Aiming at the problems of large fluctuation of output active power and poor control performance in the process of frequency support of an energy-storage-type static-var-generator(ESVG),the adaptive adjustment control ...Aiming at the problems of large fluctuation of output active power and poor control performance in the process of frequency support of an energy-storage-type static-var-generator(ESVG),the adaptive adjustment control method for its active-loop parameters is used to realize thewind-farmfrequency support,which has become the current research hotspot.Taking the ESVG with a supercapacitor on the DC side as the research object,the influence trend of the change of virtual rotation inertia and virtual damping coefficient on its virtual angular velocity and power angle is analyzed.Then,the constraint relationship between the equivalent virtual inertia time constant of the supercapacitor and the virtual rotation inertia of the ESVG is clarified.Then,combined with the second-order response characteristics of the ESVG power control loop,the selection principles of the frequency modulation coefficient,the virtual rotation inertia,and the virtual damping coefficient are determined.An ESVG adjustment control method,considering the adaptive adjustment of the active loop parameters of the supercapacitor equivalent inertia,is proposed.While ensuring the frequency support capability of the ESVG,the fluctuation degree of its output active power and the virtual angular velocity are suppressed,and the proposed adjustment method also improves the stability of the ESVG control system and the frequency support capability for the wind farm.Finally,the simulation verifies the correctness of the theoretical analysis and the effectiveness of the proposed strategy.展开更多
For the terminal guidance problem of missiles intercepting maneuvering targets in the three-dimensional space, the design of guidance laws for non-decoupling three-dimensional engage- ment geometry is studied. Firstly...For the terminal guidance problem of missiles intercepting maneuvering targets in the three-dimensional space, the design of guidance laws for non-decoupling three-dimensional engage- ment geometry is studied. Firstly, by introducing a finite time integral sliding mode manifold, a novel guidance law based on the integral sliding mode control is presented with the target acceler- ation as a known bounded external disturbance. Then, an improved adaptive guidance law based on the integral sliding mode control without the information of the upper bound on the target accel- eration is developed, where the upper bound of the target acceleration is estimated online by a designed adaptive law. The both presented guidance laws can make sure that the elevation angular rate of the line-of-sight and the azimuth angular rate of the line-of-sight converge to zero in finite time. In the end, the results of the guidance performance for the proposed guidance laws are pre- sented by numerical simulations. Although the designed guidance laws are developed for the con- stant speed missiles, the simulation results for the time-varying speed missiles are also shown to further confirm the designed guidance laws.展开更多
To intercept maneuvering targets at desired impact angles, a three-dimensional terminal guidance problem is investigated in this study. Because of a short terminal guidance time, a finitetime impact angle control guid...To intercept maneuvering targets at desired impact angles, a three-dimensional terminal guidance problem is investigated in this study. Because of a short terminal guidance time, a finitetime impact angle control guidance law is developed using the fast nonsingular terminal sliding mode control theory. However, the guidance law requires the upper bound of lumped uncertainty including target acceleration, which may not be accurately obtained. Therefore, by adopting a novel reaching law, an adaptive sliding mode guidance law is provided to release the drawback. At the same time, this method can accelerate the convergence rate and weaken the chattering phenomenon to a certain extent. In addition, another novel adaptive guidance law is also derived; this ensures systems asymptotic and finite-time stability without the knowledge of perturbations bounds.Numerical simulations have demonstrated that all the three guidance laws have effective performances and outperform the traditional terminal guidance laws.展开更多
The traditional guidance law only guarantees the accuracy of attacking a target.However,the look angle and acceleration constraints are indispensable in applications.A new adaptive three-dimensional proportional navig...The traditional guidance law only guarantees the accuracy of attacking a target.However,the look angle and acceleration constraints are indispensable in applications.A new adaptive three-dimensional proportional navigation(PN)guidance law is proposed based on convex optimization.Decomposition of the three-dimensional space is carried out to establish threedimensional kinematic engagements.The constraints and the performance index are disposed by using the convex optimization method.PN guidance gains can be obtained by solving the optimization problem.This solution is more rapid and programmatic than the traditional method and provides a foundation for future online guidance methods,which is of great value for engineering applications.展开更多
