In order to improve the prediction accuracy and test the generalization ability of the dam deformation analysis model, the back-propagation（BP） neural network model for dam deformation analysis is studied, and the m...In order to improve the prediction accuracy and test the generalization ability of the dam deformation analysis model, the back-propagation（BP） neural network model for dam deformation analysis is studied, and the merging model is built based on the neural network BP algorithm and the traditional statistical model. The three models mentioned above are calculated and analyzed according to the long-term deformation observation data in Chencun Dam. The analytical results show that the average prediction accuracies of the statistical model and the BP neural network model are ~ 0.477 and ＋- 0.390 mm, respectively, while the prediction accuracy of the merging model is ~0. 318 mm, which is improved by 33% and 18% compared to the other two models, respectively. And the merging model has a better generalization ability and broad applicability.展开更多
Before any rock engineering project,mechanical parameters of rocks such as uniaxial compressive strength and young modulus of intact rock get measured using laboratory or in-situ tests,but in some situations preparing...Before any rock engineering project,mechanical parameters of rocks such as uniaxial compressive strength and young modulus of intact rock get measured using laboratory or in-situ tests,but in some situations preparing the required specimens is impossible.By this time,several models have been established to evaluate UCS and E from rock substantial properties.Artificial neural networks are powerful tools which are employed to establish predictive models and results have shown the priority of this technique compared to classic statistical techniques.In this paper,ANN and multivariate statistical models considering rock textural characteristics have been established to estimate UCS of rock and to validate the responses of the established models,they were compared with laboratory results.For this purpose a data set for 44 samples of sandstone was prepared and for each sample some textural characteristics such as void,mineral content and grain size as well as UCS were determined.To select the best predictors as inputs of the UCS models,this data set was subjected to statistical analyses comprising basic descriptive statistics,bivariate correlation,curve fitting and principal component analyses.Results of such analyses have shown that void,ferroan calcitic cement,argillaceous cement and mica percentage have the most effect on USC.Two predictive models for UCS were developed using these variables by ANN and linear multivariate regression.Results have shown that by using simple textural characteristics such as mineral content,cement type and void,strength of studied sandstone can be estimated with acceptable accuracy.ANN and multivariate statistical UCS models,revealed responses with 0.87 and 0.76 regressions,respectively which proves higher potential of ANN model for predicting UCS compared to classic statistical models.展开更多
Top-k ranking of websites according to traffic volume is important for Internet Service Providers(ISPs) to understand network status and optimize network resources. However, the ranking result always has a big deviati...Top-k ranking of websites according to traffic volume is important for Internet Service Providers(ISPs) to understand network status and optimize network resources. However, the ranking result always has a big deviation with actual rank for the existence of unknown web traffic, which cannot be identified accurately under current techniques. In this paper, we introduce a novel method to approximate the actual rank. This method associates unknown web traffic with websites according to statistical probabilities. Then, we construct a probabilistic top-k query model to rank websites. We conduct several experiments by using real HTTP traffic traces collected from a commercial ISP covering an entire city in northern China. Experimental results show that the proposed techniques can reduce the deviation existing between the ground truth and the ranking results vastly. In addition, we find that the websites providing video service have higher ratio of unknown IP as well as higher ratio of unknown traffic than the websites providing text web page service. Specifically, we find that the top-3 video websites have more than 90% of unknown web traffic. All these findings are helpful for ISPs understanding network status and deploying Content Distributed Network(CDN).展开更多
Aiming at the application of a wireless sensor network to locating miners in underground mine,we design a wireless sensor network location node system,considering the communication performance and the intrinsic safety...Aiming at the application of a wireless sensor network to locating miners in underground mine,we design a wireless sensor network location node system,considering the communication performance and the intrinsic safety. The location node system consists of a mobile node,several fixed nodes,and a sink node,all of whose circuits were designed based on CC2430. A varistor and a RC circuit were used in the reset circuit of a sensor node to guarantee the intrinsic safety by reducing discharge energy,the theoretical analysis of the discharge energy shows that the reset circuit is an intrinsic safety one. The analysis and simulation about the performance of the location node system are discussed,such as network communication delay and packet loss rate,the results show that the highest network communication delay of the system is about 0.11 seconds,and the highest packet loss rate is about 0.13,which assures the location node system has a high reliability,and can locate miners in the underground mine.展开更多
