In this paper,we delve into the problem of exponential stability for a coupled system of a one-dimensional(1-D)N-root wave network with boundary delays.Our aim is to establish a universal controller design strategy,wh...In this paper,we delve into the problem of exponential stability for a coupled system of a one-dimensional(1-D)N-root wave network with boundary delays.Our aim is to establish a universal controller design strategy,where the designed controller must guarantee the stability of the closed-loop system.The research approach undertaken in this paper assumes that the system state is known.We employ an integral-type feedback controller to achieve system stability,where the integral kernel function serves as a parameter.We attempt to select the corresponding exponentially stable system as the target system,and then construct a bounded linear transformation to demonstrate the equivalence between the target system and the original system,thereby eliminating the adverse effects of time delays on the system.The crux lies in determining the equation that the kernel function must satisfy.Herein,we primarily present a methodology for selecting the parameter function within this transformation,to achieve an exponentially stable feedback controller.展开更多
The networks-on-chip （NoC） communication has an increasingly larger impact on the system power consumption and performance. Emerging technologies, like surface wave, are believed to have lower transmission latency a...The networks-on-chip （NoC） communication has an increasingly larger impact on the system power consumption and performance. Emerging technologies, like surface wave, are believed to have lower transmission latency and power consumption over the conventional wireless NoC. Therefore, this paper studies how to optimize the network performance and power consumption by giving the packet-switching fabric and traffic pattern of each application. Compared with the conventional method of wire-linked, which adds wireless transceivers by using the genetic algorithm （GA）, the proposed maximal declining sorting algorithm （MDSA） can effectively reduce time consumption by as much as 20.4% to 35.6%. We also evaluate the power consumption and configuration time to prove the effective of the proposed algorithm.展开更多
The directional neighbor discovery problem,i.e,spatial rendezvous,is a fundamental problem in millimeter wave(mmWave)wireless networks,where directional transmissions are used to overcome the high attenuation.The chal...The directional neighbor discovery problem,i.e,spatial rendezvous,is a fundamental problem in millimeter wave(mmWave)wireless networks,where directional transmissions are used to overcome the high attenuation.The challenge is how to let the transmitter and the receiver beams meet in space under deafness caused by directional transmission and reception,where no control channel,prior information,and coordination are available.In this paper,we present a Hunting based Directional Neighbor Discovery(HDND)scheme for ad hoc mmWave networks,where a node follows a unique sequence to determine its transmission or reception mode,and continuously r0-tates its directional beam to scan the neighborhood for other mmWave nodes.Through a rigorous analysis,we derive the conditions for ensured neighbor discovery,as well as a bound for the worst-case discovery time and the impact of sidelobes.We validate the analysis with extensive simulations and demonstrate the superior perfor-mance of the proposed scheme over several baseline schemes.展开更多
An approach based on artificial neural network （ANN） is used to develop predictive relations between hydrodynamic inline force on a vertical cylinder and some effective parameters. The data used to calibrate and val...An approach based on artificial neural network （ANN） is used to develop predictive relations between hydrodynamic inline force on a vertical cylinder and some effective parameters. The data used to calibrate and validate the ANN models are obtained from an experiment. Multilayer feed-forward neural networks that are trained with the back-propagation algorithm are constructed by use of three design parameters （i.e. wave surface height, horizontal and vertical velocities） as network inputs and the ultimate inline force as the only output. A sensitivity analysis is conducted on the ANN models to investigate the generalization ability （robustness） of the developed models, and predictions from the ANN models are compared to those obtained from Morison equation which is usually used to determine inline force as a computational method. With the existing data, it is found that least square method （LSM） gives less error in determining drag and inertia coefficients of Morison equation. With regard to the predicted results agreeing with calculations achieved from Morison equation that used LSM method, neural network has high efficiency considering its convenience, simplicity and promptitude. The outcome of this study can contribute to reducing the errors in predicting hydrodynamic inline force by use of ANN and to improve the reliability of that in comparison with the more practical state of Morison equation. Therefore, this method can be applied to relevant engineering projects with satisfactory results展开更多
