Objective To correct the nonlinear error of sensor output,a new approach to sensor inverse modeling based on Back-Propagation Fuzzy Logical System(BP FS) is presented.Methods The BP FS is a computationally efficient n...Objective To correct the nonlinear error of sensor output,a new approach to sensor inverse modeling based on Back-Propagation Fuzzy Logical System(BP FS) is presented.Methods The BP FS is a computationally efficient nonlinear universal approximator,which is capable of implementing complex nonlinear mapping from its input pattern space to the output with fast convergence speed.Results The neuro-fuzzy hybrid system,i.e.BP FS,is then applied to construct nonlinear inverse model of pressure sensor.The experimental results show that the proposed inverse modeling method automatically compensates the associated nonlinear error in pressure estimation,and thus the performance of pressure sensor is significantly improved.Conclusion The proposed method can be widely used in nonlinearity correction of various kinds of sensors to compensate the effects of nonlinearity and temperature on sensor output.展开更多
The objective of this research is the presentation of a neural network capable of solving complete nonlinear algebraic systems of n equations with n unknowns. The proposed neural solver uses the classical back propaga...The objective of this research is the presentation of a neural network capable of solving complete nonlinear algebraic systems of n equations with n unknowns. The proposed neural solver uses the classical back propagation algorithm with the identity function as the output function, and supports the feature of the adaptive learning rate for the neurons of the second hidden layer. The paper presents the fundamental theory associated with this approach as well as a set of experimental results that evaluate the performance and accuracy of the proposed method against other methods found in the literature.展开更多
The problem of global stabilization by state feedback for a class of time-delay nonlinear system is considered. By constructing the appropriate Lyapunov-Krasovskii functionals (LKF) and using the backstepping design, ...The problem of global stabilization by state feedback for a class of time-delay nonlinear system is considered. By constructing the appropriate Lyapunov-Krasovskii functionals (LKF) and using the backstepping design, a linear state feedback controller making the closed-loop system globally asymptotically stable is constructed.展开更多
This paper describes the development of a knowledgebased system (KBS) for determining whether or not, and under what conditions, a bank Ioan officer should grant a business loan to a company. The prototype system deve...This paper describes the development of a knowledgebased system (KBS) for determining whether or not, and under what conditions, a bank Ioan officer should grant a business loan to a company. The prototype system developed focuses on what is bank loans risks management, how to prevent risk by the analysis of the ability of paying back loans. The paper makes the structural analysis involved in the system's decision situation, the structured situation diagram or model, dependency diagram and the document needed by the KBS prototype system thus are developed. Through testing the samples from loan business, the quality for the analysis of the ability of paying back loans can be effectively evaluated by the KBS prototype system.展开更多
The back-stepping designs based on confine functions are suggested for the robust output-feedback global stabilization of a class of nonlinear continuous systems; the proposed stabilizer is efficient for the nonlinear...The back-stepping designs based on confine functions are suggested for the robust output-feedback global stabilization of a class of nonlinear continuous systems; the proposed stabilizer is efficient for the nonlinear continuous systems confined by a bound function, the nonlinearities of the systems may be of varied forms or uncertain; the designed stabilizer is robust means that a class of nonlinear continuous systems can be stabilized by the same output feedback stabilization schemes; numerical simulation examples are given.展开更多
Because unexpected emergency owns the characteristics of explosive,uncertain evolution direction and group diffusion,more and more researchers concentrate on and try to control it. In addition,considering the force of...Because unexpected emergency owns the characteristics of explosive,uncertain evolution direction and group diffusion,more and more researchers concentrate on and try to control it. In addition,considering the force of network,the information of the unexpected emergency will be spread and enlarged rapidly on internet. It is a new viewpoint using the indicator system to estimate the heat degree of net-mediated public opinion on unexpected emergency,which can reveal the underlying reasons about the formation of the heat degree. Moreover,we use BP(Back Propagation) neural network method instead of traditional subjective weight assignment to calculate the weights of the indicators which can make evaluation results more accurate and objective.展开更多
对Aspen Flare System Analyzer在天然气化工合成氨装置火炬管网设计中的应用进行了研究。首先阐述了化工装置火炬管网设计相关专业名词;其次介绍了Aspen Flare System Analyzer软件在火炬管网中计算方法、建模设计原则及应用范围;最后...对Aspen Flare System Analyzer在天然气化工合成氨装置火炬管网设计中的应用进行了研究。首先阐述了化工装置火炬管网设计相关专业名词;其次介绍了Aspen Flare System Analyzer软件在火炬管网中计算方法、建模设计原则及应用范围;最后结合某合成氨装置火炬系统实际案例进行了分析。结果表明:工程师在应用Aspen Flare System Analyzer进行火炬管网设计时可优先根据工程经验预先给定管道尺寸,选择Rating模式计算,能够获得满足生产要求的且更为合理的火炬管网尺寸,同时可以提高火炬管网设计的效率。展开更多
