Abstract: The present disclosure provides a risk assessment method of water inrush in tunnels constructed in water-rich grounds. The method includes the following steps: simulating a tunnel excavation process by finite element software MIDAS GTS NX and fluid-structure interaction; according to a research method of control variables, analyzing effects of a groundwater level, an elastic modulus and advanced pipe shed grouting on the stability of surrounding rock, and improving an algorithm of a radial basis function (RBF) neural network using a Grey Relation Analysis (GRA)-based Partitioning Around Medoid (PAM) clustering algorithm to assess risks of water inrush occurring in Qingdao area.

Abstract: An intelligent control method for a dynamic neural network-based variable cycle engine is provided. By adding a grey relation analysis method-based structure adjustment algorithm to the neural network training algorithm, the neural network structure is adjusted, a dynamic neural network controller is constructed, and thus the intelligent control of the variable cycle engine is realized. A dynamic neural network is trained through the grey relation analysis method-based network structure adjustment algorithm designed by the present invention, and an intelligent controller of the dynamic neural network-based variable cycle engine is constructed. Thus, the problem of coupling between nonlinear multiple variables caused by the increase of control variables of the variable cycle engine and the problem that the traditional control method relies too much on model accuracy are effectively solved.

Abstract: A vehicle running status field model-based information transmission frequency optimization method in the Internet of Vehicles belongs to the technical field of network communications. The method establishes a running status field model according to the real-time running status of a road vehicle to describe the degree of risk of the vehicle, the degree of risk can be used to dynamically adjust the transmission frequency of safety-critical information, and the transmission frequency of non-safety-critical information is adjusted through the real-time transmission frequency of safety-critical information to achieve the purpose of improving the utilization ratio of link. The method establishes the running status field model of a moving vehicle, uses the risk intensity of the vehicle in the running status field to describe the current running risk of the vehicle, and takes account of different application scenarios, thereby having generality.

Abstract: An intelligent control method for a dynamic neural network-based variable cycle engine is provided. By adding a grey relation analysis method-based structure adjustment algorithm to the neural network training algorithm, the neural network structure is adjusted, a dynamic neural network controller is constructed, and thus the intelligent control of the variable cycle engine is realized. A dynamic neural network is trained through the grey relation analysis method-based network structure adjustment algorithm designed by the present invention, and an intelligent controller of the dynamic neural network-based variable cycle engine is constructed. Thus, the problem of coupling between nonlinear multiple variables caused by the increase of control variables of the variable cycle engine and the problem that the traditional control method relies too much on model accuracy are effectively solved.

Abstract: A vehicle running status field model-based information transmission frequency optimization method in the Internet of Vehicles belongs to the technical field of network communications. The method establishes a running status field model according to the real-time running status of a road vehicle to describe the degree of risk of the vehicle, the degree of risk can be used to dynamically adjust the transmission frequency of safety-critical information, and the transmission frequency of non-safety-critical information is adjusted through the real-time transmission frequency of safety-critical information to achieve the purpose of improving the utilization ratio of link. The method establishes the running status field model of a moving vehicle, uses the risk intensity of the vehicle in the running status field to describe the current running risk of the vehicle, and takes account of different application scenarios, thereby having generality.