Millimeter-wave(mmWave) communications are highly focused as a powerful mean enabling to perform very high data transmission. However it has several inherent shortcomings like directional transmission and serious atte...Millimeter-wave(mmWave) communications are highly focused as a powerful mean enabling to perform very high data transmission. However it has several inherent shortcomings like directional transmission and serious attenuation in atmosphere. So it is difficult to implement random access in mm Wave WLANs. In this paper, a heterogeneous control and data sub-network architecture is presented, which decouples the traditional WLAN into 2.4 or 5GHz control sub-network and mm Wave data sub-network in both PHY and MAC layers. In control sub-network, DCF is adopted to transmit control information and in data sub-network, PCF is adopted to ensure the Qo S. Moreover, an omnidirectional transmission is employed in the control sub-network to support users' random access. The data sub-network only covers the required serving area by using directional antennas for specific users and can be adjusted dynamically based on control information. Simulations indicate that compared with the conventional WLANs, heterogeneous mm Wave WLANs can provide both random access and high throughput.展开更多
Shear wave velocity has numerous applications in geomechanical, petrophysical and geophysical studies of hydrocarbon reserves. However, data related to shear wave velocity isn’t available for all wells, especially ol...Shear wave velocity has numerous applications in geomechanical, petrophysical and geophysical studies of hydrocarbon reserves. However, data related to shear wave velocity isn’t available for all wells, especially old wells and it is very important to estimate this parameter using other well logging. Hence, lots of methods have been developed to estimate these data using other available information of reservoir. In this study, after processing and removing inappropriate petrophysical data, we estimated petrophysical properties affecting shear wave velocity of the reservoir and statistical methods were used to establish relationship between effective petrophysical properties and shear wave velocity. To predict (VS), first we used empirical relationships and then multivariate regression methods and neural networks were used. Multiple regression method is a powerful method that uses correlation between available information and desired parameter. Using this method, we can identify parameters affecting estimation of shear wave velocity. Neural networks can also be trained quickly and present a stable model for predicting shear wave velocity. For this reason, this method is known as “dynamic regression” compared with multiple regression. Neural network used in this study is not like a black box because we have used the results of multiple regression that can easily modify prediction of shear wave velocity through appropriate combination of data. The same information that was intended for multiple regression was used as input in neural networks, and shear wave velocity was obtained using compressional wave velocity and well logging data (neutron, density, gamma and deep resistivity) in carbonate rocks. The results show that methods applied in this carbonate reservoir was successful, so that shear wave velocity was predicted with about 92 and 95 percents of correlation coefficient in multiple regression and neural network method, respectively. Therefore, we propose using these methods to estimate shear wave velocity in wells without this parameter.展开更多
The signal synchronization transmission of a spatiotemporal chaos network is investigated. The structure of the coupling function between connected nodes of the complex network and the value range of the linear term c...The signal synchronization transmission of a spatiotemporal chaos network is investigated. The structure of the coupling function between connected nodes of the complex network and the value range of the linear term coefficient of the separated configuration in state equation of the node are obtained through constructing an appropriate Lyapunov function. Each node of the complex network is a laser spatiotemporal chaos model in which the phase-conjugate wave and the unilateral coupled map lattice are taken as a local function and a spatially extended system, respectively. The simulation results show the effectiveness of the signal synchronization transmission principle of the network.展开更多
Based on wave digital filter(WDF) principles, this paper presents a digital model of cellular neural networks(CNNs). The model can precisely simulate the dynamic behavior of CNNs.
