Unmanned Aerial Vehicles(UAVs)coupled with deep learning such as Convolutional Neural Networks(CNNs)have been widely applied across numerous domains,including agriculture,smart city monitoring,and fire rescue operatio...Unmanned Aerial Vehicles(UAVs)coupled with deep learning such as Convolutional Neural Networks(CNNs)have been widely applied across numerous domains,including agriculture,smart city monitoring,and fire rescue operations,owing to their malleability and versatility.However,the computation-intensive and latency-sensitive natures of CNNs present a formidable obstacle to their deployment on resource-constrained UAVs.Some early studies have explored a hybrid approach that dynamically switches between lightweight and complex models to balance accuracy and latency.However,they often overlook scenarios involving multiple concurrent CNN streams,where competition for resources between streams can substantially impact latency and overall system performance.In this paper,we first investigate the deployment of both lightweight and complex models for multiple CNN streams in UAV swarm.Specifically,we formulate an optimization problem to minimize the total latency across multiple CNN streams,under the constraints on UAV memory and the accuracy requirement of each stream.To address this problem,we propose an algorithm called Adaptive Model Switching of collaborative inference for MultiCNN streams(AMSM)to identify the inference strategy with a low latency.Simulation results demonstrate that the proposed AMSM algorithm consistently achieves the lowest latency while meeting the accuracy requirements compared to benchmark algorithms.展开更多
This paper mainly investigates dynamics behavior of HIV （human immunodeficiency virus） infectious disease model with switching parameters, and combined bounded noise and Gaussian white noise. This model is different...This paper mainly investigates dynamics behavior of HIV （human immunodeficiency virus） infectious disease model with switching parameters, and combined bounded noise and Gaussian white noise. This model is different from existing HIV models. Based on stochastic Ito lemma and Razumikhin-type approach, some threshold conditions are established to guarantee the disease eradication or persistence. Results show that the smaller amplitude of bounded noise and R0 〈 1 can cause the disease to die out; the disease becomes persistent if R0 〉 1. Moreover, it is found that larger noise intensity suppresses the prevalence of the disease even if R0 〉 1. Some numerical examples are given to verify the obtained results.展开更多
In the complex mechanical vibration environment, the dominant frequency of the system varies remarkably and swiftly under various running conditions, which also characterizes uncertainty and time-variation. It is very...In the complex mechanical vibration environment, the dominant frequency of the system varies remarkably and swiftly under various running conditions, which also characterizes uncertainty and time-variation. It is very impending and important to suppress or isolate the detrimental vibrations related to the above memtoned system with active vibration control (AVC) technology. This paper presented the improved linear quadratic gaussian (LQG) control scheme with a specified filter to realize broadband disturbance/noise attenuation and assure intensive suppression of vibration at the key vibration frequency, then applies and modifies the multiple model switching tuning (MMST) control method by disturbance observation to track the variation of dominant vibration component timely. The effectiveness and superiority of the presented control method were demonstrated by numerical simulation and AVC experiment on a flexible cantilever beam under sweeping excitation.展开更多
An improved nonlinear adaptive switching control method is presented to relax the assumption on the higher order nonlinear terms of a class of discrete-time non-affine nonlinear systems. The proposed control strategy ...An improved nonlinear adaptive switching control method is presented to relax the assumption on the higher order nonlinear terms of a class of discrete-time non-affine nonlinear systems. The proposed control strategy is composed of a linear adaptive controller, a neural network(NN) based nonlinear adaptive controller and a switching mechanism. An incremental model is derived to represent the considered system and an improved robust adaptive law is chosen to update the parameters of the linear adaptive controller. A new performance criterion of the switching mechanism is designed to select the proper controller. Using this control scheme, all the signals in the system are proved to be bounded. Numerical examples verify the effectiveness of the proposed algorithm.展开更多
Traffic modeling is a key step in several intelligent transportation systems（ITS） applications. This paper regards the traffic modeling through the enhancement of the cell transmission model. It considers the traffi...Traffic modeling is a key step in several intelligent transportation systems（ITS） applications. This paper regards the traffic modeling through the enhancement of the cell transmission model. It considers the traffic flow as a hybrid dynamic system and proposes a piecewise switched linear traffic model. The latter allows an accurate modeling of the traffic flow in a given section by considering its geometry. On the other hand, the piecewise switched linear traffic model handles more than one congestion wave and has the advantage to be modular. The measurements at upstream and downstream boundaries are also used in this model in order to decouple the traffic flow dynamics of successive road portions. Finally, real magnetic sensor data, provided by the performance measurement system on a portion of the Californian SR60-E highway are used to validate the proposed model.展开更多
