Mine Internet of Things Based on Neural Network and its Research and Application

2011 ◽  
Vol 467-469 ◽  
pp. 1746-1752
Author(s):  
Zhen Yu Wang ◽  
Chun Lei Wang ◽  
Zhi Dong Wang ◽  
Shao Yi Jia
Keyword(s):  
Neural Network ◽  
Internet Of Things ◽  
Production Management ◽  
Information Age ◽  
Mining Enterprise ◽  
Development Direction ◽  
Control Production ◽  
Neural Network System ◽  
Safety Production ◽  
And Control

Internet of things is an ultimate development direction of the information age, while mine informatization is only way to realize the safety production and management of mining enterprise. In this paper, we research and simulate the human neural network system and propose the structure of internet of things based on human neural network. We connect all the objects and systems of the mines through mine internet of things to simulate the reflex activities of human body, regulate and control production, management and other links of the mining enterprises, so that it will become a coordinated and efficient whole.

scholarly journals Enterprise Work Safety Standardization Optimization Mode on VSM in China

2020 ◽  
Author(s):  
Dunwen Liu ◽  
Chun Gong ◽  
Yinghua Jian
Keyword(s):  
Management System ◽  
Production Management ◽  
Safety Management ◽  
Work Safety ◽  
Safety Production ◽  
The Government ◽  
Traditional Work ◽  
The One ◽  
Viable System ◽  
And Control

The work safety standardization of enterprises based on the traditional work safety theory has played a significant role in reducing the number of accidents and improving work safety to some extent in China. However, some problems are coming with the work safety standardization of enterprises developing constantly in China. On the one hand, it is not combined with the actual situation of the enterprise, lacking pertinence and specificity, these defects resulted that it is not integrated with original safety production management system of enterprise and make it difficult to carry out. On the other hand, there is a lack of systematic management methods for the work safety management system of enterprise, most of enterprises only pay attention to the inspection result rather than the process control. This means after the check of the government, many enterprises will relax to carry out the system. This paper puts forward a new method for optimizing the standardization management mode of work safety based on the Viable System Model(VSM), which can solve the defects of work safety standardization of enterprises management system. An optimization model of work safety standardization based on VSM was construct for explaining the process optimization and control of work safety standardization management. It can improve the connectivity between the enterprise and the government. The conclusion of this paper can provide reference for achieving the development and optimization of work safety standardization of enterprises in China.

scholarly journals Neural Network System Identification and Controlling of Multivariable System

2012 ◽  
pp. 154-159
Author(s):  
H.M.Reshma Begum ◽  
Revathi. P ◽  
Babiyola. D
Keyword(s):  
Neural Network ◽  
System Identification ◽  
Mimo Systems ◽  
Industrial Processes ◽  
Network System ◽  
Data Sets ◽  
Output Data ◽  
Neural Network System ◽  
And Control ◽  
System Transfer Function

Most of the industrial processes are multivariable in nature. Here Greenhouse system is considered which is the important application in agricultural process. Greenhouse is to improve the environmental conditions in which plants are grown .In this paper we have proposed identification of greenhouse system using input and output data sets to estimate the best model and validate the model. For MIMO systems, Neural Network System identification provides a better alternative to find their system transfer function. The results were analyzed and the model is obtained. From this obtained model ,the system is controlled by conventional method. By these method we can identify the model and control the complicated systems like Greenhouse.

scholarly journals Design of Online Mine Safety Detection System Based on Internet of Things

2016 ◽  
Vol 12 (12) ◽  
pp. 60 ◽  
Author(s):  
Zhao-ming Qian ◽  
Yan-bin Yuan ◽  
Sa-sa Zhang ◽  
Gao-feng Ren
Keyword(s):  
Internet Of Things ◽  
Production Management ◽  
Safety Management ◽  
Detection System ◽  
Mine Safety ◽  
Open Architecture ◽  
Comprehensive Management ◽  
Safety Production ◽  
On Line ◽  
Internet Of Things Technology

Safety production is a major problem faced by mining enterprises. In view of the requirements of mine safety production and the development of information technology, the application of Internet of Things technology to the mining process can not only improve the safety management technology of mine enterprises, The steady growth of the national economy and the sustainable and healthy development of mining have a profound impact. The on-line monitoring system of mining safety based on Internet of Things technology can help mine personnel, equipment and environment comprehensive management, enrich the mine safety production management means, and improve the ability of mine to resist various risks and disasters. In this paper, combined with the actual situation of the mine, focusing on the Internet of Things technology-based mine safety inspection and protection system construction of the necessity, and based on the three-tier architecture of the open architecture of the network, based on mine safety on-line detection support system Of the application model structure. For the construction of mine networking provides the experience and technology<strong>.</strong>

Parking Motion Planning and Control of a Car-Like Robot Using a Fuzzy Neural Network