With the development of self-interference(SI) cancelation technology, full-duplex(FD) communication becomes possible. FD communication can theoretically double the spectral efficiency. When the time slot(TS) resources...With the development of self-interference(SI) cancelation technology, full-duplex(FD) communication becomes possible. FD communication can theoretically double the spectral efficiency. When the time slot(TS) resources are limited and the number of flows is large, the scheduling mechanism of the flows becomes more important. Therefore, the effectiveness of FD scheduling mechanism for the flows is studied in millimeter wave wireless backhaul network with the limited TS resources. We proposed a full duplex concurrent scheduling algorithm based on coalition game(FDCG) to maximize the number of flows with their QoS requirements satisfied. We transformed the problem of maximizing the number of flows with their QoS requirements satisfied into the problem of maximizing sum rate of concurrently scheduled flows in each slot. We obtained the scheduled flows with maximum sum rate in first slot by using coalition game.And then with certain restrictions, the maximum sum rate of concurrently scheduled flows can also be achieved in subsequent time slots. The simulation results show that the proposed FDCG algorithm canachieve superior performance in terms of the number of flows that meet their QoS requirements and system throughput compared with other three algorithms.展开更多
This article focuses on the aggression of lightning overload on the equipment of the electrical network of sites where storm activity is very dense;and the electrocution of people located in the direct environment of ...This article focuses on the aggression of lightning overload on the equipment of the electrical network of sites where storm activity is very dense;and the electrocution of people located in the direct environment of the high-voltage substation during the flow of lightning current to the ground through the ground socket. The modeling of the flow circuit of the shock wave consisting of guard wire, lightning arrester and ground socket couple to the transformer of the high voltage substations, thanks to the approach of a servo block, led to the synthesis of a PID regulator (corrector) whose action is to reject the effects of the overvoltage on the network equipment and to significantly reduce or even cancel the effects of the step or touch voltage due to the distribution of the potential around the ground socket;and thus improve the quality of service of the high-voltage transmission and distribution electricity network, especially in stormy times.展开更多
The demand for wireless data has been driving network capacity to double about every two years for the past 50 years, if not 100 years, and this has come to be known as Cooper＇s Law. In recent years, this trend has a...The demand for wireless data has been driving network capacity to double about every two years for the past 50 years, if not 100 years, and this has come to be known as Cooper＇s Law. In recent years, this trend has accelerated as a greater proportion of the population adopts wireless devices with ever greater capabilities, including tablets that support HD video and other advanced capabilities.展开更多
This paper develops a nonlinear mathematical model to simulate the dynamic motion behavior of the barge equipped with the portable outboard Dynamic Positioning （DP） system in short-crested waves. The self-tuning Pro...This paper develops a nonlinear mathematical model to simulate the dynamic motion behavior of the barge equipped with the portable outboard Dynamic Positioning （DP） system in short-crested waves. The self-tuning Proportional- Derivative （PD） controller based on the neural network algorithm is applied to control the thrusters for optimal adjustment of the barge position in waves. In addition to the wave, the current, the wind and the nonlinear drift force are also considered in the calculations. The time domain simulations for the six-degree-of-freedom motions of the barge with the DP system are solved by the 4th order Runge-Kutta method which can compromise the efficiency and the accuracy of the simulations. The technique of the portable alternative DP system developed here can serve as a practical tool to assist those ships without being equipped with the DP facility while the dynamic positioning missions are needed.展开更多
A method to eliminate spiral waves and spatiotemporal chaos by using the synchronization transmission technology of network signals is proposed in this paper. The character of the spiral waves and the spatiotemporal c...A method to eliminate spiral waves and spatiotemporal chaos by using the synchronization transmission technology of network signals is proposed in this paper. The character of the spiral waves and the spatiotemporal chaos in the Fitzhugh-Nagumo model is presented. The network error evolution equation with spatiotemporal variables and the corresponding eigenvalue equation are determined based on the stability theory, and the global synchronization condition is obtained. Simulations are made in a complex network with Fitzhugh-Nagumo models as the nodes to verify the effectiveness of the synchronization transmission principle of the network signal.展开更多
