Study on Data Fusion and Optimization Based on Neural Networks

2014 ◽  
Vol 530-531 ◽  
pp. 463-466 ◽  
Author(s):  
Liang Cheng
Keyword(s):  
Neural Network ◽  
Routing Protocol ◽  
Bp Neural Network ◽  
Network Routing ◽  
Original Model ◽  
Wireless Sensor ◽  
Sink Node ◽  
Data Set ◽  
Hierarchical Routing ◽  
Neural Network Algorithm

Due to limited energy wireless sensor networks, in order to extend the life cycle of WSN, the need for wireless sensor network routing protocol has been improved, based on the original model of hierarchical routing protocol LEACH algorithm, combined with efficient use of energy, new determine the clustering structure methods. The paper used in each sub-clan structures BP neural network algorithm for nodes preclude the data set is processed to reduce the amount of data transmitted to the sink node, reduce communication energy consumption to prolong the network lifetime goal.

scholarly journals Comparison between Flat and Hierarchical Routing Protocols in Wireless Sensor Network

2020 ◽  
pp. 364-369
Author(s):  
Ms Mamta
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Routing Protocol ◽  
Routing Protocols ◽  
Low Cost ◽  
Network Routing ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Hierarchical Routing ◽  
Flat Routing

Wireless Sensor Network (WSN) has delivered the accessibility of small, tiny and low cost sensor nodes which are capable to sense various kinds of physical and environmental conditions, data processing, wireless communication and data gathering. In wireless sensor network routing protocols can be divided into two categories first is flat routing protocol and another is hierarchical routing protocol. In this paper flat and hierarchical routing protocols are evaluated and compared based on various performance parameters. In the last decade we have seen expanded enthusiasm for the potential utilization of remote wireless sensor systems (WSNs) in an extensive change of uses and it has turned into a unique research zone. So finally, in this research paper we are focusing on two different classes of routing protocols in WSN: flat routing and hierarchical or clustering routing.

Research of Fault Diagnosis of Belt Conveyor Based on Fuzzy Neural Network

2014 ◽  
Vol 8 (1) ◽  
pp. 916-921
Author(s):  
Yuan Yuan ◽  
Wenjun Meng ◽  
Xiaoxia Sun
Keyword(s):  
Neural Network ◽  
Fault Diagnosis ◽  
Bp Neural Network ◽  
Fault Location ◽  
Fuzzy Neural Network ◽  
Fuzzy Theory ◽  
Belt Conveyor ◽  
Fuzzy Neural ◽  
Neural Network Algorithm ◽  
Network Fault

To address deficiencies in the process of fault diagnosis of belt conveyor, this study uses a BP neural network algorithm combined with fuzzy theory to provide an intelligent fault diagnosis method for belt conveyor and to establish a BP neural network fault diagnosis model with a predictive function. Matlab is used to simulate the fuzzy BP neural network fault diagnosis of the belt conveyor. Results show that the fuzzy neural network can filter out unnecessary information; save time and space; and improve the fault diagnosis recognition, classification, and fault location capabilities of belt conveyor. The proposed model has high practical value for engineering.

PERFORMANCE EVALUATION ANALYSIS OF WIRELESS SENSOR NETWORKS ROUTING PROTOCOLS IN SMART GRIDS

2016 ◽  
Vol 26 (1) ◽  
pp. 17
Author(s):  
Carlos Deyvinson Reges Bessa
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Routing Protocol ◽  
Smart Grids ◽  
Network Routing ◽  
Base Station ◽  
Wireless Sensor ◽  
Delay Jitter ◽  
La Red

ABSTRACTThis work aims to study which wireless sensor network routing protocol is more suitable for Smart Grids applications, through simulation of AODV protocols, AOMDV, DSDV and HTR in the NS2 simulation environment. Was simulated a network based on a residential area with 47 residences, with one node for each residence and one base station, located about 25m from the other nodes. Many parameters, such as packet loss, throughput, delay, jitter and energy consumption were tested.  The network was increased to 78 and 93 nodes in order to evaluate the behavior of the protocols in larger networks. The tests proved that the HTR is the routing protocol that has the best results in performance and second best in energy consumption. The DSDV had the worst performance according to the tests.Key words.- Smart grid, QoS analysis, Wireless sensor networks, Routing protocols.RESUMENEste trabajo tiene como objetivo estudiar el protocolo de enrutamiento de la red de sensores inalámbricos es más adecuado para aplicaciones de redes inteligentes, a través de la simulación de protocolos AODV, AOMDV, DSDV y HTR en el entorno de simulación NS2. Se simuló una red basada en una zona residencial con 47 residencias, con un nodo para cada residencia y una estación base, situada a unos 25 metros de los otros nodos. Muchos parámetros, tales como la pérdida de paquetes, rendimiento, retardo, jitter y el consumo de energía se probaron. La red se incrementó a 78 y 93 nodos con el fin de evaluar el comportamiento de los protocolos de redes más grandes. Las pruebas demostraron que el HTR es el protocolo de enrutamiento que tiene los mejores resultados en el rendimiento y el segundo mejor en el consumo de energía. El DSDV tuvo el peor desempeño de acuerdo a las pruebas.Palabras clave.- redes inteligentes, análisis de calidad de servicio, redes de sensores inalámbricas, protocolos de enrutamiento.

