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Junjie Zhou

Publications and source records attributed to Junjie Zhou.

58 records · Page 4Linked to original sources

Multi-activity Influence and Intervention

Using a general network model with multiple activities, we analyse a planner's welfare maximising interventions taking into account within-activity network spillovers and cross-activity interdependence. We show that the direction of the optimal intervention, under sufficiently large budgets, critically depends on the spectral properties of two matrices: the first matrix depicts the social connections among agents, while the second one quantifies the strategic interdependence among different activities. In particular, the first principal component of the interdependence matrix determines budget resource allocation across different activities, while the first (last) principal component of the network matrix shapes the resource allocation across different agents when network effects are strategic complements (substitutes). We explore some comparative statics analysis with respective to model primitives and discuss several applications and extensions.

econ.TH↗

Research on the Inverse Kinematics Prediction of a Soft Biomimetic Actuator via BP Neural Network

In this work, we address the inverse kinetics problem of motion planning of soft biomimetic actuators driven by three chambers. Soft biomimetic actuators have been applied in many applications owing to their intrinsic softness. Although a mathematical model can be derived to describe the inverse dynamics of this actuator, it is still not accurate to capture the nonlinearity and uncertainty of the material and the system. Besides, such a complex model is time-consuming, so it is not easy to apply in the real-time control unit. Therefore, developing a model-free approach in this area could be a new idea. To overcome these intrinsic problems, we propose a back-propagation (BP) neural network learning the inverse kinetics of the soft biomimetic actuator moving in three-dimensional space. After training with sample data, the BP neural network model can represent the relation between the manipulator tip position and the pressure applied to the chambers. The proposed algorithm is more precise than the analytical model. The results show that a desired terminal position can be achieved with a degree of accuracy of 2.46% relative average error with respect to the total actuator length.

cs.RO↗

Structural Interventions in Networks

Two types of interventions are commonly implemented in networks: characteristic intervention, which influences individuals' intrinsic incentives, and structural intervention, which targets the social links among individuals. In this paper we provide a general framework to evaluate the distinct equilibrium effects of both types of interventions. We identify a hidden equivalence between a structural intervention and an endogenously determined characteristic intervention. Compared with existing approaches in the literature, the perspective from such an equivalence provides several advantages in the analysis of interventions that target network structure. We present a wide range of applications of our theory, including identifying the most wanted criminal(s) in delinquent networks and targeting the key connector for isolated communities.

econ.TH↗

Research on Control Method and Evaluation System of Ground Unmanned Vehicle Formation Transform

In this paper,we design a formation control systrm for multi-unmanned ground vehicles(UGV) from the prospective of path planning and path tracking.The master-slave control is adopted by electing out a main vehicle to address the problem of possible accumulation,tranmission and amplification of errors.In the process of formation transformation,we first generate an expected path by combing the methods of dynamic window and potential energy field.Then a path tracking algorithm based on Hermite curve is adopted to make the formation transformation process more stable and accurate.Finally,the evaluation system of the formation control system is constructed,which combines the expected position,the actual position,the expected speed, the actual speed and the actual acceleration,giving an evalutaion on the performance of the formation transformation,response of the formation driving process and the performance of the formation stability.

cs.RO↗