In order to accurately and quickly identify the safety status pattern of coalmines,a new safety status pattern recognition method based on the extension neural network (ENN) was proposed,and the design of structure of...In order to accurately and quickly identify the safety status pattern of coalmines,a new safety status pattern recognition method based on the extension neural network (ENN) was proposed,and the design of structure of network,the rationale of recognition algorithm and the performance of proposed method were discussed in detail.The safety status pattern recognition problem of coalmines can be regard as a classification problem whose features are defined in a range,so using the ENN is most appropriate for this problem.The ENN-based recognition method can use a novel extension distance to measure the similarity between the object to be recognized and the class centers.To demonstrate the effectiveness of the proposed method,a real-world application on the geological safety status pattern recognition of coalmines was tested.Comparative experiments with existing method and other traditional ANN-based methods were conducted.The experimental results show that the proposed ENN-based recognition method can identify the safety status pattern of coalmines accurately with shorter learning time and simpler structure.The experimental results also confirm that the proposed method has a better performance in recognition accuracy,generalization ability and fault-tolerant ability,which are very useful in recognizing the safety status pattern in the process of coal production.展开更多
The paper design hardware platform based on network node, and analyze ZigBee protocol architecture and standards of each layer; on based of ZigBee protocol stack, we design the application program of network coordinat...The paper design hardware platform based on network node, and analyze ZigBee protocol architecture and standards of each layer; on based of ZigBee protocol stack, we design the application program of network coordinator and terminal node to realize the data acquisition; design of network system has the characteristics of low cost, small volume, test results show that the mesh topology, network support, can be rapidly deployed, temperature, humidity, light intensity information of the smooth reading environment, that can be used for domestic environmental monitoring field.展开更多
Agricultural system is very complex since it deals with large data situation which comes from a number of factors. A lot of techniques and approaches have been used to identify any interactions between factors that af...Agricultural system is very complex since it deals with large data situation which comes from a number of factors. A lot of techniques and approaches have been used to identify any interactions between factors that affecting yields with the crop performances. The application of neural network to the task of solving non-linear and complex systems is promising. This paper presents a review on the use of artificial neural network （ANN） in predicting crop yield using various crop performance factors. General overview on the application of ANN and the basic concept of neural network architecture are also presented. From the literature, it has been shown that ANN provides better interpretation of crop variability compared to the other methods.展开更多
This paper proposes a Back Propagation (BP) neural network with momentum enhancement aiming to achieving the smooth convergence for aggregate volumetric estimation purpose. Network inputs are first selected by optical...This paper proposes a Back Propagation (BP) neural network with momentum enhancement aiming to achieving the smooth convergence for aggregate volumetric estimation purpose. Network inputs are first selected by optically measuring the eight geometry-related parameters from the given particle image. To simplify the network structure, principal component analysis technique is applied to reduce the input dimension. The specific network structure is finalized based on both empirical expertise and analysis on selecting the appropriate number of neurons in hidden layer. The network is trained using the finite number of randomly-picked particles. The training and test results suggest that, compared to the generic BP network, the training duration of the proposed neural network is greatly attenuated, the complexity of the network structure is largely reduced, and the estimation precision is within 2%, being sufficiently up to technical satisfaction.展开更多
In this study, a Multi-Layer BP neural network(MLBP) with dynamic thresholds is employed to build a classifier model.As to the design of the neural network structure, theoretical guidance and plentiful experiments are...In this study, a Multi-Layer BP neural network(MLBP) with dynamic thresholds is employed to build a classifier model.As to the design of the neural network structure, theoretical guidance and plentiful experiments are combined to optimize the hidden layers' parameters which include the number of hidden layers and their node numbers.The classifier with dynamic thresholds is used to standardize the output for the first time, and it improves the robustness of the model to a high level.Finally, the classifier is applied to forecast box office revenue of a movie before its theatrical release.The comparison results with the MLP method show that the MLBP classifier model achieves more satisfactory results, and it is more reliable and effective to solve the problem.展开更多