It is known that packet collisions in wireless networks will deteriorate system performance, hence substantial efforts have been made to avoid collision in multi-user access designs. Also, there have been many studies...It is known that packet collisions in wireless networks will deteriorate system performance, hence substantial efforts have been made to avoid collision in multi-user access designs. Also, there have been many studies on throughput analysis of CSMA wireless networks. However, for a typical CSMA network in which not all nodes can sense each other, it is still not well investigated how link throughputs are affected by collisions. We note that in practical 802.11-like networks, the time is divided into mini-timeslots and packet collisions are in fact unavoidable. Thus, it is desirable to move forward to explore how collisions in such a network will affect system performance. Based on the collision-free ideal CSMA network(ICN) model, this paper attempts to analyze link throughputs when taking the backoff collisions into account and examine the effect of collisions on link throughputs. Specifically, we propose an Extended Ideal CSMA Network(EICN) model to characterize the collision effects as well as the interactions and dependency among links in the network. Based on EICN, we could directly compute link throughputs and collision probabilities. Simulations show that the EICN model is of high accuracy. Under various network topologies and protocol parameter settings, the computation error of link throughputs using EICN is kept to 4% or below. Interestingly, we find that unlike expected, the effect of collisions on link throughputs in a modest CSMA wireless network is not significant, which enriches our understanding on practical CSMA wireless networks such as Wi-Fi.展开更多
A comprehensive quantification method of fatigue degree is proposed concerning subjective and objective quantifications.Using the fatigue degree test software,fatigue degree is objectively quantified by analyzing the ...A comprehensive quantification method of fatigue degree is proposed concerning subjective and objective quantifications.Using the fatigue degree test software,fatigue degree is objectively quantified by analyzing the reaction and operation abilities of drivers about traffic signals.By comparison experiment with that EEG signal based,multivariate statistical analysis and fusion identification based on BP neural network(BPNN) results show that the experimental procedure is simple and practical,and the proposed method can reveal the correlation between fatigue feature parameters and fatigue degree in theory,and also can achieve accurate and reliable quantification of fatigue degree,especially under the associated action of multiple fatigue feature parameters.展开更多
In order to meet the requirement of network synthesis optimization design for a micro component, a three-level information frame and functional module based on web was proposed. Firstly, the finite element method （FE...In order to meet the requirement of network synthesis optimization design for a micro component, a three-level information frame and functional module based on web was proposed. Firstly, the finite element method （FEM） was used to analyze the dynamic property of coupled-energy-domain of virtual prototype instances and to obtain some optimal information data. Secondly, the rough set theory （RST） and the genetic algorithm （GA） were used to work out the reduction of attributes and the acquisition of principle of optimality and to confirm key variable and restriction condition in the synthesis optimization design. Finally, the regression analysis （RA） and GA were used to establish the synthesis optimization design model and carry on the optimization design. A corresponding prototype system was also developed and the synthesis optimization design of a thermal actuated micro-pump was carded out as a demonstration in this paper.展开更多
基金The Scientific Innovation Research of College Graduates in Jiangsu Province(No.CXLX11_0143)
文摘In order to improve the prediction accuracy and test the generalization ability of the dam deformation analysis model, the back-propagation（BP） neural network model for dam deformation analysis is studied, and the merging model is built based on the neural network BP algorithm and the traditional statistical model. The three models mentioned above are calculated and analyzed according to the long-term deformation observation data in Chencun Dam. The analytical results show that the average prediction accuracies of the statistical model and the BP neural network model are ~ 0.477 and ＋- 0.390 mm, respectively, while the prediction accuracy of the merging model is ~0. 318 mm, which is improved by 33% and 18% compared to the other two models, respectively. And the merging model has a better generalization ability and broad applicability.
文摘Before any rock engineering project,mechanical parameters of rocks such as uniaxial compressive strength and young modulus of intact rock get measured using laboratory or in-situ tests,but in some situations preparing the required specimens is impossible.By this time,several models have been established to evaluate UCS and E from rock substantial properties.Artificial neural networks are powerful tools which are employed to establish predictive models and results have shown the priority of this technique compared to classic statistical techniques.In this paper,ANN and multivariate statistical models considering rock textural characteristics have been established to estimate UCS of rock and to validate the responses of the established models,they were compared with laboratory results.For this purpose a data set for 44 samples of sandstone was prepared and for each sample some textural characteristics such as void,mineral content and grain size as well as UCS were determined.To select the best predictors as inputs of the UCS models,this data set was subjected to statistical analyses comprising basic descriptive statistics,bivariate correlation,curve fitting and principal component analyses.Results of such analyses have shown that void,ferroan calcitic cement,argillaceous cement and mica percentage have the most effect on USC.Two predictive models for UCS were developed using these variables by ANN and linear multivariate regression.Results have shown that by using simple textural characteristics such as mineral content,cement type and void,strength of studied sandstone can be estimated with acceptable accuracy.ANN and multivariate statistical UCS models,revealed responses with 0.87 and 0.76 regressions,respectively which proves higher potential of ANN model for predicting UCS compared to classic statistical models.