A novel and accurate method is proposed to extract the intrinsic elements of the GaN high-electron-mobility transistor（HEMT） switch.The new extraction method is verified by comparing the simulated S-parameters with ...A novel and accurate method is proposed to extract the intrinsic elements of the GaN high-electron-mobility transistor（HEMT） switch.The new extraction method is verified by comparing the simulated S-parameters with the measured data over the 5-40 GHz frequency range.The percentage errors E（ij） within 3.83% show the great agreement between the simulated S-parameters and the measured data.展开更多
The cause of substorm onset is not yet understood. Chen CX(2016) proposed an entropy switch model, in which substorm onset results from the development of interchange instability. In this study, we sought observationa...The cause of substorm onset is not yet understood. Chen CX(2016) proposed an entropy switch model, in which substorm onset results from the development of interchange instability. In this study, we sought observational evidence for this model by using Time History of Events and Macroscale Interactions during Substorms(THEMIS) data. We examined two events, one with and the other without a streamer before substorm onset. In contrast to the stable magnetosphere, where the total magnetic field strength is a decreasing function and entropy is an increasing function of the downtail distance, in both events the total magnetic field strength and entropy were reversed before substorm onset. After onset, the total magnetic field strength, entropy, and other plasma quantities fluctuated. In addition, a statistical study was performed. By confining the events with THEMIS satellites located in the downtail region between ~8 and ~12 Earth radii, and 3 hours before and after midnight, we found the occurrence rate of the total magnetic field strength reversal to be 69% and the occurrence rate of entropy reversal to be 77% of the total 205 events.展开更多
This paper proposes a data-driven learning-based approach to predictive control for switched nonlinear systems subject to state and control constraints and external stochastic disturbances.A switched Koopman modeling ...This paper proposes a data-driven learning-based approach to predictive control for switched nonlinear systems subject to state and control constraints and external stochastic disturbances.A switched Koopman modeling framework is developed,where a multi-mode neural network for state lifting is trained simultaneously with Koopman operators and state reconstruction matrices for all modes.This framework facilitates the construction of the switched linear Koopman model in a transformed space and effectively captures the dynamics of the original nonlinear system.A switched predictive control strategy is then designed to regulate the switched Koopman model with constrained states and control inputs against both the stochastic disturbances and the uncertainties introduced by the lifting neural network.The proposed control scheme ensures mean-square stability and guarantees boundedness during the online phase.Furthermore,boundedness analysis is performed to determine the bounded set of the original system state across all admissible switching sequences.The effectiveness of the proposed methodology is demonstrated through a case study of a gene regulatory network.展开更多
The Internet is believed to bring more technological dividends to vulnerable farmers during the green agriculture transformation.However,this is different from the theory of skill-biased technological change,which emp...The Internet is believed to bring more technological dividends to vulnerable farmers during the green agriculture transformation.However,this is different from the theory of skill-biased technological change,which emphasizes that individuals with higher levels of human capital and more technological endowments benefit more.This study investigates the effects of Internet use on farmers'adoption of integrated pest management(IPM),theoretically and empirically,based on a dataset containing 1015 farmers in China's Shandong Province.By exploring the perspective of rational inattention,the reasons for the heterogeneity of the effects across farmers with different endowments,i.e.,education and land size,are analyzed.The potential endogeneity issues are addressed using the endogenous switching probit model.The results reveal that:(1)although Internet use significantly positively affects farmers'adoption of IPM,vulnerable farmers do not benefit more from it.Considerable selection bias leads to an overestimation of technological dividends for vulnerable farmers;(2)different sources of technology information lead to the difference in the degree of farmers'rational inattention toward Internet information,which plays a crucial role in the heterogeneous effect of Internet use;and(3)excessive dependence on strong-tie social network information sources entraps vulnerable farmers in information cocoons,hindering their ability to reap the benefits of Internet use fully.Therefore,it is essential to promote services geared towards elderly-oriented Internet agricultural technology information and encourage farmers with strong Internet utilization skills to share technology information with other farmers actively.展开更多
For the preparation of any target Bell state under continuous quantum measurement, this paper proposes a method which achieves the control objective by switching between two different models or by switching between tw...For the preparation of any target Bell state under continuous quantum measurement, this paper proposes a method which achieves the control objective by switching between two different models or by switching between two control channels under one model. Proper control Hamiltonians are selected for the two system models, a switching strategy between the two models is designed, and the stability of the whole switching system is proved in theory. For a given target Bell state, the effectiveness of the proposed switching control strategy between different models is illustrated through simulation experiments.展开更多
