33 results about "Adaptive planning" patented technology

A method for planning a transportation service includes sending transportation proposal to a plurality of organizations. The proposal includes one or more initial options, each including a set of variable parameters. Each organization can generate a modified option and make a commitment conditional on selected ones of the parameters. Each organization sends respective modified options to commuters of that organization who may specify their own pledges for at least one of the modified options, conditional on the organization-selected values for the variable parameters and optionally on commuter-selected values for the variable parameters. A cost-benefit function is computed for each of a set of revised options for the transportation service, each of the revised options being based on a combination of the variable parameters for which pledges which cover the combination have been received and one or more of the revised options is identified, based on the computed cost-benefit function.

A system for dynamic localization of medical instruments includes an ultrasound imaging system (110) configured to image a volume where one or more medical instruments are deployed. A registration module (136) registers two images of the one or more medical instruments to compute a transform between the two images, the two images being separated in time. A planning module (142) is configured to have positions of the volume and the one or more medical instruments updated based on the transform and, in turn, update a treatment plan in accordance with the updated positions such that changes in the volume and positions of the one or more medical instruments are accounted for in the updated plan.

The invention relates to an intelligent control method based on adaptive planning of a virtual ship for an under-drive unmanned ship formation. The method comprises the following steps of 1, setting aformation and initializing parameters; 2, collecting a position coordinate (xL, yL) and a heading angle psiL of a leader ship, conducting wave filtering, and transmitting the position coordinate andthe heading angle to a following ship; 3, according to the formation, the position coordinate and the heading angle information of the leader ship, obtaining a reference position (xr, yr) and a reference motion posture psir of the following ship in the formation in real time; 4, introducing the virtual ship and conducting real-time adaptive planning to obtain a reference track of the following ship; 5, using a combination strategy of RBF neural networks and a minimum parameter learning algorithm to train learning parameters online to generate intelligent formation control signals, wherein theintelligent formation control signals include the rotating speed nF of a mainframe of the following ship and a rudder angle command signal deltaF. Compared with the prior art, the method has the advantages that the method adapts to curved path tasks, overhead is avoided, leader ship speed information is not needed, and the method is simple, convenient and excellent in real-time performance.

The invention discloses a self-adaptive planning method for an atmosphere entrance guidance trajectory. The method comprises the following steps: (1) acquiring a change rule of a flight longitudinal range and a cross range along with a heeling angle; (2) sectioning a whole entrance process, and determining a guidance law of each stage; (3) setting different entrance point initial longitudinal ranges, judging whether parachute-opening states in different entrance points satisfy given constraints, if so, positively increasing the initial longitudinal range or negatively decreasing the initial cross range, until a certain constraint is not satisfied, and determining a limit range of the initial longitudinal range which can be adjusted by the above guidance law; (4) in a actual flight process,judging whether the initial entrance point longitudinal range is within the above limit range, if so, using the guidance law in the step (2) to control; if not, executing the step (5); and (5) calculating a deviation value of the actual initial longitudinal range exceeding the limit range, correcting a longitudinal range reference value of a reference ground track, and substituting a corrected value into the guidance law in the step (2), to obtain a new guidance law, and using the new guidance law to control.

The invention provides a method and system for adaptive planning of port routes and berths. The berth positioning data set is acquired, the ship's positioning coordinates are collected, and the remaining time of berthing is obtained. Based on the berth positioning data set and the remaining time of berthing, the self-adaptive planning is calculated. The planning matrix searches the adaptive planning matrix to obtain the digital path and the digital berth corresponding to the digital path, realizes the rapid adaptive arrangement of the path composed of multiple berths, and automatically plans according to the expected occupancy time of the berth and the position coordinates of the berth The optimal route for ships to enter the berth achieves the beneficial results of saving berth route planning time and improving berth utilization efficiency.

The invention relates to an intelligent virtual network path planning method for large-scale container clusters. After extracting the interface information, the entire network information is sensed, and the topology information is reconstructed; traffic statistics are performed on switches; After the statistics, the corresponding flow table information is automatically extracted to obtain two types of features including the number of inbound bytes of port traffic and the number of outbound bytes of port traffic, and two types of self-built features are constructed, namely, the inflow rate of port traffic and the outflow rate of port traffic. Normalize the input features, and obtain the traffic prediction model after training; use the traffic prediction model to predict the port traffic of the switch in a fixed time period in the future according to different tasks, and compare the prediction result with the threshold value to the corresponding switch Perform sleep / start operation; carry out adaptive planning according to the characteristics of the task; execute the action strategy to be taken.