4 results about "Cross-training" patented technology

A method of compiling workout information in a workout session includes, at a workout server, receiving, via a network, first login information from a first exercise device; receiving, via the network, first workout information from the first exercise device; recording the first workout information in an active workout session; receiving, via the network, second login information from a second exercise device; receiving, via the network, second workout information from the second exercise device; and recording the second workout information in the active workout session.

The utility model discloses an adjustable cross fork training device which comprises a height adjusting assembly, the lower end of a fixing frame is fixedly arranged on a base, a sliding seat is arranged at the upper end of the fixing frame in a sliding mode, the height adjusting assembly is arranged between the fixing frame and the sliding seat and used for driving the sliding seat to slide, and the sliding seat is connected with the upper end of a circulating pull rod. The lower end of the circulating pull rod is connected with the seat, the seat is slidably arranged on a guide rod, the guide rod is fixedly arranged on the base, adjusting leg rods are hinged to the two sides of the seat, the lower ends of the adjusting leg rods are slidably arranged on the base, and the height adjusting assembly is electrically connected with the control center. And the leg rods can be adjusted to extend and retract under the action of the control center. The height adjusting assembly drives the seat to move up and down, so that cross-fork trainers with different heights and different states can be exercised, and the cross-fork trainers can automatically adjust the cross-fork trainers according to needs without assistance of other people.

The present application relates to the technical field of deep learning, in particular to a novel deep learning method and device based on symmetric cross compound training, which specifically comprises: obtaining first sample data, dividing the first sample data into a first training set, a first validation set and a first test set, and further dividing the first training set into a first data set and a second data set; taking the first data set and the second data set alternately as a training set and a validation set to perform symmetric cross training, obtaining outlier samples and true samples; performing compound training on the outlier samples and the true samples, simultaneously performing output correction classification, and obtaining a first optimal model. The present application changes the traditional deep learning training method mode, uses the function of deep learning feature extraction to automatically identify and separate the outlier samples in the training set, and further improves the model performance.

The present specification relates to the technical field of petrochemical production, and particularly relates to a three-agent use data comprehensive analysis and optimization method, device and equipment. Including: obtaining historical production data of three-agent related materials in a production line, classifying the obtained historical production data according to the categories of the three agents; then establishing the historical production data into multiple data models according to the categories, wherein the data models include: a price ratio model, a cost model and a device model; the data models are subjected to multi-condition constraints according to actual conditions, and an overall optimization model is generated through cross-training, the production demand in actual production is input into the optimization model to generate optimization suggestions, so that the operating personnel can purchase, produce and other processes according to the optimization suggestions. Thus, an optimization model capable of generating an optimization suggestion covering the whole process of three-agent production is realized.