This paper focused on three application problems of the traditional Deep Deterministic Policy Gradient(DDPG) algorithm. That is, the agent exploration is insufficient, the neural network performance is unsatisfied, the agent output fluctuates greatly. In terms of agent exploration strategy, network training algorithm and overall algorithm implementation, an improved DDPG method based on double-layer BP neural network is proposed. This method introduces fuzzy algorithm and BFGS algorithm based on Armijo-Goldstein criterion, improves the exploration efficiency, learning efficiency and convergence of BP neural network, increases the number of layers of BP neural network to improve the fitting ability of the network, and adopts periodic update to ensure the stable operation of the algorithm. The experimental results show that the deep learning network based on the improved DDPG algorithm has greatly improved the performance compared with the traditional method after multiple rounds of self-learning under variable working conditions. This study lays a theoretical and experimental foundation for the extended application of deep learning algorithm.

The current situation and future development of the supply and demand coupling coordination of elderly care service resources reflect the level of elderly care service resource allocation. Whether factors affecting its development can be found is the key to promote the accurate allocation of elderly care service. Based on the coupling coordination model, the supply and demand of elderly care service resources, the development circumstance and the spatio-temporal evolution of supply and demand coupling coordination are analyzed in this paper by using the data of the elderly care service resources in 31 regions and autonomous regions in China from 2010 to 2019. The result shows that there are regional differences in the development of supply and demand coupling coordination of elderly care service resources. The degree of supply and demand coupling coordination of elderly care service resources in the western and northern regions is lower than that in the eastern and southern regions. Although the level in most areas of supply and demand coupling coordination of elderly care service resources will improve in the future, there is still a gap from good coordination. In order to strengthen the supply of elderly care service resources, and promote the upgrade of the supply and demand of elderly care service resources, the government should start from the demand of the elderly to increase investment in infrastructure construction, investment in elderly care services resources, talent training and other aspects.

With the rapid growth of the elderly population of China in recent years, the service demands of older Chinese people continue to increase. The increasingly severe situation with respect to the elderly population is an important social problem that China will face for a long time into the future. It is urgent to solve the problem of how to scientifically carry out allocation planning of service resources for the aged and guide the effective supply of service resources. This paper analyzes the factors affecting service resources for the aged, divides China’s service resource supply and demand system into a supply subsystem, a demand subsystem, and a population and economy subsystem. Using system dynamics methods to analyze the causal relationship between variables and the state space method to build a mathematical model and perform simulation analysis, we research the the current situation of China’s service resources supply and demand balance for the aged. In addition, we put forward resource configuration optimization measures for the future allocation of service resources for the aged, providing a practical basis for future decision-making.

In this paper, focusing on the inconvenience of variable value PID based on manual parameter adjustment for the hydraulic drive unit (HDU) of a legged robot, a method employing double-layer back propagation (BP) neural networks for learning the law of PID control parameters is proposed. The first layer is used to learn the relationship between different control parameters and the control performance of the system under various working conditions. The second layer is used to study the relationship between the parameters of the working conditions and the optimizing control parameters under various working conditions. The effectiveness of the proposed control method was verified by simulation and experiment. The results showed that the proposed method can provide a theoretical and experimental basis for the selection of control parameters, and can be extended to similar controllers, therefore possessing engineering application value.

With the improvement of Chinese economic status, Chinese A‐share market has attracted more and more attention from international investors. Sub‐new stock is a general name for the companies which list less than a year, most companies of this category come from the China Growth Enterprise Market (GEM) and are high‐tech companies with high growth. To study the influence of major asset restructuring on the stock prices of different companies, this paper adopts the event study method to calculate the samples' abnormal return in a 20‐day window period, compares related party transactions and unrelated party transactions, as well as different payment methods for the restructuring. The analysis shows that the listed companies of Growth Enterprise Market can get higher excess returns, the sample of unrelated transaction obtains more abnormal income than the sample of related transaction. The research can provide a reference for local and international investors.