In this paper, the Artificial Neural Network (ANN) is used to study the wave forces on a semi-circular breakwater. The process of establishing the network model for a specific physical problem is presented. Networks w...In this paper, the Artificial Neural Network (ANN) is used to study the wave forces on a semi-circular breakwater. The process of establishing the network model for a specific physical problem is presented. Networks with double implicit layers have been studied by numerical experiments. 117 sets of experimental data are used to train and test the ANN. According to the results of ANN simulation, this method is proved to have good precision compared with experimental and numerical results.展开更多
The prediction of solitary wave run-up has important practical significance in coastal and ocean engineering, but the calculation precision is limited in the existing models. For improving the calculation precision, a...The prediction of solitary wave run-up has important practical significance in coastal and ocean engineering, but the calculation precision is limited in the existing models. For improving the calculation precision, a solitary wave run-up calculation model was established based on artificial neural networks in this study. A back-propagation （BP） network with one hidden layer was adopted and modified with the additional momentum method and the auto-adjusting learning factor. The model was applied to calculation of solitary wave run-up. The correlation coefficients between the neural network model results and the experimental values was 0.996 5. By comparison with the correlation coefficient of 0.963 5, between the Synolakis formula calculation results and the experimental values, it is concluded that the neural network model is an effective method for calculation and analysis of solitary wave ran-up.展开更多
This research aims at improving the methods of prediction of shear wave velocity in underground layers. We propose and showcase our methodology using a case study on the Mashhad plain in north eastern part of Iran. Ge...This research aims at improving the methods of prediction of shear wave velocity in underground layers. We propose and showcase our methodology using a case study on the Mashhad plain in north eastern part of Iran. Geotechnical investigations had previously reported nine measurements of the SASW (Spectral Analysis of Surface Waves) method over this field and above wells which have DHT (Down Hole Test) result. Since SASW utilizes an analytical formula (which suffers from some simplicities and noise) for evaluating shear wave velocity, we use the results of SASW in a trained artificial neural network (ANN) to estimate the un- known nonlinear relationships between SASW results and those obtained by the method of DHT (treated here as real values). Our results show that an appropriately trained neural network can reliably predict the shear wave velocity between wells accurately.展开更多
A new method of fault analysis and detection by signal classification inrotating machines is presented. The Local Wave time-frequency spectrum which is a new method forprocessing a non-stationary signal is used to pro...A new method of fault analysis and detection by signal classification inrotating machines is presented. The Local Wave time-frequency spectrum which is a new method forprocessing a non-stationary signal is used to produce the representation of the signal. This methodallows the decomposition of one-dimensional signals into intrinsic mode functions (IMFs) usingempirical mode decomposition and the calculation of a meaningful multi-component instantaneousfrequency. Applied to fault signals , it provides new time-frequency attributes. Then the momentsand margins of the time-frequency spectrum are calculated as the feature vectors. The probabilisticneural network is used to classify different fault modes. The accuracy and robustness of theproposed methods is investigated on signals obtained during the different fault modes (early rub,loose, misalignment of the rotor).展开更多
We investigate the performances of the pairwise correlations（PCs） in different quantum networks consisting of fourwave mixers（FWMs） and beamsplitters（BSs）. PCs with quantum correlation in different quantum netwo...We investigate the performances of the pairwise correlations（PCs） in different quantum networks consisting of fourwave mixers（FWMs） and beamsplitters（BSs）. PCs with quantum correlation in different quantum networks can be verified by calculating the degree of relative intensity squeezing for any pair of all the output fields. More interestingly, the quantum correlation recovery and enhancement are present in the FWM＋BS network and the repulsion effect phenomena（signal（idler）-frequency mode cannot be quantum correlated with the other two idler（signal）-frequency modes simultaneously）between the PCs with quantum correlation are predicted in the FWM ＋ FWM and FWM ＋ FWM ＋ FWM networks. Our results presented here pave the way for the manipulation of the quantum correlation in quantum networks.展开更多
This paper introduces the principle for recognition of engine work wave signal with neural network. A diagnosis method for recognizing engine trouble by its work wave is proposed. The designing process is illustrated ...This paper introduces the principle for recognition of engine work wave signal with neural network. A diagnosis method for recognizing engine trouble by its work wave is proposed. The designing process is illustrated by diagnosing the voltage trouble of the fuel injector of an electronic control (EC) engine.展开更多
基金supported by the National Natural Science Foundation of China(No.12301579)the Fundamental Research Funds for the Central Universities of Civil Aviation University of China(No.3122019140).
