scholarly journals Security Control Technology and Simulation of Network News Communication under the Environment of Internet of Things

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Xudong Zhou ◽  
Jing Wang ◽  
Xiao Zhou
Keyword(s):  
Genetic Algorithm ◽  
Internet Of Things ◽  
Control Method ◽  
Network News ◽  
Frame Structure ◽  
Response Strategy ◽  
Cooperative Localization ◽  
Intrusion Response ◽  
Security Control ◽  
Response Task

Internet of Things is an application of network news communication technology. Based on the Internet, it uses physical access technologies such as radio frequency tag and wireless sensor network news communication and network news communication information transmission technology to build a network news communication information system that can cover people and things. In the physical layer, the relative position of the object is calculated by using multipoint cooperative localization, so as to determine the minimum anonymous region. Generate and maintain the anonymous tree topology on the network news dissemination layer, and provide storage management support for multiple anonymous groups. In the application layer, the object determines the corresponding anonymity degree according to the identity and uses the frame structure to construct and return the new anonymous group consistent with the existing anonymous group, which can prevent the persistent multiprecision query attack. A real-time control method for intrusion response of a security control system is designed, which includes two stages: response task generation and integrated scheduling. An intrusion response task set generation method based on an improved nondominated sorting genetic algorithm is presented, and a distributed integrated task scheduling and optimization algorithm based on a genetic algorithm and a directed acyclic graph is designed. The numerical simulation results show that this method can quickly and smoothly implement the response strategy of information security intrusion without affecting the normal execution of system tasks.

An efficient intelligent decision method for bionic motion unmanned system

2021 ◽  
pp. 095965182110655
Author(s):  
Haipeng Chen ◽  
Wenxing Fu ◽  
Yuze Feng ◽  
Jia Long ◽  
Kang Chen
Keyword(s):  
Genetic Algorithm ◽  
Evolutionary Algorithms ◽  
Path Planning ◽  
Motion Control ◽  
Control Method ◽  
Improved Genetic Algorithm ◽  
Decision Method ◽  
Multiple Traveling Salesman Problem ◽  
Intelligent Decision ◽  
Unmanned System

In this article, we propose an efficient intelligent decision method for a bionic motion unmanned system to simulate the formation change during the hunting process of the wolves. Path planning is a burning research focus for the unmanned system to realize the formation change, and some traditional techniques are designed to solve it. The intelligent decision based on evolutionary algorithms is one of the famous path planning approaches. However, time consumption remains to be a problem in the intelligent decisions of the unmanned system. To solve the time-consuming problem, we simplify the multi-objective optimization as the single-objective optimization, which was regarded as a multiple traveling salesman problem in the traditional methods. Besides, we present the improved genetic algorithm instead of evolutionary algorithms to solve the intelligent decision problem. As the unmanned system’s intelligent decision is solved, the bionic motion control, especially collision avoidance when the system moves, should be guaranteed. Accordingly, we project a novel unmanned system bionic motion control of complex nonlinear dynamics. The control method can effectively avoid collision in the process of system motion. Simulation results show that the proposed simplification, improved genetic algorithm, and bionic motion control method are stable and effective.

Air Suspension Optimal Control Based on the Genetic Algorithm

2011 ◽  
Vol 467-469 ◽  
pp. 1066-1071
Author(s):  
Zhong Xin Li ◽  
Ji Wei Guo ◽  
Ming Hong Gao ◽  
Hong Jiang
Keyword(s):  
Genetic Algorithm ◽  
Optimal Control ◽  
Dynamic Model ◽  
Control Method ◽  
Control Model ◽  
Weight Matrix ◽  
Object A ◽  
Full Vehicle ◽  
Air Suspension ◽  
Optimal Control Method

Taking the full-vehicle eight-freedom dynamic model of a type of bus as the simulation object , a new optimal control method is introduced. This method is based on the genetic algorithm, and the full-vehicle optimal control model is built in the MatLab. The weight matrix of the optimal control is optimized through the genetic algorithm; then the outcome is compared with the artificially-set optimal control simulation, which shows that the genetic-algorithm based optimal control presents better performance, thereby creating a smoother ride and improving the steering stability of the vehicle.