A well-documented finding is that explicitly using jumps cannot efficiently enhance the predictability of crude oil price volatility.To address this issue,we find a phenomenon,“momentum of jumps”(MoJ),that the predi...A well-documented finding is that explicitly using jumps cannot efficiently enhance the predictability of crude oil price volatility.To address this issue,we find a phenomenon,“momentum of jumps”(MoJ),that the predictive ability of the jump component is persistent when forecasting the oil futures market volatility.Specifically,we propose a strategy that allows the predictive model to switch between a benchmark model without jumps and an alternative model with a jump component according to their recent past forecasting performance.The volatility data are based on the intraday prices of West Texas Intermediate.Our results indicate that this simple strategy significantly outperforms the individual models and a series of competing strategies such as forecast combinations and shrinkage methods.A mean–variance investor who targets a constant Sharpe ratio can realize the highest economic gains using the MoJ-based volatility forecasts.Our findings survive a wide variety of robustness tests,including different jump measures,alternative volatility measures,various financial markets,and extensive model specifications.展开更多
Regime switching,which is described by a Markov chain,is introduced in a Markov copula model.We prove that the marginals（X,H^i）,i = 1,2,3 of the Markov copula model（X,H） are still Markov processes and have marting...Regime switching,which is described by a Markov chain,is introduced in a Markov copula model.We prove that the marginals（X,H^i）,i = 1,2,3 of the Markov copula model（X,H） are still Markov processes and have martingale property.In this proposed model,a pricing formula of credit default swap（CDS） with bilateral counterparty risk is derived.展开更多
In this paper,a stochastic SIQS epidemic model perturbed by both white and telephone noises is investigated.By constructing several suitable Lyapunov functions,we obtain sufficient conditions for the existence of ergo...In this paper,a stochastic SIQS epidemic model perturbed by both white and telephone noises is investigated.By constructing several suitable Lyapunov functions,we obtain sufficient conditions for the existence of ergodic stationary distribution of the positive solution.Moreover,by solving the Fokker-Planck equation,we obtain the exact expression of probability density function around the quasi-equilibrium of the stochastic model.In addition,sufficient conditions for the extinction are established.Finally,the results of this paper are further verified by numerical simulation.展开更多
Multi-terminal direct current(MTDC)grids provide the possibility of meshed interconnections between regional power systems and various renewable energy resources to boost supply reliability and economy.The modular mul...Multi-terminal direct current(MTDC)grids provide the possibility of meshed interconnections between regional power systems and various renewable energy resources to boost supply reliability and economy.The modular multilevel converter(MMC)has become the basic building block for MTDC and DC grids due to its salient features,i.e.,modularity and scalability.Therefore,the MMC-based MTDC systems should be pervasively embedded into the present power system to improve system performance.However,several technical challenges hamper their practical applications and deployment,including modeling,control,and protection of the MMC-MTDC grids.This paper presents a comprehensive investigation and reference in modeling,control,and protection of the MMC-MTDC grids.A general overview of state-of-the-art modeling techniques of the MMC along with their performance in simulation analysis for MTDC applications is provided.A review of control strategies of the MMC-MTDC grids which provide AC system support is presented.State-of-the art protection techniques of the MMCMTDC systems are also investigated.Finally,the associated research challenges and trends are highlighted.展开更多
This paper presents the complete mathematical model and predicts the performance of switched reluctance generator with time average and small signal models. The complete mathematical model is developed in three stages...This paper presents the complete mathematical model and predicts the performance of switched reluctance generator with time average and small signal models. The complete mathematical model is developed in three stages. First, a switching model is developed based on quasi-linear inductance profile. Next, based on the switching behaviour, a time average model is obtained to measure the difference between the excitation and generation time in each switching cycle. Finally, to track control voltage and current wave shapes, a small signal model is designed. The effectiveness of the complete multilevel model combining electrical machine, power converter, load and control with programming language is demonstrated through simulations. A PI controller is used for controlling the voltage of the generator. The results presented show that the controller exhibits accurate tracking control of load voltage under different operating conditions. This demonstrates that the proposed model is able to perform an accurate control of the generated output voltage even in transient situations. The simulation is performed to choose the control parameters and study the performance of switched reluctance generator prior to its actual implementation. Initial experimental results are presented using NI-Data acquisition card to control the output power according to load requirements.展开更多