A dispersion compensation method is introduced to correct the distorted image passing through an ultrathin metal film.An LCD-CCD system is modeled by the back propagation network and used to evaluate the transmittance...A dispersion compensation method is introduced to correct the distorted image passing through an ultrathin metal film.An LCD-CCD system is modeled by the back propagation network and used to evaluate the transmittance of the ultrathin metal film.Training samples for the network come from 729 images captured by shooting test patches,in which the RGB values are uniformity distributed between 0 and 255.The RGB value of the original image that will be distorted by the dispersion is first transformed by mapping from the LCD to the CCD,multiplied by the inverse matrix of the transmittance matrix,and finally transformed by mapping from the CCD to the LCD,then the corrected image is obtained.In order to verify the effectiveness of the proposed method,ultrathin aluminum films with different thicknesses are evaporated on glass substrates and laid between the CCD and LCD.Experimental results show that the proposed method compensates for the dispersion successfully.展开更多
The goal of this paper is to introduce a new neural network architecture called Sigmoid Diagonal Recurrent Neural Network (SDRNN) to be used in the adaptive control of nonlinear dynamical systems. This is done by addi...The goal of this paper is to introduce a new neural network architecture called Sigmoid Diagonal Recurrent Neural Network (SDRNN) to be used in the adaptive control of nonlinear dynamical systems. This is done by adding a sigmoid weight victor in the hidden layer neurons to adapt of the shape of the sigmoid function making their outputs not restricted to the sigmoid function output. Also, we introduce a dynamic back propagation learning algorithm to train the new proposed network parameters. The simulation results showed that the (SDRNN) is more efficient and accurate than the DRNN in both the identification and adaptive control of nonlinear dynamical systems.展开更多
Cryptographic systems are the most widely used techniques for information security. These systems however have their own pitfalls as they rely on prevention as their sole means of defense. That is why most of the orga...Cryptographic systems are the most widely used techniques for information security. These systems however have their own pitfalls as they rely on prevention as their sole means of defense. That is why most of the organizations are attracted to the intrusion detection systems. The intrusion detection systems can be broadly categorized into two types, Anomaly and Misuse Detection systems. An anomaly-based system detects com-puter intrusions and misuse by monitoring system activity and classifying it as either normal or anomalous. Misuse detection systems can detect almost all known attack patterns;they however are hardly of any use to de-tect yet unknown attacks. In this paper, we use Neural Networks for detecting intrusive web documents avail-able on Internet. For this purpose Back Propagation Neural (BPN) Network architecture is applied that is one of the most popular network architectures for supervised learning. Analysis is carried out on Internet Security and Acceleration (ISA) server 2000 log for finding out the web documents that should not be accessed by the unau-thorized persons in an organization. There are lots of web documents available online on Internet that may be harmful for an organization. Most of these documents are blocked for use, but still users of the organization try to access these documents and may cause problem in the organization network.展开更多
基金This work was supported by National Natural Science Foundation of China(No.60276037).
文摘Objective To correct the nonlinear error of sensor output,a new approach to sensor inverse modeling based on Back-Propagation Fuzzy Logical System(BP FS) is presented.Methods The BP FS is a computationally efficient nonlinear universal approximator,which is capable of implementing complex nonlinear mapping from its input pattern space to the output with fast convergence speed.Results The neuro-fuzzy hybrid system,i.e.BP FS,is then applied to construct nonlinear inverse model of pressure sensor.The experimental results show that the proposed inverse modeling method automatically compensates the associated nonlinear error in pressure estimation,and thus the performance of pressure sensor is significantly improved.Conclusion The proposed method can be widely used in nonlinearity correction of various kinds of sensors to compensate the effects of nonlinearity and temperature on sensor output.
文摘The objective of this research is the presentation of a neural network capable of solving complete nonlinear algebraic systems of n equations with n unknowns. The proposed neural solver uses the classical back propagation algorithm with the identity function as the output function, and supports the feature of the adaptive learning rate for the neurons of the second hidden layer. The paper presents the fundamental theory associated with this approach as well as a set of experimental results that evaluate the performance and accuracy of the proposed method against other methods found in the literature.
基金Supported by the "973" Project of P. R. China (G1998020300)
文摘The problem of global stabilization by state feedback for a class of time-delay nonlinear system is considered. By constructing the appropriate Lyapunov-Krasovskii functionals (LKF) and using the backstepping design, a linear state feedback controller making the closed-loop system globally asymptotically stable is constructed.