文摘In this paper,we delve into the problem of exponential stability for a coupled system of a one-dimensional(1-D)N-root wave network with boundary delays.Our aim is to establish a universal controller design strategy,where the designed controller must guarantee the stability of the closed-loop system.The research approach undertaken in this paper assumes that the system state is known.We employ an integral-type feedback controller to achieve system stability,where the integral kernel function serves as a parameter.We attempt to select the corresponding exponentially stable system as the target system,and then construct a bounded linear transformation to demonstrate the equivalence between the target system and the original system,thereby eliminating the adverse effects of time delays on the system.The crux lies in determining the equation that the kernel function must satisfy.Herein,we primarily present a methodology for selecting the parameter function within this transformation,to achieve an exponentially stable feedback controller.
基金supported by the National Natural Science Foundation of China under Grant No.61376024 and No.61306024the Natural Science Foundation of Guangdong Province under Grant No.S2013040014366Basic Research Program of Shenzhen No.JCYJ20140417113430642 and JCYJ20140901003939020
文摘The networks-on-chip （NoC） communication has an increasingly larger impact on the system power consumption and performance. Emerging technologies, like surface wave, are believed to have lower transmission latency and power consumption over the conventional wireless NoC. Therefore, this paper studies how to optimize the network performance and power consumption by giving the packet-switching fabric and traffic pattern of each application. Compared with the conventional method of wire-linked, which adds wireless transceivers by using the genetic algorithm （GA）, the proposed maximal declining sorting algorithm （MDSA） can effectively reduce time consumption by as much as 20.4% to 35.6%. We also evaluate the power consumption and configuration time to prove the effective of the proposed algorithm.
基金supported in part by the NSF under Grants ECCS-1923717 and CNS-1320472the Wireless Engineering Research and Education Center,Auburn University,Auburn,AL,USA.
文摘The directional neighbor discovery problem,i.e,spatial rendezvous,is a fundamental problem in millimeter wave(mmWave)wireless networks,where directional transmissions are used to overcome the high attenuation.The challenge is how to let the transmitter and the receiver beams meet in space under deafness caused by directional transmission and reception,where no control channel,prior information,and coordination are available.In this paper,we present a Hunting based Directional Neighbor Discovery(HDND)scheme for ad hoc mmWave networks,where a node follows a unique sequence to determine its transmission or reception mode,and continuously r0-tates its directional beam to scan the neighborhood for other mmWave nodes.Through a rigorous analysis,we derive the conditions for ensured neighbor discovery,as well as a bound for the worst-case discovery time and the impact of sidelobes.We validate the analysis with extensive simulations and demonstrate the superior perfor-mance of the proposed scheme over several baseline schemes.