This paper investigates the problem of global disturbance rejection for a class of switched nonlinear systems where the solvability of the disturbance rejection problem for subsystems is not assumed. The disturbances ...This paper investigates the problem of global disturbance rejection for a class of switched nonlinear systems where the solvability of the disturbance rejection problem for subsystems is not assumed. The disturbances are assumed to be sinusoidal with completely unknown frequencies, phases and amplitudes. First, as an extension of the classic concept of internal model for non-switched systems, a switched internal model is proposed. Second, in order to solve the problem under study, an adaptive control method is established on the basis of the multiple Lyapunov functions method. Also,adaptive state-feedback controllers of subsystems are designed and incorporated with a switching law to asymptotically reject the unknown disturbances. Finally, an example is provided to demonstrate the effectiveness of the proposed design method.展开更多
Gallium nitride （GaN） high electron mobility transistor （HEMT） with symmetrical structure as a control device is discussed in this paper. The equivalent circuit model is proposed on the basis of physical and elect...Gallium nitride （GaN） high electron mobility transistor （HEMT） with symmetrical structure as a control device is discussed in this paper. The equivalent circuit model is proposed on the basis of physical and electrical properties of the GaN HEMT device. A transistor with 0.5 μm gate length and 6 x 125 gm gate width is fabricated to verify the model, which can be treated as a single pole single throw （SPST） switch due to the ON state and OFF state. The measurement results show a lzood agreement with the simulation results, which demonstrates the effectiveness of the proposed model.展开更多
This paper presents a new hybrid compartmental model for studying the COVID-19 epidemic evolution in Italy since the beginning of the vaccination campaign started on 2020/12/27 and shows forecasts of the epidemic evol...This paper presents a new hybrid compartmental model for studying the COVID-19 epidemic evolution in Italy since the beginning of the vaccination campaign started on 2020/12/27 and shows forecasts of the epidemic evolution in Italy in the first six months.The proposed compartmental model subdivides the population into six compartments and extends the SEIRD model proposed in[E.L.Piccolomini and F.Zama,PLOS ONE,15(8):1e17,082020]by adding the vaccinated population and framing the global model as a hybridswitched dynamical system.Aiming to represent the quantities that characterize the epidemic behaviour from an accurate fit to the observed data,we partition the observation time interval into sub-intervals.The model parameters change according to a switching rule depending on the data behaviour and the infection rate continuity condition.In particular,we study the representation of the infection rate both as linear and exponential piecewise continuous functions.We choose the length of sub-intervals balancing the data fit with the model complexity through the Bayesian Information Criterion.We tested the model on italian data and on local data from Emilia-Romagna region.The calibration of the model shows an excellent representation of the epidemic behaviour in both cases.Thirty days forecasts have proven to well reproduce the infection spread,better for regional than for national data.Both models produce accurate predictions of infected,but the exponential-based one perform better in most of the cases.Finally,we discuss different possible forecast scenarios obtained by simulating an increased vaccination rate.展开更多
Given the capabilities of modern high-performance missiles,efficient evasion maneuver strategies are crucial for enhancing UAV survivability.This paper addresses the integration of evasion strategies and maneuver timi...Given the capabilities of modern high-performance missiles,efficient evasion maneuver strategies are crucial for enhancing UAV survivability.This paper addresses the integration of evasion strategies and maneuver timing for targeted UAVs.First,a three-dimensional engagement scenario is modeled using the relative motion mechanism.Subsequently,a fundamental evasion strategy focusing on large roll maneuvers and two-phase acceleration is developed.With the initiation timing of direct force control designated as the control variable,the formulation of a constrained optimization problem to maximize miss distance is fully articulated.While preserving the high fidelity of the established switching model,the feasible timing intervals and the optimal timing are determined through numerical optimization.Finally,simulation experiments are conducted focusing on omnidirectional attacks from the upper hemisphere.The results demonstrate that by implementing specific evasion maneuvers at optimal timing,the target successfully escapes the effective range of the proximity fuse,thus confirming the feasibility of the proposed evasion maneuver and timing strategy.展开更多
In view of the abrupt and phased features of natural gas consumption,this paper attempts to predict natural gas consumption in China with a refined forecasting approach.First,we establish a Markov switching(MS)model t...In view of the abrupt and phased features of natural gas consumption,this paper attempts to predict natural gas consumption in China with a refined forecasting approach.First,we establish a Markov switching(MS)model to identify the phase characteristics after eliminating change points in the natural gas consumption sequence,using the product partition model(PPM).The results show that there are"rapid growth"and"slow growth"regimes in the development process of natural gas consumption in China.Second,the Bayesian model average(BMA)method is employed to determine the core determinants of natural gas consumption under sub-regimes,and it is determined that there are significant differences in the influencing factors under different regimes and periods.Third,this paper establishes the BMA model of the"rapid growth"regime after predicting the state of future natural gas consumption in China.We find that,compared to some other models,the BMA model that fully recognizes the regime without considering change points has the best predictive performance.Finally,the results of static and dynamic scenario analyses show that natural gas consumption continues to rise in 2019 and has obvious seasonal charac-teristics,while possible ultra-rapid growth of consumption in the future provides a new requirement for the supply of natural gas.展开更多
