Badminton Backcourt Stroke Route Planning Method Based on Deep Learning

In order to improve the planning ability of the badminton backcourt stroke line, this study designs a badminton backcourt stroke line planning method based on deep learning. Firstly, the trajectory adaptive learning method of motion primitives is used to design the hitting line nodes and path space, so as to construct the shortest distributed grid structure model of the hitting line. Then, the constraint parameters of hitting route planning are analyzed, and then the hitting position and player posture are controlled according to node positioning and shortest path optimization deployment. Finally, the adaptive optimization of the route planning process is realized by combining the deep learning method. The simulation results show that this method has good learning control ability and good convergence performance and improves the reliability of badminton backcourt hitting line planning.

Impact of task preparedness on L2 oral performance and strategy use

The present study sets out to explore the effects of pre-task planning and unpressured on-line planning on L2 learners’ oral performance and their choices of planning strategies in a dialogic task condition. Forty-eight intermediate Chinese EFL learners were invited to perform the task and were then assigned to four groups, each with a different planning condition. Complexity, accuracy, and fluency of their oral production were measured. Results indicated that in the dialogic task condition, unpressured on-line planning raised syntactic complexity. Strikingly, pre-task planning did not improve L2 performance in all dimensions. Additionally, a trade-off effect was found between complexity and accuracy. Retrospective interviews were conducted to explore strategies employed by the participants and their perceptions of task preparedness. Results showed that the participants preferred to use metacognitive strategies and social/affective strategies in the dialogic task. Both advantages and limitations were identified by the participants regarding different planning conditions.

Integrated Optimization of Line Planning, Timetabling and Rolling Stock Allocation for Urban Railway Lines

In order to improve train operation planning from the two perspectives of enterprise operating costs and passengers’ travel time, this paper proposes an integrated optimization model of three sub-problems, namely line planning, timetabling and rolling stock allocation for urban railway transit lines based on passengers’ travelling demands and the constraints of the urban rail line. The model features dwelling time at stations, turnaround operations at terminal stations, entering/exiting depot operations and an assignment for passengers’ travelling flow. We propose a solution method based on a metaheuristic method that simulates annealing to generate an optimal solution for the overall problem using MATLAB. Finally, we use the example of Xi’an metro line one to demonstrate the performance of the model.

Simulation application of three-dimensional GIS based on full-scenario intelligence in power grid company transmission line planning

Traditional data collection and review methods in power grid planning have always had the problems of time-consuming, poor real-time performance, and cumbersome processes. The application of mobile GIS solves the problems of data collection and review methods and makes more efficient use of mobile GIS terminal collection. The data of the mobile GIS solve the urgent problems that need to be solved since the popularization and application of mobile GIS. This system implements functions such as storage, transmission, and review based on mobile GIS data, which will greatly improve the efficiency of data collection by mobile terminals and reduce the cost of data collection. Realize the planning simulation of the power grid under the intelligent cycle of the whole scene.

An Exact Solution Approach for the Bus Line Planning Problem with Integrated Passenger Routing

The bus line planning problem or transit network design problem with integrated passenger routing is a challenging combinatorial problem. Although well-known benchmark instances for this problem have been available for decades, the state of the art lacks optimal solutions for these instances. The branch and bound algorithm, presented in this paper, introduces three novel concepts to determine these optimal solutions: (1) a new line pool generation method based on dominance, (2) the introduction of essential links, i.e., links which can be determined beforehand and must be present in the optimal solution, and (3) a new network representation based on adding only extra edges. Next to presenting the newly obtained optimal solutions, each of the abovementioned concepts is examined in isolation in the experiments, and it is shown that they contribute significantly to the success of the algorithm.