文摘An approach based on artificial neural network （ANN） is used to develop predictive relations between hydrodynamic inline force on a vertical cylinder and some effective parameters. The data used to calibrate and validate the ANN models are obtained from an experiment. Multilayer feed-forward neural networks that are trained with the back-propagation algorithm are constructed by use of three design parameters （i.e. wave surface height, horizontal and vertical velocities） as network inputs and the ultimate inline force as the only output. A sensitivity analysis is conducted on the ANN models to investigate the generalization ability （robustness） of the developed models, and predictions from the ANN models are compared to those obtained from Morison equation which is usually used to determine inline force as a computational method. With the existing data, it is found that least square method （LSM） gives less error in determining drag and inertia coefficients of Morison equation. With regard to the predicted results agreeing with calculations achieved from Morison equation that used LSM method, neural network has high efficiency considering its convenience, simplicity and promptitude. The outcome of this study can contribute to reducing the errors in predicting hydrodynamic inline force by use of ANN and to improve the reliability of that in comparison with the more practical state of Morison equation. Therefore, this method can be applied to relevant engineering projects with satisfactory results
基金supported in part by National Natural Science Foundation of China(No.61372070)Natural Science Basic Research Plan in Shaanxi Province of China(2015JM6324)+2 种基金Hong Kong,Macao and Taiwan Science & Technology Cooperation Program of China(2014DFT10320)EU FP7 Project MONICA(PIRSES-GA-2011-295222)the 111 Project(B08038)
文摘Millimeter-wave(mmWave) communications are highly focused as a powerful mean enabling to perform very high data transmission. However it has several inherent shortcomings like directional transmission and serious attenuation in atmosphere. So it is difficult to implement random access in mm Wave WLANs. In this paper, a heterogeneous control and data sub-network architecture is presented, which decouples the traditional WLAN into 2.4 or 5GHz control sub-network and mm Wave data sub-network in both PHY and MAC layers. In control sub-network, DCF is adopted to transmit control information and in data sub-network, PCF is adopted to ensure the Qo S. Moreover, an omnidirectional transmission is employed in the control sub-network to support users' random access. The data sub-network only covers the required serving area by using directional antennas for specific users and can be adjusted dynamically based on control information. Simulations indicate that compared with the conventional WLANs, heterogeneous mm Wave WLANs can provide both random access and high throughput.
文摘Shear wave velocity has numerous applications in geomechanical, petrophysical and geophysical studies of hydrocarbon reserves. However, data related to shear wave velocity isn’t available for all wells, especially old wells and it is very important to estimate this parameter using other well logging. Hence, lots of methods have been developed to estimate these data using other available information of reservoir. In this study, after processing and removing inappropriate petrophysical data, we estimated petrophysical properties affecting shear wave velocity of the reservoir and statistical methods were used to establish relationship between effective petrophysical properties and shear wave velocity. To predict (VS), first we used empirical relationships and then multivariate regression methods and neural networks were used. Multiple regression method is a powerful method that uses correlation between available information and desired parameter. Using this method, we can identify parameters affecting estimation of shear wave velocity. Neural networks can also be trained quickly and present a stable model for predicting shear wave velocity. For this reason, this method is known as “dynamic regression” compared with multiple regression. Neural network used in this study is not like a black box because we have used the results of multiple regression that can easily modify prediction of shear wave velocity through appropriate combination of data. The same information that was intended for multiple regression was used as input in neural networks, and shear wave velocity was obtained using compressional wave velocity and well logging data (neutron, density, gamma and deep resistivity) in carbonate rocks. The results show that methods applied in this carbonate reservoir was successful, so that shear wave velocity was predicted with about 92 and 95 percents of correlation coefficient in multiple regression and neural network method, respectively. Therefore, we propose using these methods to estimate shear wave velocity in wells without this parameter.
基金Project supported by the Natural Science Foundation of Liaoning Province,China (Grant No. 20082147)
文摘The signal synchronization transmission of a spatiotemporal chaos network is investigated. The structure of the coupling function between connected nodes of the complex network and the value range of the linear term coefficient of the separated configuration in state equation of the node are obtained through constructing an appropriate Lyapunov function. Each node of the complex network is a laser spatiotemporal chaos model in which the phase-conjugate wave and the unilateral coupled map lattice are taken as a local function and a spatially extended system, respectively. The simulation results show the effectiveness of the signal synchronization transmission principle of the network.
文摘Based on wave digital filter(WDF) principles, this paper presents a digital model of cellular neural networks(CNNs). The model can precisely simulate the dynamic behavior of CNNs.