基金supported by the National Natural Science Foundation of China(No.61931011)the Jiangsu Provincial Key Research and Development Program,China(No.BE2021013-4)the Fundamental Research Project in University Characteristic Disciplines,China(No.ILF240071A24)。
文摘Unmanned Aerial Vehicles(UAVs)coupled with deep learning such as Convolutional Neural Networks(CNNs)have been widely applied across numerous domains,including agriculture,smart city monitoring,and fire rescue operations,owing to their malleability and versatility.However,the computation-intensive and latency-sensitive natures of CNNs present a formidable obstacle to their deployment on resource-constrained UAVs.Some early studies have explored a hybrid approach that dynamically switches between lightweight and complex models to balance accuracy and latency.However,they often overlook scenarios involving multiple concurrent CNN streams,where competition for resources between streams can substantially impact latency and overall system performance.In this paper,we first investigate the deployment of both lightweight and complex models for multiple CNN streams in UAV swarm.Specifically,we formulate an optimization problem to minimize the total latency across multiple CNN streams,under the constraints on UAV memory and the accuracy requirement of each stream.To address this problem,we propose an algorithm called Adaptive Model Switching of collaborative inference for MultiCNN streams(AMSM)to identify the inference strategy with a low latency.Simulation results demonstrate that the proposed AMSM algorithm consistently achieves the lowest latency while meeting the accuracy requirements compared to benchmark algorithms.
基金supported by the National Natural Science Foundation of China(Grant Nos.11172233,11472212,11272258,and 11302170)the Natural Science and Engineering Research Council of Canada(NSERC)
文摘This paper mainly investigates dynamics behavior of HIV （human immunodeficiency virus） infectious disease model with switching parameters, and combined bounded noise and Gaussian white noise. This model is different from existing HIV models. Based on stochastic Ito lemma and Razumikhin-type approach, some threshold conditions are established to guarantee the disease eradication or persistence. Results show that the smaller amplitude of bounded noise and R0 〈 1 can cause the disease to die out; the disease becomes persistent if R0 〉 1. Moreover, it is found that larger noise intensity suppresses the prevalence of the disease even if R0 〉 1. Some numerical examples are given to verify the obtained results.
文摘In the complex mechanical vibration environment, the dominant frequency of the system varies remarkably and swiftly under various running conditions, which also characterizes uncertainty and time-variation. It is very impending and important to suppress or isolate the detrimental vibrations related to the above memtoned system with active vibration control (AVC) technology. This paper presented the improved linear quadratic gaussian (LQG) control scheme with a specified filter to realize broadband disturbance/noise attenuation and assure intensive suppression of vibration at the key vibration frequency, then applies and modifies the multiple model switching tuning (MMST) control method by disturbance observation to track the variation of dominant vibration component timely. The effectiveness and superiority of the presented control method were demonstrated by numerical simulation and AVC experiment on a flexible cantilever beam under sweeping excitation.
基金Supported by the National Natural Science Foundation of China(61333010,21376077,61203157)the Natural Science Foundation of Shanghai(14ZR1421800)State Key Laboratory of Synthetical Automation for Process Industries(PAL-N201404)
文摘An improved nonlinear adaptive switching control method is presented to relax the assumption on the higher order nonlinear terms of a class of discrete-time non-affine nonlinear systems. The proposed control strategy is composed of a linear adaptive controller, a neural network(NN) based nonlinear adaptive controller and a switching mechanism. An incremental model is derived to represent the considered system and an improved robust adaptive law is chosen to update the parameters of the linear adaptive controller. A new performance criterion of the switching mechanism is designed to select the proper controller. Using this control scheme, all the signals in the system are proved to be bounded. Numerical examples verify the effectiveness of the proposed algorithm.
文摘Traffic modeling is a key step in several intelligent transportation systems（ITS） applications. This paper regards the traffic modeling through the enhancement of the cell transmission model. It considers the traffic flow as a hybrid dynamic system and proposes a piecewise switched linear traffic model. The latter allows an accurate modeling of the traffic flow in a given section by considering its geometry. On the other hand, the piecewise switched linear traffic model handles more than one congestion wave and has the advantage to be modular. The measurements at upstream and downstream boundaries are also used in this model in order to decouple the traffic flow dynamics of successive road portions. Finally, real magnetic sensor data, provided by the performance measurement system on a portion of the Californian SR60-E highway are used to validate the proposed model.
