Research on Human Resource Allocation Model Based on SOM Neural Network

With the fierce competition of the enterprise market, the human resource allocation of enterprises will face multiple risks. This article takes the connotation of human resource configuration management as the research object and establishes the human resource configuration model through SOM neural network. And the model is trained, learned, and tested. What's more, it is applied to human resources management to adjust the allocation of human resources for the enterprise in a timely manner. It provides a detailed basis for proposing coping strategies and has a great application value.

A Dynamic Contagion Risk Model with Recovery Features

We introduce threshold growth in the classical threshold contagion model, or equivalently a network of Cramér-Lundberg processes in which nodes have downward jumps when there is a failure of a neighboring node. Choosing the configuration model as underlying graph, we prove fluid limits for the baseline model, as well as extensions to the directed case, state-dependent interarrival times and the case of growth driven by upward jumps. We obtain explicit ruin probabilities for the nodes according to their characteristics: initial threshold and in- (and out-) degree. We then allow nodes to choose their connectivity by trading off link benefits and contagion risk. We define a rational equilibrium concept in which nodes choose their connectivity according to an expected failure probability of any given link and then impose condition that the expected failure probability coincides with the actual failure probability under the optimal connectivity. We show existence of an asymptotic equilibrium and convergence of the sequence of equilibria on the finite networks. In particular, our results show that systems with higher overall growth may have higher failure probability in equilibrium.

Optimal Configuration of the Integrated Charging Station for PV and Hydrogen Storage

This paper designs the integrated charging station of PV and hydrogen storage based on the charging station. The energy storage system includes hydrogen energy storage for hydrogen production, and the charging station can provide services for electric vehicles and hydrogen vehicles at the same time. To improve the independent energy supply capacity of the hybrid charging station and reduce the cost, the components are reasonably configured. To minimize the configuration cost of the integrated charging station and the proportion of power purchase to the demand of the charging station, the energy flow strategy of the integrated charging station is designed, and the optimal configuration model of optical storage capacity is constructed. The NSGA-II algorithm optimizes the non-inferior Pareto solution set, and a fuzzy comprehensive evaluation evaluates the optimal configuration.

Remotely-sensed slowing down in spatially patterned dryland ecosystems

Regular vegetation patterns have been predicted to indicate a system slowing down and possibly desertification of drylands. However, these predictions have not yet been observed in dryland vegetation due to the inherent logistic difficulty to gather longer-term in situ data. Here, we use recently developed methods using remote-sensing EVI time-series in combination with classified regular vegetation patterns along a rainfall gradient in Sudan to test these predictions. Overall, three temporal indicators (responsiveness, temporal autocorrelation, variance) show slowing down as vegetation patterns change from gaps to labyrinths to spots towards more arid conditions, confirming predictions. However, this transition exhibits non-linearities, specifically when patterns change configuration. Model simulations reveal that the transition between patterns temporarily slows down the system affecting the temporal indicators. These transient states when vegetation patterns reorganize thus affect the systems resilience indicators in a non-linear way. Our findings suggest that spatial self-organization of dryland vegetation is associated with critical slowing down, but this transition towards reduced resilience happens in a non-linear way. Future work should aim to better understand transient dynamics in regular vegetation patterns in dryland ecosystems, because long transients make regular vegetation patterns of limited use for management in anticipating critical transitions.

Research on Life Extension Method of Transmission Line Intelligent Sensing System Based on Environmental Energy Harvesting

In this paper, we focus on building and researching the self-power sensor system based on the tiny energy harvesting technology which can be used in the scenario of ubiquitous power Internet of Things (UPIoT) and prove the possibility and efficiency for the life extension of transmission line intelligent sensing system. Large scale of sensor in the smart grid technology application, especially in high-voltage transmission lines, is not convenient; it is worth mentioning that most of all kinds of sensor node equipment using battery power make the life of the equipment or components limited by greatly. Therefore, low power consumption, long life, no battery dependence, free maintenance, and other requirements are increasingly important to solve the difficulties of deployment and maintenance. At the same time, the problem of the battery case electricity use with low efficiency and short life of sensor node has become the bottleneck of further widely deployed wireless sensor node equipment. The power collection technology based on environmental energy can effectively handle with the problems of energy collection efficiency and management that need to be urgently solved in new application scenarios such as zero-standby power consumption devices, remote active tags, battery-free telemetry and remote control, and ultralong life sensing system. By studying various kinds of environmental energy collection technologies and utilizing the conversion and management technologies of available weak environmental energy, such as solar energy and magnetic field energy, into electric energy, this paper establishes an energy conversion test system and configuration model and verifies the feasibility of the assumption of maintenance-free for the intelligent sensing system of transmission lines.