基金supported by the National Natural Science Foundation of China Grants 61725101 and 61801016the China Postdoctoral Science Foundation under Grant 2017M610040 and 2018T110041+2 种基金National key research and development program under Grant 2016YFE0200900the Beijing Natural Fund under Grant L172020Major projects of Beijing Municipal Science and Technology Commission under Grant No. Z181100003218010
文摘With the development of self-interference(SI) cancelation technology, full-duplex(FD) communication becomes possible. FD communication can theoretically double the spectral efficiency. When the time slot(TS) resources are limited and the number of flows is large, the scheduling mechanism of the flows becomes more important. Therefore, the effectiveness of FD scheduling mechanism for the flows is studied in millimeter wave wireless backhaul network with the limited TS resources. We proposed a full duplex concurrent scheduling algorithm based on coalition game(FDCG) to maximize the number of flows with their QoS requirements satisfied. We transformed the problem of maximizing the number of flows with their QoS requirements satisfied into the problem of maximizing sum rate of concurrently scheduled flows in each slot. We obtained the scheduled flows with maximum sum rate in first slot by using coalition game.And then with certain restrictions, the maximum sum rate of concurrently scheduled flows can also be achieved in subsequent time slots. The simulation results show that the proposed FDCG algorithm canachieve superior performance in terms of the number of flows that meet their QoS requirements and system throughput compared with other three algorithms.
文摘This article focuses on the aggression of lightning overload on the equipment of the electrical network of sites where storm activity is very dense;and the electrocution of people located in the direct environment of the high-voltage substation during the flow of lightning current to the ground through the ground socket. The modeling of the flow circuit of the shock wave consisting of guard wire, lightning arrester and ground socket couple to the transformer of the high voltage substations, thanks to the approach of a servo block, led to the synthesis of a PID regulator (corrector) whose action is to reject the effects of the overvoltage on the network equipment and to significantly reduce or even cancel the effects of the step or touch voltage due to the distribution of the potential around the ground socket;and thus improve the quality of service of the high-voltage transmission and distribution electricity network, especially in stormy times.
文摘The demand for wireless data has been driving network capacity to double about every two years for the past 50 years, if not 100 years, and this has come to be known as Cooper＇s Law. In recent years, this trend has accelerated as a greater proportion of the population adopts wireless devices with ever greater capabilities, including tablets that support HD video and other advanced capabilities.
基金financially supported by the Science Council Taiwan (Grant No. NSC-96-2221-E006-329-MY3)partly supported by the Research Center of Ocean Environment and Technology NCKU
文摘This paper develops a nonlinear mathematical model to simulate the dynamic motion behavior of the barge equipped with the portable outboard Dynamic Positioning （DP） system in short-crested waves. The self-tuning Proportional- Derivative （PD） controller based on the neural network algorithm is applied to control the thrusters for optimal adjustment of the barge position in waves. In addition to the wave, the current, the wind and the nonlinear drift force are also considered in the calculations. The time domain simulations for the six-degree-of-freedom motions of the barge with the DP system are solved by the 4th order Runge-Kutta method which can compromise the efficiency and the accuracy of the simulations. The technique of the portable alternative DP system developed here can serve as a practical tool to assist those ships without being equipped with the DP facility while the dynamic positioning missions are needed.
基金Project Supported by the National Natural Science Foundation of China (Grant No.60974004)
文摘A method to eliminate spiral waves and spatiotemporal chaos by using the synchronization transmission technology of network signals is proposed in this paper. The character of the spiral waves and the spatiotemporal chaos in the Fitzhugh-Nagumo model is presented. The network error evolution equation with spatiotemporal variables and the corresponding eigenvalue equation are determined based on the stability theory, and the global synchronization condition is obtained. Simulations are made in a complex network with Fitzhugh-Nagumo models as the nodes to verify the effectiveness of the synchronization transmission principle of the network signal.
文摘In this paper, the Artificial Neural Network (ANN) is used to study the wave forces on a semi-circular breakwater. The process of establishing the network model for a specific physical problem is presented. Networks with double implicit layers have been studied by numerical experiments. 117 sets of experimental data are used to train and test the ANN. According to the results of ANN simulation, this method is proved to have good precision compared with experimental and numerical results.
