Abstract: This application discloses a placement location obtaining method, a model training method, and a related device. The method includes: obtaining first size information of an unoccupied area in an accommodation space and second size information of a first object; generating M candidate placement locations based on the first size information and N pieces of second size information, where one candidate placement location indicates one placement location of one determined first object in the unoccupied area; generating a first score value of each candidate placement location based on the first size information by using a first machine learning model; and selecting a first placement location from the M candidate placement locations based on the first score value. This avoids excessive dependence on experience of a technical person, and improves an automation level and efficiency of placing/loading an object in the warehousing and/or logistics field.

Abstract: The present disclosure relates to item separation methods. One example method includes receiving a to-be-processed order, where the to-be-processed order includes a type of a to-be-separated item and a quantity of to-be-separated items, and obtaining a separation configuration of the to-be-processed order based on the to-be-processed order and a separation configuration of a historical order included in a separation database, where the separation configuration of the to-be-processed order includes a type of a box for packing the to-be-separated item and a first quantity of boxes, and the separation configuration of the historical order includes a type of an item, a quantity of items, a type of a box for packing the item, and a second quantity of boxes.

Abstract: A terminal positioning method and a network device, where the network device obtains radio signal sampling information of a first terminal at a current moment. The first terminal is any terminal in a target region, and the target region is a preset geographic region. The network device obtains position information of the first terminal at the current moment by prediction based on the radio signal sampling information of the first terminal at the current moment and a predictive model of the target region. The predictive model is obtained by extensive data training in the target region, has relatively strong error tolerance and error-correction capabilities, and can accurately reflect a relationship between radio signal sampling information and position information of a terminal. Terminal positioning accuracy is effectively improved.

Abstract: A terminal positioning method and a network device, where the network device obtains radio signal sampling information of a first terminal at a current moment. The first terminal is any terminal in a target region, and the target region is a preset geographic region. The network device obtains position information of the first terminal at the current moment by prediction based on the radio signal sampling information of the first terminal at the current moment and a predictive model of the target region. The predictive model is obtained by extensive data training in the target region, has relatively strong error tolerance and error-correction capabilities, and can accurately reflect a relationship between radio signal sampling information and position information of a terminal. Terminal positioning accuracy is effectively improved.