40 results about "Demand modeling" patented technology

The invention provides a method and a device for analyzing test coverage automatically aiming at an automatic test system. The method for analyzing the test coverage automatically mainly comprises the following steps of: establishing a test demand model through visualization; formulating the mapping relation of test items and test demands and test coverage indexes by users; converting the test demand model into a test demand description XML file; and finally, resolving the file to analyze the test coverage. The device for analyzing the test coverage automatically mainly comprises a test demand modeling module, a test demand and test item mapping module, a test coverage index formulating module, a coverage analysis script module and the like, supports the visual modeling on the XML test demands, establishes the mapping relation of the test items and the test demands and the test coverage indexes, and realizes the automatic analysis of the test coverage. The method and the device can assist analysts in analyzing the test coverage automatically and improve working efficiency and the accuracy of analytical results, and the adopted visual operation is simple, quick and convenient.

An analysis method of electric vehicle travel and charging demand considering the charging feedback effect: modeling of electric vehicle user travel demand in destination mode; time-series interactive analysis of travel and charging demand, and establishing power consumption based on travel demand when the user is in the driving state Model, establish a charging demand generation model based on fuzzy theory when the user is in the driving state, establish a power replenishment model considering the adequacy of charging facilities when the user is in the staying state, and make user difference decisions based on the charging feedback effect when the user is in the leaving state ; Time-series interactive simulation of user travel and charging demand. The invention can realize the time sequence interaction between the travel demand and the charging demand of the electric vehicle user, and analyze the change trend of the charging demand of the user and the hysteresis and recovery of the travel demand.

The invention discloses a requirement modeling method based on a new characteristic model and a model transformation method. A model is established by the new characteristic model through a hierarchical structure of expansion of ability characteristics along with addition of a 'service layer' and a quality characteristic with addition of four hierarchical structures. Five types of conditions of the characteristic model are simplified to two types of conditions through introduction of a 'selectable set'. A requirement modeling technological process is designed according to the new characteristic model. A characteristic pattern is converted into a unified modeling language (UM) class pattern and a UML case using pattern. The requirement modeling method based on the new characteristic model is capable of greatly promoting reusability of software requirement assets and improving production efficiency and quality of software. The model transformation method is joined with the requirement modeling method based on the characteristic model and a UML pattern modeling method.

The invention discloses a reconstruction method of an acetabular tissue model oriented to serialized CT images of the hip joint. Select the point with the largest gradient on the vertical line on the line; traverse the thick contour of the femoral head to obtain the contour point set of the point with the largest gradient on the tangent vertical line; the points in the contour point set are connected to form the fine contour of the femoral head tissue in the CT slice ; Sequential femoral head contour extraction step, sequence acetabular image extraction step and three-dimensional reconstruction step. Based on the bone shape of the patient's individual hip joint, the present invention obtains individualized relevant position parameters, performs acetabular segmentation in CT images, and obtains accurate acetabular tissue images and three-dimensional models, which are used for the subsequent personalized reflection of the artificial femoral head prosthesis. For modeling, no prior knowledge obtained by training with other data sets is required, and the implementation is simple.