1995 ◽  
Vol 7 (1) ◽  
pp. 52-56 ◽  
Author(s):  
Motoji Yamamoto ◽  
◽  
Masaaki Kobayashi ◽  
Akira Mohri
Keyword(s):  
Neural Network ◽  
Motion Planning ◽  
Fuzzy Neural Network ◽  
Control Method ◽  
Difficult Problem ◽  
Human Control ◽  
Planning And Control ◽  
Fuzzy Neural ◽  
Neural Network System ◽  
And Control

This paper discusses a parking motion planning and control of a car-like robot. Because of non-holonomic constraints of the system, motion planning and control is regarded as a difficult problem. In this paper, constraints of steering operation and obstacle avoidance with garage and walls are also considered. As one approach to this problem, extracting human control strategy can be considered, because many drivers can easily park their cars in garages. This paper proposes a motion planning and control method using a fuzzy neural network (FNN). The fuzzy neural network system for parking motion planning learns good parking motions by human operations to generate motion strategy of parking. The fuzzy neural network is then used for parking motion planning in a restricted area surrounded by walls. Computer simulation demonstrates the effectiveness of the planning method. Furthermore, the method can be considered as a feedback control law for the parking of car-like robot. Therefore, an experiment of parking motion control using the fuzzy neural network is also tested.

Neural network system for detecting and neutralizing remote unauthorized interference into the components of the Internet of Things

2021 ◽  
Author(s):  
A. I. Vlasov ◽  
E. R. Zakharov ◽  
V. O. Zakharova
Keyword(s):  
Neural Network ◽  
Internet Of Things ◽  
Normal Modes ◽  
The Internet ◽  
Network System ◽  
Neural Network Approach ◽  
The Neural Network ◽  
Neural Network System ◽  
Artificial Neural ◽  
The Internet Of Things

In this work the authors have analyzed the neural network system for detecting and neutralizing remote and unauthorized interference with components of the Internet of Things. The main focus is on considering the neural network approach to detecting intrusions into the Internet of Things network, its monitoring and countering suspicious activity on the host. Features of development of model of artificial neural networks for application of apparatus of neural network in this direction have been considered. This allows you to reflect the successful identification of various types of attacks in terms of true and false positive results. However, the problems of obtaining data on overload and critical modes of the system remain unresolved. The use of a neural network system for detecting and neutralizing remote and unauthorized interference with components of the Internet of Things allows you to implement a module for detecting anomalies in the network, based on the Voltaire series, which considers the theoretical prerequisites of the method of dynamically building an artificial neural network. The main types of attacks, types of intrusion detection systems, interpretations of the obtained data, a brief study of works in the field of neural network solutions have been analyzed. An effective solution has been offered to protect workstations in the Internet of Things network from unauthorized access, and to configure security for all component modules. In conclusion, recommendations have been given for implementing the construction of a neural network module that detects deviations in the operation of the Internet of Things from normal modes.

Study on the Application of Safety Assessment Model about Source of Hazardous Chemicals

2010 ◽  
Vol 113-116 ◽  
pp. 1925-1929 ◽  
Author(s):  
Hong Huo ◽  
Zhen Yu Xiong
Keyword(s):  
Safety Assessment ◽  
Production Management ◽  
Assessment Model ◽  
Hazardous Chemicals ◽  
Hazardous Chemical ◽  
Real Risk ◽  
Safety Production ◽  
And Control ◽  
Technology Level ◽  
Real Danger

Safety assessment about source of hazardous chemicals is an important element in the safety production management. Its model has been introduced, moreover, a series of factors which can affect inherent hazard and real danger have been analyzed in this essay. A mathematical model can be established and put into practice. Through specific analysis of the realities of the Source of Hazardous chemical, it is easy to find that real danger has to do with many factors: Technology level, equipment level, the degree of the quality of personnel. These factors can offset and control the risk, therefore the real risk has been greatly reduced compared with the inherent risk.

Improving the effectiveness of traditional education based on computer artificial intelligence and neural network system

2020 ◽  
pp. 1-11
Author(s):  
Wenjuan Ma ◽  
Xuesi Zhao ◽  
Yuxiu Guo
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Education Reform ◽  
Traditional Education ◽  
Machine Learning Algorithms ◽  
Local Optimum ◽  
Optimization Strategy ◽  
Fish School ◽  
Tlbo Algorithm ◽  
Neural Network System

The application of artificial intelligence and machine learning algorithms in education reform is an inevitable trend of teaching development. In order to improve the teaching intelligence, this paper builds an auxiliary teaching system based on computer artificial intelligence and neural network based on the traditional teaching model. Moreover, in this paper, the optimization strategy is adopted in the TLBO algorithm to reduce the running time of the algorithm, and the extracurricular learning mechanism is introduced to increase the adjustable parameters, which is conducive to the algorithm jumping out of the local optimum. In addition, in this paper, the crowding factor in the fish school algorithm is used to define the degree or restraint of teachers’ control over students. At the same time, students in the crowded range gather near the teacher, and some students who are difficult to restrain perform the following behavior to follow the top students. Finally, this study builds a model based on actual needs, and designs a control experiment to verify the system performance. The results show that the system constructed in this paper has good performance and can provide a theoretical reference for related research.

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