Research on expansion and classification of imbalanced data based on SMOTE algorithm

With the development of artificial intelligence, big data classification technology provides the advantageous help for the medicine auxiliary diagnosis research. While due to the different conditions in the different sample collection, the medical big data is often imbalanced. The class-imbalance problem has been reported as a serious obstacle to the classification performance of many standard learning algorithms. SMOTE algorithm could be used to generate sample points randomly to improve imbalance rate, but its application is affected by the marginalization generation and blindness of parameter selection. Focusing on this problem, an improved SMOTE algorithm based on Normal distribution is proposed in this paper, so that the new sample points are distributed closer to the center of the minority sample with a higher probability to avoid the marginalization of the expanded data. Experiments show that the classification effect is better when use proposed algorithm to expand the imbalanced dataset of Pima, WDBC, WPBC, Ionosphere and Breast-cancer-wisconsin than the original SMOTE algorithm. In addition, the parameter selection of the proposed algorithm is analyzed and it is found that the classification effect is the best when the distribution characteristics of the original data was maintained best by selecting appropriate parameters in our designed experiments.

Transferability of the working envelope approach for parameter selection and optimization in thin wall WAAM

This work aims to propose and assess a methodology for parameterization for WAAM of thin walls based on a previously existing working envelope built for a basic material (parameter transferability). This work also aimed at investigating whether the working envelope approach can be used to optimize the parameterization for a target wall width in terms of arc energy (which governs microstructure and microhardness), surface finish and active deposition time. To reach the main objective, first, a reference working envelope was developed through a series of deposited walls with a plain C-Mn steel wire. Wire feed speed (WFS) and travel speed (TS) were treated as independent variables, while the geometric wall features were considered dependent variables. After validation, three combinations of WFS and TS capable of achieving the same effective wall width were deposited with a 2.25Cr-1Mo steel wire. To evaluate the parameter transferability between the two materials, the geometric features of these walls were measured and compared with the predicted values. The results showed minor deviations between the predicted and measured values. As a result, WAAM parameter selection for another material showed to be feasible after only fewer experiments (shorter time and lower resource consumption) from a working envelope previously developed. The usage of the approach to optimize parameterization was also demonstrated. For this case, lower values of WFS and TS were capable of achieving a better surface finish. However, higher WFS and TS are advantageous in terms of production time. As long as the same wall width is maintained, variations in WFS and TS do not significantly affect microstructure and microhardness.

An Improved Artificial Potential Field Escape Method with Weight Adjustment

Aiming at the problems of obstacle avoidance and bullet avoidance during the patrol swarm, this paper analyzed the defects of the classical artificial potential field, proposed an adjustable escape method, which establish the relationship between the adjustment coefficient and the distance. This method avoid too large or too small escape force that get the bullet into new local shock problem near the target. Then given the weight calculation and parameter selection method, restricted the escape motion by kinematics according to the constraints in the actual motion. This improved method can effecting solve the problem of avoidance in dynamic and complex environment.

Matching calculation of accidental movement protection device for elevator Car

The cage accidental movement protection system is an important protection system of elevator. The basic principle and structure of the cage accidental movement protection device are described. Combined with the whole process from accidental movement of the cage to the operation of the protection device, the theoretical calculation and judgment principle of the accidental movement of the cage protection device are introduced. Aiming at the requirement of the matching calculation of the accidental movement protection of elevator car, the selection of several key parameters which affect the matching calculation of the accidental movement protection of elevator car was proposed. The influence of several key parameters on the matching calculation is analyzed, and the parameter selection is discussed based on relevant standards, and feasible solutions are proposed. These schemes provide a reference for the selection and matching calculation of accidental movement protection devices.