基金Supported by the National Science Foundation of China(No.7977086)
文摘This paper describes the development of a knowledgebased system (KBS) for determining whether or not, and under what conditions, a bank Ioan officer should grant a business loan to a company. The prototype system developed focuses on what is bank loans risks management, how to prevent risk by the analysis of the ability of paying back loans. The paper makes the structural analysis involved in the system's decision situation, the structured situation diagram or model, dependency diagram and the document needed by the KBS prototype system thus are developed. Through testing the samples from loan business, the quality for the analysis of the ability of paying back loans can be effectively evaluated by the KBS prototype system.
基金This project was supported by the National Natural Science Foundation of China(69974017 60274020 60128303)
文摘The back-stepping designs based on confine functions are suggested for the robust output-feedback global stabilization of a class of nonlinear continuous systems; the proposed stabilizer is efficient for the nonlinear continuous systems confined by a bound function, the nonlinearities of the systems may be of varied forms or uncertain; the designed stabilizer is robust means that a class of nonlinear continuous systems can be stabilized by the same output feedback stabilization schemes; numerical simulation examples are given.
基金supported by the National Natural Science Foundation of China (Grant No. 90924029)
文摘Because unexpected emergency owns the characteristics of explosive,uncertain evolution direction and group diffusion,more and more researchers concentrate on and try to control it. In addition,considering the force of network,the information of the unexpected emergency will be spread and enlarged rapidly on internet. It is a new viewpoint using the indicator system to estimate the heat degree of net-mediated public opinion on unexpected emergency,which can reveal the underlying reasons about the formation of the heat degree. Moreover,we use BP(Back Propagation) neural network method instead of traditional subjective weight assignment to calculate the weights of the indicators which can make evaluation results more accurate and objective.
文摘对Aspen Flare System Analyzer在天然气化工合成氨装置火炬管网设计中的应用进行了研究。首先阐述了化工装置火炬管网设计相关专业名词;其次介绍了Aspen Flare System Analyzer软件在火炬管网中计算方法、建模设计原则及应用范围;最后结合某合成氨装置火炬系统实际案例进行了分析。结果表明:工程师在应用Aspen Flare System Analyzer进行火炬管网设计时可优先根据工程经验预先给定管道尺寸,选择Rating模式计算,能够获得满足生产要求的且更为合理的火炬管网尺寸,同时可以提高火炬管网设计的效率。
基金Project supported by the National High Technology Research and Development Program of China (Grant No. 2009AA044001)the Open Funds of the State Key Laboratory of Robotics and Systems (HIT),China (Grant No. SKLRS-2010-MS-01)the Fundamental Research Funds for the Central Universities,China
文摘A dispersion compensation method is introduced to correct the distorted image passing through an ultrathin metal film.An LCD-CCD system is modeled by the back propagation network and used to evaluate the transmittance of the ultrathin metal film.Training samples for the network come from 729 images captured by shooting test patches,in which the RGB values are uniformity distributed between 0 and 255.The RGB value of the original image that will be distorted by the dispersion is first transformed by mapping from the LCD to the CCD,multiplied by the inverse matrix of the transmittance matrix,and finally transformed by mapping from the CCD to the LCD,then the corrected image is obtained.In order to verify the effectiveness of the proposed method,ultrathin aluminum films with different thicknesses are evaporated on glass substrates and laid between the CCD and LCD.Experimental results show that the proposed method compensates for the dispersion successfully.
文摘The goal of this paper is to introduce a new neural network architecture called Sigmoid Diagonal Recurrent Neural Network (SDRNN) to be used in the adaptive control of nonlinear dynamical systems. This is done by adding a sigmoid weight victor in the hidden layer neurons to adapt of the shape of the sigmoid function making their outputs not restricted to the sigmoid function output. Also, we introduce a dynamic back propagation learning algorithm to train the new proposed network parameters. The simulation results showed that the (SDRNN) is more efficient and accurate than the DRNN in both the identification and adaptive control of nonlinear dynamical systems.
文摘Cryptographic systems are the most widely used techniques for information security. These systems however have their own pitfalls as they rely on prevention as their sole means of defense. That is why most of the organizations are attracted to the intrusion detection systems. The intrusion detection systems can be broadly categorized into two types, Anomaly and Misuse Detection systems. An anomaly-based system detects com-puter intrusions and misuse by monitoring system activity and classifying it as either normal or anomalous. Misuse detection systems can detect almost all known attack patterns;they however are hardly of any use to de-tect yet unknown attacks. In this paper, we use Neural Networks for detecting intrusive web documents avail-able on Internet. For this purpose Back Propagation Neural (BPN) Network architecture is applied that is one of the most popular network architectures for supervised learning. Analysis is carried out on Internet Security and Acceleration (ISA) server 2000 log for finding out the web documents that should not be accessed by the unau-thorized persons in an organization. There are lots of web documents available online on Internet that may be harmful for an organization. Most of these documents are blocked for use, but still users of the organization try to access these documents and may cause problem in the organization network.