文摘A novel and accurate method is proposed to extract the intrinsic elements of the GaN high-electron-mobility transistor（HEMT） switch.The new extraction method is verified by comparing the simulated S-parameters with the measured data over the 5-40 GHz frequency range.The percentage errors E（ij） within 3.83% show the great agreement between the simulated S-parameters and the measured data.
基金supported by the National Natural Science Foundation of China(Grant No.NSFC41974204)。
文摘The cause of substorm onset is not yet understood. Chen CX(2016) proposed an entropy switch model, in which substorm onset results from the development of interchange instability. In this study, we sought observational evidence for this model by using Time History of Events and Macroscale Interactions during Substorms(THEMIS) data. We examined two events, one with and the other without a streamer before substorm onset. In contrast to the stable magnetosphere, where the total magnetic field strength is a decreasing function and entropy is an increasing function of the downtail distance, in both events the total magnetic field strength and entropy were reversed before substorm onset. After onset, the total magnetic field strength, entropy, and other plasma quantities fluctuated. In addition, a statistical study was performed. By confining the events with THEMIS satellites located in the downtail region between ~8 and ~12 Earth radii, and 3 hours before and after midnight, we found the occurrence rate of the total magnetic field strength reversal to be 69% and the occurrence rate of entropy reversal to be 77% of the total 205 events.
基金supported in part by Ministry of EducationSingapore+2 种基金under Ac RF TIER 1 Grant No.RG64/23in part by open project funding of Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education under Grant No.LICO2023YB01in part by the Eric and Wendy Schmidt AI in Science Postdoctoral Fellowship,a program of Schmidt Sciences。
文摘This paper proposes a data-driven learning-based approach to predictive control for switched nonlinear systems subject to state and control constraints and external stochastic disturbances.A switched Koopman modeling framework is developed,where a multi-mode neural network for state lifting is trained simultaneously with Koopman operators and state reconstruction matrices for all modes.This framework facilitates the construction of the switched linear Koopman model in a transformed space and effectively captures the dynamics of the original nonlinear system.A switched predictive control strategy is then designed to regulate the switched Koopman model with constrained states and control inputs against both the stochastic disturbances and the uncertainties introduced by the lifting neural network.The proposed control scheme ensures mean-square stability and guarantees boundedness during the online phase.Furthermore,boundedness analysis is performed to determine the bounded set of the original system state across all admissible switching sequences.The effectiveness of the proposed methodology is demonstrated through a case study of a gene regulatory network.
基金the National Social Science Fund of China(20CGL027)。
文摘The Internet is believed to bring more technological dividends to vulnerable farmers during the green agriculture transformation.However,this is different from the theory of skill-biased technological change,which emphasizes that individuals with higher levels of human capital and more technological endowments benefit more.This study investigates the effects of Internet use on farmers'adoption of integrated pest management(IPM),theoretically and empirically,based on a dataset containing 1015 farmers in China's Shandong Province.By exploring the perspective of rational inattention,the reasons for the heterogeneity of the effects across farmers with different endowments,i.e.,education and land size,are analyzed.The potential endogeneity issues are addressed using the endogenous switching probit model.The results reveal that:(1)although Internet use significantly positively affects farmers'adoption of IPM,vulnerable farmers do not benefit more from it.Considerable selection bias leads to an overestimation of technological dividends for vulnerable farmers;(2)different sources of technology information lead to the difference in the degree of farmers'rational inattention toward Internet information,which plays a crucial role in the heterogeneous effect of Internet use;and(3)excessive dependence on strong-tie social network information sources entraps vulnerable farmers in information cocoons,hindering their ability to reap the benefits of Internet use fully.Therefore,it is essential to promote services geared towards elderly-oriented Internet agricultural technology information and encourage farmers with strong Internet utilization skills to share technology information with other farmers actively.
基金supported by the Fundamental Research Funds for the Central Universities under Grant No.WK2100100019the National Natural Science Foundation of China under Grant No.61573330
文摘For the preparation of any target Bell state under continuous quantum measurement, this paper proposes a method which achieves the control objective by switching between two different models or by switching between two control channels under one model. Proper control Hamiltonians are selected for the two system models, a switching strategy between the two models is designed, and the stability of the whole switching system is proved in theory. For a given target Bell state, the effectiveness of the proposed switching control strategy between different models is illustrated through simulation experiments.