scholarly journals IoT Heating Solution for Smart Home with Fuzzy Control

2020 ◽  
Vol 26 (6) ◽  
pp. 747-761
Author(s):  
Łukasz Apiecionek ◽  
Jacek Czerniak ◽  
Dawid Ewald ◽  
Mateusz Biedziak
Keyword(s):  
Fuzzy Logic ◽  
Internet Of Things ◽  
Fuzzy Control ◽  
Smart Home ◽  
Control Method ◽  
Computer Systems ◽  
The Internet ◽  
Climate Chamber

There is currently an era of Internet of Things in the computer systems, which consists in connecting all possible devices to the Internet in order to provide them with new functionalities and thus { to improve the user's life standard. One of such solutions could be Smart Home. The possibility of monitoring inner environment is required for such solutions. Such monitoring provides potential for e.g. better heating control. The authors of this paper propose some heating control method with Fuzzy Logic. The proposed method was tested in a special climate chamber. The authors provided conclusions at the end of the paper.

Security Control Method of Loading for Surcharge Preloading Based on the Stress Path

2011 ◽  
Vol 368-373 ◽  
pp. 2795-2803
Author(s):  
Heng Hu ◽  
Yan Li ◽  
Zhi Liang Dong ◽  
Yan Luo ◽  
Gong Xin Zhang
Keyword(s):  
Pore Water ◽  
Safety Factor ◽  
Control Method ◽  
Pore Water Pressure ◽  
Water Pressure ◽  
Stress Path ◽  
Excess Pore Water Pressure ◽  
Surcharge Preloading ◽  
Security Control ◽  
Excess Pore

All the time, security control method of loading is an important research part in the surcharge preloading, which is directly related to safety of the construction process. Starting from the stress path, discussing the variation of excess pore water pressure and relationship between stress path and security, and bringing forward the control method with a safety factor Fs based on the stress path. By measuring the change of excess pore water pressure, the control method with a safety factor Fs can reflect quantitatively the security status of soil and achieve the purpose of the process control, finally the security control method including the safety factor of loading and speed control is put forward to monitor construction safety. The safety factor of loading Fs is verified and back analyzed with the finite-element software, getting the correction factor from 0.90 to 1.20.

Application of Blow-off Wind Tunnel Control Based on Genetic Algorithm Optimized BP-Neural Network PID Neural Network

2013 ◽  
Vol 310 ◽  
pp. 557-559 ◽  
Author(s):  
Li Ji ◽  
Xiao Fei Lian
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Wind Tunnel ◽  
Bp Neural Network ◽  
Control Method ◽  
Network Control ◽  
Operating Conditions ◽  
Algorithm Optimization ◽  
Large Delay ◽  
Neural Network Pid

For a blow-off tunnel running, there is the large delay and lag issues. We build a mathematical model of the wind tunnel Mach number control by the test modeling method, then analyse the pros and cons of various control methods based on BP neural network control algorithm. Put forward genetic algorithm optimization neural network adaptive control method to solve the large inertia of the wind tunnel system, and large delay. A large number of simulation studies, run a variety of operating conditions for the wind tunnel simulation proved that the improved adaptive neural network PID control method is reasonable and effective.

Research on Human-Computer Interaction Control Method in the Background of Internet of Things

2021 ◽  
Author(s):  
Yingying Hu ◽  
Zhongyang Li
Keyword(s):  
Internet Of Things ◽  
Control Method ◽  
Computer Control ◽  
Control Device ◽  
Smart Devices ◽  
The Internet ◽  
Interactive Control ◽  
Interaction Control ◽  
Different Types ◽  
The Internet Of Things

Against the background of the growing development of the Internet of Things, this article conducts research on more efficient methods for controlling the interconnection of all things, and proposes that smart devices use the same operating platform, and the human-computer interface presents universal modular controls for manipulation, it can satisfy the requirement that one device controls several different types of controlled device simultaneously. At the same time, the interactive method uses the controlled device to actively submit control content to the control device, and discusses the human-computer interactive control method applicable to the Internet of Everything, and strives to achieve a convenient and easy-to-use human-computer control experience.

Sign in / Sign up

Export Citation Format

Share Document