基金supported by 111 Project of China under Grant No.B08004
文摘Top-k ranking of websites according to traffic volume is important for Internet Service Providers(ISPs) to understand network status and optimize network resources. However, the ranking result always has a big deviation with actual rank for the existence of unknown web traffic, which cannot be identified accurately under current techniques. In this paper, we introduce a novel method to approximate the actual rank. This method associates unknown web traffic with websites according to statistical probabilities. Then, we construct a probabilistic top-k query model to rank websites. We conduct several experiments by using real HTTP traffic traces collected from a commercial ISP covering an entire city in northern China. Experimental results show that the proposed techniques can reduce the deviation existing between the ground truth and the ranking results vastly. In addition, we find that the websites providing video service have higher ratio of unknown IP as well as higher ratio of unknown traffic than the websites providing text web page service. Specifically, we find that the top-3 video websites have more than 90% of unknown web traffic. All these findings are helpful for ISPs understanding network status and deploying Content Distributed Network(CDN).
基金Projects 20070411065 supported by the China Postdoctoral Science Foundation0801028B by the Jiangsu Postdoctoral Science Research Foundation
文摘Aiming at the application of a wireless sensor network to locating miners in underground mine,we design a wireless sensor network location node system,considering the communication performance and the intrinsic safety. The location node system consists of a mobile node,several fixed nodes,and a sink node,all of whose circuits were designed based on CC2430. A varistor and a RC circuit were used in the reset circuit of a sensor node to guarantee the intrinsic safety by reducing discharge energy,the theoretical analysis of the discharge energy shows that the reset circuit is an intrinsic safety one. The analysis and simulation about the performance of the location node system are discussed,such as network communication delay and packet loss rate,the results show that the highest network communication delay of the system is about 0.11 seconds,and the highest packet loss rate is about 0.13,which assures the location node system has a high reliability,and can locate miners in the underground mine.
基金partially supported by the National Natural Science Foundation of China under Grant 61571178,Grant 61771315 and Grant 61501160
文摘It is known that packet collisions in wireless networks will deteriorate system performance, hence substantial efforts have been made to avoid collision in multi-user access designs. Also, there have been many studies on throughput analysis of CSMA wireless networks. However, for a typical CSMA network in which not all nodes can sense each other, it is still not well investigated how link throughputs are affected by collisions. We note that in practical 802.11-like networks, the time is divided into mini-timeslots and packet collisions are in fact unavoidable. Thus, it is desirable to move forward to explore how collisions in such a network will affect system performance. Based on the collision-free ideal CSMA network(ICN) model, this paper attempts to analyze link throughputs when taking the backoff collisions into account and examine the effect of collisions on link throughputs. Specifically, we propose an Extended Ideal CSMA Network(EICN) model to characterize the collision effects as well as the interactions and dependency among links in the network. Based on EICN, we could directly compute link throughputs and collision probabilities. Simulations show that the EICN model is of high accuracy. Under various network topologies and protocol parameter settings, the computation error of link throughputs using EICN is kept to 4% or below. Interestingly, we find that unlike expected, the effect of collisions on link throughputs in a modest CSMA wireless network is not significant, which enriches our understanding on practical CSMA wireless networks such as Wi-Fi.
基金Supported by the National Nature Science Foundation of China(No.61304205,61203273,61103086,41301037)the Open Funding Project of State Key Laboratory of Virtual Reality Technology and Systems,Beihang University(No.BUAA-VR-13KF-04)+1 种基金Jiangsu Ordinary University Science Research Project(No.13KJB120007)Innovation and Entrepreneurship Training Project of College Students(No.201410300153,201410300165)
文摘A comprehensive quantification method of fatigue degree is proposed concerning subjective and objective quantifications.Using the fatigue degree test software,fatigue degree is objectively quantified by analyzing the reaction and operation abilities of drivers about traffic signals.By comparison experiment with that EEG signal based,multivariate statistical analysis and fusion identification based on BP neural network(BPNN) results show that the experimental procedure is simple and practical,and the proposed method can reveal the correlation between fatigue feature parameters and fatigue degree in theory,and also can achieve accurate and reliable quantification of fatigue degree,especially under the associated action of multiple fatigue feature parameters.
基金Projects 50375118,5014006 supported by the National Natural Science Foundation of China
文摘In order to meet the requirement of network synthesis optimization design for a micro component, a three-level information frame and functional module based on web was proposed. Firstly, the finite element method （FEM） was used to analyze the dynamic property of coupled-energy-domain of virtual prototype instances and to obtain some optimal information data. Secondly, the rough set theory （RST） and the genetic algorithm （GA） were used to work out the reduction of attributes and the acquisition of principle of optimality and to confirm key variable and restriction condition in the synthesis optimization design. Finally, the regression analysis （RA） and GA were used to establish the synthesis optimization design model and carry on the optimization design. A corresponding prototype system was also developed and the synthesis optimization design of a thermal actuated micro-pump was carded out as a demonstration in this paper.