基金Yaojie Zhang acknowledges the financial support from the National Natural Science Foundation of China(72001110)the Fundamental Research Funds for the Central Universities(30919013232)+4 种基金the Research Fund for Young Teachers of School of Economics and Management,NJUST(JGQN2009)Yudong Wang acknowledges the financial support from the National Natural Science Foundation of China(72071114)Feng Ma acknowledges the support from the National Natural Science Foundation of China(71701170,72071162)Yu Wei acknowledges the support from the National Natural Science Foundation of China(71671145,71971191)Science and technology innovation team of Yunnan provincial.
文摘A well-documented finding is that explicitly using jumps cannot efficiently enhance the predictability of crude oil price volatility.To address this issue,we find a phenomenon,“momentum of jumps”(MoJ),that the predictive ability of the jump component is persistent when forecasting the oil futures market volatility.Specifically,we propose a strategy that allows the predictive model to switch between a benchmark model without jumps and an alternative model with a jump component according to their recent past forecasting performance.The volatility data are based on the intraday prices of West Texas Intermediate.Our results indicate that this simple strategy significantly outperforms the individual models and a series of competing strategies such as forecast combinations and shrinkage methods.A mean–variance investor who targets a constant Sharpe ratio can realize the highest economic gains using the MoJ-based volatility forecasts.Our findings survive a wide variety of robustness tests,including different jump measures,alternative volatility measures,various financial markets,and extensive model specifications.
基金Supported by Jiangsu Government Scholarship for Overseas Studiesthe NNSF of China(Grant Nos.11401419,11301369,11371274)+1 种基金the CPSF(2014M561453)the NSF of Jiangsu Province(Grant Nos.BK20140279,BK20130260)
文摘Regime switching,which is described by a Markov chain,is introduced in a Markov copula model.We prove that the marginals（X,H^i）,i = 1,2,3 of the Markov copula model（X,H） are still Markov processes and have martingale property.In this proposed model,a pricing formula of credit default swap（CDS） with bilateral counterparty risk is derived.
基金supported by the Natural Science Foundation of Changchun Normal University(No.2021-005).
文摘In this paper,a stochastic SIQS epidemic model perturbed by both white and telephone noises is investigated.By constructing several suitable Lyapunov functions,we obtain sufficient conditions for the existence of ergodic stationary distribution of the positive solution.Moreover,by solving the Fokker-Planck equation,we obtain the exact expression of probability density function around the quasi-equilibrium of the stochastic model.In addition,sufficient conditions for the extinction are established.Finally,the results of this paper are further verified by numerical simulation.
基金funded by SGCC Science and Technology Program under project Research on Electromagnetic Transient Simulation Technology for Large-scale MMC-HVDC Systems.
文摘Multi-terminal direct current(MTDC)grids provide the possibility of meshed interconnections between regional power systems and various renewable energy resources to boost supply reliability and economy.The modular multilevel converter(MMC)has become the basic building block for MTDC and DC grids due to its salient features,i.e.,modularity and scalability.Therefore,the MMC-based MTDC systems should be pervasively embedded into the present power system to improve system performance.However,several technical challenges hamper their practical applications and deployment,including modeling,control,and protection of the MMC-MTDC grids.This paper presents a comprehensive investigation and reference in modeling,control,and protection of the MMC-MTDC grids.A general overview of state-of-the-art modeling techniques of the MMC along with their performance in simulation analysis for MTDC applications is provided.A review of control strategies of the MMC-MTDC grids which provide AC system support is presented.State-of-the art protection techniques of the MMCMTDC systems are also investigated.Finally,the associated research challenges and trends are highlighted.
文摘This paper presents the complete mathematical model and predicts the performance of switched reluctance generator with time average and small signal models. The complete mathematical model is developed in three stages. First, a switching model is developed based on quasi-linear inductance profile. Next, based on the switching behaviour, a time average model is obtained to measure the difference between the excitation and generation time in each switching cycle. Finally, to track control voltage and current wave shapes, a small signal model is designed. The effectiveness of the complete multilevel model combining electrical machine, power converter, load and control with programming language is demonstrated through simulations. A PI controller is used for controlling the voltage of the generator. The results presented show that the controller exhibits accurate tracking control of load voltage under different operating conditions. This demonstrates that the proposed model is able to perform an accurate control of the generated output voltage even in transient situations. The simulation is performed to choose the control parameters and study the performance of switched reluctance generator prior to its actual implementation. Initial experimental results are presented using NI-Data acquisition card to control the output power according to load requirements.