There is an increasing number of Internet applications, which leads to an increasing network capacity and availability. Internet traffic characterisation and application identification are, therefore, more important f...There is an increasing number of Internet applications, which leads to an increasing network capacity and availability. Internet traffic characterisation and application identification are, therefore, more important for efficient network management. In this paper, we construct flow graphs from detailed Internet traffic data collected from the public networks of Internet Service Providers. We analyse the community structures of the flow graph that is naturally formed by different applications. The community size, degree distribution of the community, and community overlap of 10 Internet applications are investigated. We further study the correlations between the communities from different applications. Our results provide deep insights into the behaviour Internet applications and traffic, which is helpful for both network management and user behaviour analysis.展开更多
This research is a development in management information system （MIS） planning based on operation analysis and development according to concurrent engineering approach and reestablishment of database management. Acc...This research is a development in management information system （MIS） planning based on operation analysis and development according to concurrent engineering approach and reestablishment of database management. According to our case study industry, such industry currently used traditional network systems such as LAN, and ＂Bus Network＂ Network Topology. Client/Server distributed computing has a problem with database management in data redundancy, data inconsistency, and data independency. For Network Topology, Bus Network has problem with multitasking since the network are able to handle only a set of data at a time so the traffic problem will occur when multiple users request for the service. Thus, such condition is inconsistent with concurrent engineering which must be able to access the data simultaneously. As a consequence, this study develops a network system, network system of working system, using LAN and ＂Star Network＂ network topology. The file server processing distributed is an application while database is stored in host computer or file server but the data will be processed in users＇ computer. When the user needs to access the data, file server will send it to the user and the user can further analysis or manage such data in the user computer, so called ＂Hierarchical Database Model＂. Hierarchical database structure is easily developed like general organization command structure with different level of responsibility. In details, the data level in the database is divided into three levels including DBI, DB2, and DB3, so development of simultaneously systemic flow and access of various critical data is performed in parallel. Furthermore, this is consistent with access of all three data levels including： Level 1 is overall dataflow of both inside and outside the organization; Level 2 is dataflow of each division in the organization; and Level 3 is dataflow of subunit in each division in the organization. After systemize flow and access of data with concurrent engineering as mentioned, it provided optimal efficiency in the whole production system management reducing loss in the whole system of the organization展开更多
基金Project(107021) supported by the Key Foundation of Chinese Ministry of Education Project(2009643013) supported by China Scholarship Fund
文摘In order to accurately and quickly identify the safety status pattern of coalmines,a new safety status pattern recognition method based on the extension neural network (ENN) was proposed,and the design of structure of network,the rationale of recognition algorithm and the performance of proposed method were discussed in detail.The safety status pattern recognition problem of coalmines can be regard as a classification problem whose features are defined in a range,so using the ENN is most appropriate for this problem.The ENN-based recognition method can use a novel extension distance to measure the similarity between the object to be recognized and the class centers.To demonstrate the effectiveness of the proposed method,a real-world application on the geological safety status pattern recognition of coalmines was tested.Comparative experiments with existing method and other traditional ANN-based methods were conducted.The experimental results show that the proposed ENN-based recognition method can identify the safety status pattern of coalmines accurately with shorter learning time and simpler structure.The experimental results also confirm that the proposed method has a better performance in recognition accuracy,generalization ability and fault-tolerant ability,which are very useful in recognizing the safety status pattern in the process of coal production.
文摘The paper design hardware platform based on network node, and analyze ZigBee protocol architecture and standards of each layer; on based of ZigBee protocol stack, we design the application program of network coordinator and terminal node to realize the data acquisition; design of network system has the characteristics of low cost, small volume, test results show that the mesh topology, network support, can be rapidly deployed, temperature, humidity, light intensity information of the smooth reading environment, that can be used for domestic environmental monitoring field.
