Particle Swarm Algorithm Path-Planning Method for Mobile Robots Based on Artificial Potential Fields.

Path planning is an important part of the navigation control system of mobile robots since it plays a decisive role in whether mobile robots can realize autonomy and intelligence. The particle swarm algorithm can effectively solve the path-planning problem of a mobile robot, but the traditional particle swarm algorithm has the problems of a too-long path, poor global search ability, and local development ability. Moreover, the existence of obstacles makes the actual environment more complex, thus putting forward more stringent requirements on the environmental adaptation ability, path-planning accuracy, and path-planning efficiency of mobile robots.

Artificial intelligence method for predicting the maximum stress of an off-center casing under non-uniform ground stress with support vector machine.

Unlabelled: The situation of an off-center casing under non-uniform ground stress can occur in the process of drilling a salt-gypsum formation, and the related casing stress calculation has not yet been solved analytically. In addition, the experimental equipment in many cases cannot meet the actual conditions and the experimental cost is very high. These comprehensive factors cause the existing casing design to not meet the actual conditions and cause casing deformation, affecting the drilling operation in Tarim oil field.

Study on the mutual interactions between the parameters of a CANON system and its coping strategy when operating at room temperature (15 to 25 °C) using response surface methodology.

The coping strategy of a CANON (completely autotrophic nitrogen removal over nitrite) reactor working at room temperature was investigated using response surface methodology. The total nitrogen (TN) removal efficiency was taken as a dependent variable. The temperature (X), dissolved oxygen (DO) concentration (Y), and influent nitrogen loading rate (Z) were taken as independent variables.