traffic intersection through image acquisition equipment, preprocessing the image data, and extracting traffic flow key parameters; and S2, space-time sequence prediction: constructing a PCA-LSTM traffic flow prediction model based on principal component analysis PCA and a long short-term memory neural network LSTM, inputting the preprocessed traffic flow historical data, and outputting a short-term traffic flow prediction result. The traffic signal control method based on machine visual perception and time-space sequence prediction is comprehensive in data coverage and low in acquisition cost; and the prediction performance is better: through abnormal data processing and dynamic principal component selection of the PCA-LSTM model, the prediction precision is improved by 2%-5% compared with the traditional LSTM, and the calculation efficiency is improved by 15.01%.

This utility model discloses an elevator guide shoe wear detection mechanical probe assembly, including a detection mechanical probe body with a guide shoe threadedly fixed to its lower end and rubber pads fixed to three sides of the inner side of the guide shoe; a prediction component, which includes a connecting block welded to one end of the detection mechanical probe body, rectangular grooves symmetrically opened on both sides of one side of the connecting block, a threaded hole in the middle section of the rectangular groove, a detection probe threadedly fixed to the middle section of the connecting block, and an observation ruler threadedly fixed in the rectangular groove; and a reminder component, which includes a central fixing block fixed to one side of the upper end of the rubber pad, a torsion spring fitted inside the fixing block, and rotating blocks fixed to both ends of the torsion spring. This utility model, through its prediction component, can quickly and intuitively detect whether the elevator guide shoe is misaligned or tilted, causing the detection mechanical probe to malfunction, thus improving maintenance efficiency, enhancing safety performance, and preventing personal injury.