Algorithm for secure communication of wireless network based on node energy control

2021 ◽  
pp. 1-11
Author(s):  
Shu Zhang ◽  
Jianhua Chen
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Routing Protocol ◽  
Secure Communication ◽  
Network Routing ◽  
Wireless Sensor ◽  
Route Selection ◽  
Joint Function ◽  
Energy Control ◽  
Establishment Process

 This paper analyzes the security algorithm and energy cost of wireless sensor networks in depth, and designs and implements a series of energy-optimized security solutions to ensure the secure establishment and operation of wireless sensor networks. This paper proposes an improved Ad hoc network routing protocol based on energy control. It introduces a low-energy balanced routing algorithm to reduce routing transmission energy consumption, balance network traffic, and improve the energy control performance of network routing protocols. The protocol uses a cross-layer design in this way, the route selection combines the information of the link the remaining energy. A joint function is formed by the transmit power level remaining energy. The joint function of all nodes on the path is used as the basis for route selection and applied to the route discovery stage. At the same time, the protocol introduces edge degree parameters in the establishment process, the idea of minimum energy consumption path and the introduction of energy consumption ratio parameters in the cluster skull backbone network generation process are adopted to realize the energy optimization of the path establishment process. At the same time, the protocol uses the message interaction mechanism in the path establishment process to implement a node security authentication scheme based on secret shared information without adding any routing communication messages, which effectively prevents the passive and active attacks of the attacker on the network. The results of simulation experiments prove that the secure routing protocol achieves the network’s balanced energy consumption while ensuring the secure communication of the network, and solves the energy problem.

scholarly journals A Method of Ore Blending Based on the Quality of Beneficiation and Its Application in a Concentrator

2021 ◽  
Vol 11 (11) ◽  
pp. 5092
Author(s):  
Bingyu Liu ◽  
Dingsen Zhang ◽  
Xianwen Gao
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Industrial Test ◽  
Modeling Method ◽  
Daily Work ◽  
Production Site ◽  
Neural Network Algorithm ◽  
The Relationship ◽  
Ore Dressing

Ore blending is an essential part of daily work in the concentrator. Qualified ore dressing products can make the ore dressing more smoothly. The existing ore blending modeling usually only considers the quality of ore blending products and ignores the effect of ore blending on ore dressing. This research proposes an ore blending modeling method based on the quality of the beneficiation concentrate. The relationship between the properties of ore blending products and the total concentrate recovery is fitted by the ABC-BP neural network algorithm, taken as the optimization goal to guarantee the quality of ore dressing products at the source. The ore blending system was developed and operated stably on the production site. The industrial test and actual production results have proved the effectiveness and reliability of this method.

Precision Power System Harmonic Analysis Algorithm Based on ABC-BPNN

2013 ◽  
Vol 483 ◽  
pp. 630-634
Author(s):  
Shu Chuan Gan ◽  
Ling Tang ◽  
Li Cao ◽  
Ying Gao Yue
Keyword(s):  
Neural Network ◽  
Power System ◽  
Harmonic Analysis ◽  
Bp Neural Network ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Optimal Solution ◽  
Bee Colony ◽  
Network Algorithm ◽  
Neural Network Algorithm

An algorithm of artificial colony algorithm to optimize the BP neural network algorithm was presented and used to analyze the harmonics of power system. The artificial bee colony algorithm global searching ability, convergence speed for the BP neural network algorithm for harmonic analysis is easy to fall into local optimal solution of the disadvantages, and the initial weights of the artificial bee colony algorithm also greatly enhance whole algorithm model generalization capability. This algorithm using MATLAB for Artificial bee colony algorithm and BP neural network algorithm simulation training toolbox found using artificial bee colony algorithm to optimize BP neural network algorithm converges faster results with greater accuracy, with better harmonic analysis results.

Application of BP Neural Network PID Algorithm in Refrigerated Space Temperature Control

2014 ◽  
Vol 599-601 ◽  
pp. 827-830 ◽  
Author(s):  
Wei Tian ◽  
Yi Zhun Peng ◽  
Pan Wang ◽  
Xiao Yu Wang
Keyword(s):  
Neural Network ◽  
Temperature Control ◽  
Bp Neural Network ◽  
Pid Control ◽  
Bp Algorithm ◽  
Pid Algorithm ◽  
Controller Performance ◽  
Neural Network Algorithm ◽  
Adaptive Ability ◽  
Neural Network Pid

Taking the temperature control of a refrigerated space as example, this paper designs a controller which is based on traditional PID operation and BP neural network algorithm. It has better steady-state precision and adaptive ability. Firstly, the article introduces the concepts of the refrigerated space, PID and BP algorithm. Then, the temperature control of refrigerated space is simulated in MATLAB. The PID parameters will be adjusted by simulation in BP Neural Network. The PID control parameters could be created real-time online, which makes the controller performance best.

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