基金supported by State Key Development Program of Basic Research of China (Grant No.2010CB429001)
文摘The prediction of solitary wave run-up has important practical significance in coastal and ocean engineering, but the calculation precision is limited in the existing models. For improving the calculation precision, a solitary wave run-up calculation model was established based on artificial neural networks in this study. A back-propagation （BP） network with one hidden layer was adopted and modified with the additional momentum method and the auto-adjusting learning factor. The model was applied to calculation of solitary wave run-up. The correlation coefficients between the neural network model results and the experimental values was 0.996 5. By comparison with the correlation coefficient of 0.963 5, between the Synolakis formula calculation results and the experimental values, it is concluded that the neural network model is an effective method for calculation and analysis of solitary wave ran-up.
文摘This research aims at improving the methods of prediction of shear wave velocity in underground layers. We propose and showcase our methodology using a case study on the Mashhad plain in north eastern part of Iran. Geotechnical investigations had previously reported nine measurements of the SASW (Spectral Analysis of Surface Waves) method over this field and above wells which have DHT (Down Hole Test) result. Since SASW utilizes an analytical formula (which suffers from some simplicities and noise) for evaluating shear wave velocity, we use the results of SASW in a trained artificial neural network (ANN) to estimate the un- known nonlinear relationships between SASW results and those obtained by the method of DHT (treated here as real values). Our results show that an appropriately trained neural network can reliably predict the shear wave velocity between wells accurately.
文摘A new method of fault analysis and detection by signal classification inrotating machines is presented. The Local Wave time-frequency spectrum which is a new method forprocessing a non-stationary signal is used to produce the representation of the signal. This methodallows the decomposition of one-dimensional signals into intrinsic mode functions (IMFs) usingempirical mode decomposition and the calculation of a meaningful multi-component instantaneousfrequency. Applied to fault signals , it provides new time-frequency attributes. Then the momentsand margins of the time-frequency spectrum are calculated as the feature vectors. The probabilisticneural network is used to classify different fault modes. The accuracy and robustness of theproposed methods is investigated on signals obtained during the different fault modes (early rub,loose, misalignment of the rotor).
基金Project supported by the National Natural Science Foundation of China(Grants Nos.91436211,11374104,and 10974057)the Natural Science Foundation of Shanghai,China(Grant No.17ZR1442900)+5 种基金the Specialized Research Fund for the Doctoral Program of Higher Education,China(Grant No.20130076110011)the Program for Professor of Special Appointment(Eastern Scholar)at Shanghai Institutions of Higher Learning,the Program for New Century Excellent Talents in University,China(Grant No.NCET-10-0383)the Shu Guang Project supported by Shanghai Municipal Education Commission and Shanghai Education Development Foundation,China(Grant No.11SG26)the Shanghai Pujiang Program,China(Grant No.09PJ1404400)the Scientific Research Foundation for the Returned Overseas Chinese Scholars,State Education Ministry,National Basic Research Program of China(Grant No.2016YFA0302103)the Program of State Key Laboratory of Advanced 207 Optical Communication Systems and Networks,China(Grant No.2016GZKF0JT003)
文摘We investigate the performances of the pairwise correlations（PCs） in different quantum networks consisting of fourwave mixers（FWMs） and beamsplitters（BSs）. PCs with quantum correlation in different quantum networks can be verified by calculating the degree of relative intensity squeezing for any pair of all the output fields. More interestingly, the quantum correlation recovery and enhancement are present in the FWM＋BS network and the repulsion effect phenomena（signal（idler）-frequency mode cannot be quantum correlated with the other two idler（signal）-frequency modes simultaneously）between the PCs with quantum correlation are predicted in the FWM ＋ FWM and FWM ＋ FWM ＋ FWM networks. Our results presented here pave the way for the manipulation of the quantum correlation in quantum networks.
文摘This paper introduces the principle for recognition of engine work wave signal with neural network. A diagnosis method for recognizing engine trouble by its work wave is proposed. The designing process is illustrated by diagnosing the voltage trouble of the fuel injector of an electronic control (EC) engine.