文摘Agricultural system is very complex since it deals with large data situation which comes from a number of factors. A lot of techniques and approaches have been used to identify any interactions between factors that affecting yields with the crop performances. The application of neural network to the task of solving non-linear and complex systems is promising. This paper presents a review on the use of artificial neural network （ANN） in predicting crop yield using various crop performance factors. General overview on the application of ANN and the basic concept of neural network architecture are also presented. From the literature, it has been shown that ANN provides better interpretation of crop variability compared to the other methods.
基金Funded by Ningbo Natural Science Foundation (No. 2006A610016)Foundation of National Education Ministry for Returned Overseas Chinese Students & Scholars (SRF for ROCS, SEM. No.2006699)
文摘This paper proposes a Back Propagation (BP) neural network with momentum enhancement aiming to achieving the smooth convergence for aggregate volumetric estimation purpose. Network inputs are first selected by optically measuring the eight geometry-related parameters from the given particle image. To simplify the network structure, principal component analysis technique is applied to reduce the input dimension. The specific network structure is finalized based on both empirical expertise and analysis on selecting the appropriate number of neurons in hidden layer. The network is trained using the finite number of randomly-picked particles. The training and test results suggest that, compared to the generic BP network, the training duration of the proposed neural network is greatly attenuated, the complexity of the network structure is largely reduced, and the estimation precision is within 2%, being sufficiently up to technical satisfaction.
基金Supported by National Natural Science Foundation of China (No. 60573172)
文摘In this study, a Multi-Layer BP neural network(MLBP) with dynamic thresholds is employed to build a classifier model.As to the design of the neural network structure, theoretical guidance and plentiful experiments are combined to optimize the hidden layers' parameters which include the number of hidden layers and their node numbers.The classifier with dynamic thresholds is used to standardize the output for the first time, and it improves the robustness of the model to a high level.Finally, the classifier is applied to forecast box office revenue of a movie before its theatrical release.The comparison results with the MLP method show that the MLBP classifier model achieves more satisfactory results, and it is more reliable and effective to solve the problem.
基金supported by the National Natural Science Foundation of Chinaunder Grant No.61171098the Fundamental Research Funds for the Central Universities of Chinathe 111 Project of China under Grant No.B08004
文摘There is an increasing number of Internet applications, which leads to an increasing network capacity and availability. Internet traffic characterisation and application identification are, therefore, more important for efficient network management. In this paper, we construct flow graphs from detailed Internet traffic data collected from the public networks of Internet Service Providers. We analyse the community structures of the flow graph that is naturally formed by different applications. The community size, degree distribution of the community, and community overlap of 10 Internet applications are investigated. We further study the correlations between the communities from different applications. Our results provide deep insights into the behaviour Internet applications and traffic, which is helpful for both network management and user behaviour analysis.
文摘This research is a development in management information system （MIS） planning based on operation analysis and development according to concurrent engineering approach and reestablishment of database management. According to our case study industry, such industry currently used traditional network systems such as LAN, and ＂Bus Network＂ Network Topology. Client/Server distributed computing has a problem with database management in data redundancy, data inconsistency, and data independency. For Network Topology, Bus Network has problem with multitasking since the network are able to handle only a set of data at a time so the traffic problem will occur when multiple users request for the service. Thus, such condition is inconsistent with concurrent engineering which must be able to access the data simultaneously. As a consequence, this study develops a network system, network system of working system, using LAN and ＂Star Network＂ network topology. The file server processing distributed is an application while database is stored in host computer or file server but the data will be processed in users＇ computer. When the user needs to access the data, file server will send it to the user and the user can further analysis or manage such data in the user computer, so called ＂Hierarchical Database Model＂. Hierarchical database structure is easily developed like general organization command structure with different level of responsibility. In details, the data level in the database is divided into three levels including DBI, DB2, and DB3, so development of simultaneously systemic flow and access of various critical data is performed in parallel. Furthermore, this is consistent with access of all three data levels including： Level 1 is overall dataflow of both inside and outside the organization; Level 2 is dataflow of each division in the organization; and Level 3 is dataflow of subunit in each division in the organization. After systemize flow and access of data with concurrent engineering as mentioned, it provided optimal efficiency in the whole production system management reducing loss in the whole system of the organization