基金supported by the National Natural Science Foundation of China under Grant Nos.61773100 and 61773098IAPI Fundamental Research Funds under Grant No.2013ZCX03-02Fundamental Research Funds for the Central Universities under Grant No.N150404024
文摘This paper investigates the problem of global disturbance rejection for a class of switched nonlinear systems where the solvability of the disturbance rejection problem for subsystems is not assumed. The disturbances are assumed to be sinusoidal with completely unknown frequencies, phases and amplitudes. First, as an extension of the classic concept of internal model for non-switched systems, a switched internal model is proposed. Second, in order to solve the problem under study, an adaptive control method is established on the basis of the multiple Lyapunov functions method. Also,adaptive state-feedback controllers of subsystems are designed and incorporated with a switching law to asymptotically reject the unknown disturbances. Finally, an example is provided to demonstrate the effectiveness of the proposed design method.
基金supported by the National Natural Science Foundation of China (61574108, 61574112, 61504099)the Natural Science Basic Research Plan in Shaanxi Province of China (605119425012)
文摘Gallium nitride （GaN） high electron mobility transistor （HEMT） with symmetrical structure as a control device is discussed in this paper. The equivalent circuit model is proposed on the basis of physical and electrical properties of the GaN HEMT device. A transistor with 0.5 μm gate length and 6 x 125 gm gate width is fabricated to verify the model, which can be treated as a single pole single throw （SPST） switch due to the ON state and OFF state. The measurement results show a lzood agreement with the simulation results, which demonstrates the effectiveness of the proposed model.
文摘This paper presents a new hybrid compartmental model for studying the COVID-19 epidemic evolution in Italy since the beginning of the vaccination campaign started on 2020/12/27 and shows forecasts of the epidemic evolution in Italy in the first six months.The proposed compartmental model subdivides the population into six compartments and extends the SEIRD model proposed in[E.L.Piccolomini and F.Zama,PLOS ONE,15(8):1e17,082020]by adding the vaccinated population and framing the global model as a hybridswitched dynamical system.Aiming to represent the quantities that characterize the epidemic behaviour from an accurate fit to the observed data,we partition the observation time interval into sub-intervals.The model parameters change according to a switching rule depending on the data behaviour and the infection rate continuity condition.In particular,we study the representation of the infection rate both as linear and exponential piecewise continuous functions.We choose the length of sub-intervals balancing the data fit with the model complexity through the Bayesian Information Criterion.We tested the model on italian data and on local data from Emilia-Romagna region.The calibration of the model shows an excellent representation of the epidemic behaviour in both cases.Thirty days forecasts have proven to well reproduce the infection spread,better for regional than for national data.Both models produce accurate predictions of infected,but the exponential-based one perform better in most of the cases.Finally,we discuss different possible forecast scenarios obtained by simulating an increased vaccination rate.
文摘Given the capabilities of modern high-performance missiles,efficient evasion maneuver strategies are crucial for enhancing UAV survivability.This paper addresses the integration of evasion strategies and maneuver timing for targeted UAVs.First,a three-dimensional engagement scenario is modeled using the relative motion mechanism.Subsequently,a fundamental evasion strategy focusing on large roll maneuvers and two-phase acceleration is developed.With the initiation timing of direct force control designated as the control variable,the formulation of a constrained optimization problem to maximize miss distance is fully articulated.While preserving the high fidelity of the established switching model,the feasible timing intervals and the optimal timing are determined through numerical optimization.Finally,simulation experiments are conducted focusing on omnidirectional attacks from the upper hemisphere.The results demonstrate that by implementing specific evasion maneuvers at optimal timing,the target successfully escapes the effective range of the proximity fuse,thus confirming the feasibility of the proposed evasion maneuver and timing strategy.
基金The paper is supported by the National Natural Science Foundation of China(NSFC)under grant No.71473155the New Star of Youth Science and Technology Plan Project in China’s Shaanxi Province with No.2016KJXX-142016 Annual Basic Scientific Research Project of Xidian University with No.JB160603.
文摘In view of the abrupt and phased features of natural gas consumption,this paper attempts to predict natural gas consumption in China with a refined forecasting approach.First,we establish a Markov switching(MS)model to identify the phase characteristics after eliminating change points in the natural gas consumption sequence,using the product partition model(PPM).The results show that there are"rapid growth"and"slow growth"regimes in the development process of natural gas consumption in China.Second,the Bayesian model average(BMA)method is employed to determine the core determinants of natural gas consumption under sub-regimes,and it is determined that there are significant differences in the influencing factors under different regimes and periods.Third,this paper establishes the BMA model of the"rapid growth"regime after predicting the state of future natural gas consumption in China.We find that,compared to some other models,the BMA model that fully recognizes the regime without considering change points has the best predictive performance.Finally,the results of static and dynamic scenario analyses show that natural gas consumption continues to rise in 2019 and has obvious seasonal charac-teristics,while possible ultra-rapid growth of consumption in the future provides a new requirement for the supply of natural gas.