To overcome the limitations posed by three-dimensional corner separation,this paper proposes a novel flow control technology known as passive End-Wall(EW)self-adaptive jet.Two single EW slotted schemes(EWS1 and EWS2),...To overcome the limitations posed by three-dimensional corner separation,this paper proposes a novel flow control technology known as passive End-Wall(EW)self-adaptive jet.Two single EW slotted schemes(EWS1 and EWS2),alongside a combined(COM)scheme featuring double EW slots,were investigated.The results reveal that the EW slot,driven by pressure differentials between the pressure and suction sides,can generate an adaptive jet with escalating velocity as the operational load increases.This high-speed jet effectively re-excites the local low-energy fluid,thereby mitigating the corner separation.Notably,the EWS1 slot,positioned near the blade leading edge,exhibits relatively low jet velocities at negative incidence angles,causing jet separation and exacerbating the corner separation.Besides,the EWS2 slot is close to the blade trailing edge,resulting in massive low-energy fluid accumulating and separating before the slot outlet at positive incidence angles.In contrast,the COM scheme emerges as the most effective solution for comprehensive corner separation control.It can significantly reduce the total pressure loss and improve the static pressure coefficient for the ORI blade at 0°-4° incidence angles,while causing minimal negative impact on the aerodynamic performance at negative incidence angles.Therefore,the corner stall is delayed,and the available incidence angle range is broadened from -10°--2°to -10°-4°.This holds substantial promise for advancing the aerodynamic performance,operational stability,and load capacity of future highly loaded compressors.展开更多
Prediction of primary quality variables in real time with adaptation capability for varying process conditions is a critical task in process industries.This article focuses on the development of non-linear adaptive so...Prediction of primary quality variables in real time with adaptation capability for varying process conditions is a critical task in process industries.This article focuses on the development of non-linear adaptive soft sensors for prediction of naphtha initial boiling point(IBP)and end boiling point(EBP)in crude distillation unit.In this work,adaptive inferential sensors with linear and non-linear local models are reported based on recursive just in time learning(JITL)approach.The different types of local models designed are locally weighted regression(LWR),multiple linear regression(MLR),partial least squares regression(PLS)and support vector regression(SVR).In addition to model development,the effect of relevant dataset size on model prediction accuracy and model computation time is also investigated.Results show that the JITL model based on support vector regression with iterative single data algorithm optimization(ISDA)local model(JITL-SVR:ISDA)yielded best prediction accuracy in reasonable computation time.展开更多
Developing the alternative supported noble metal catalysts with low cost,high catalytic efficiency,and good resistance toward carbon dioxide and water vapor is critically demanded for the oxidative removal of volatile...Developing the alternative supported noble metal catalysts with low cost,high catalytic efficiency,and good resistance toward carbon dioxide and water vapor is critically demanded for the oxidative removal of volatile organic compounds(VOCs).In this work,we prepared the mesoporous chromia-supported bimetallic Co and Ni single-atom(Co_(1)Ni_(1)/meso-Cr_(2)O_(3))and bimetallic Co and Ni nanoparticle(Co_(NP)Ni_(NP)/mesoCr_(2)O_(3))catalysts adopting the one-pot polyvinyl pyrrolidone(PVP)-and polyvinyl alcohol(PVA)-protecting approaches,respectively.The results indicate that the Co_(1)Ni_(1)/meso-Cr_(2)O_(3)catalyst exhibited the best catalytic activity for n-hexane(C_(6)H_(14))combustion(T_(50%)and T_(90%)were 239 and 263℃ at a space velocity of 40,000 mL g^(-1)h^(-1);apparent activation energy and specific reaction rate at 260℃ were 54.7 kJ mol^(-1)and 4.3×10^(-7)mol g^(-1)_(cat)s^(-1),respectively),which was associated with its higher(Cr^(5+)+Cr^(6+))amount,large n-hexane adsorption capacity,and good lattice oxygen mobility that could enhance the deep oxidation of n-hexane,in which Ni_(1) was beneficial for the enhancements in surface lattice oxygen mobility and low-temperature reducibility,while Co_(1) preferred to generate higher contents of the high-valence states of chromium and surface oxygen species as well as adsorption and activation of n-hexane.n-Hexane combustion takes place via the Mars van Krevelen(MvK)mechanism,and its reaction pathways are as follows:n-hexane→olefins or 3-hexyl hydroperoxide→3-hexanone,2-hexanone or 2,5-dimethyltetrahydrofuran→2-methyloxirane or 2-ethyl-oxetane→acrylic acid→CO_x→CO_(2)and H_(2)O.展开更多
This study examines how organizational support influences the career adaptability of novice university teachers in Guangdong,China,and the mediating role of teacher self-efficacy.Drawing on social cognitive theory and...This study examines how organizational support influences the career adaptability of novice university teachers in Guangdong,China,and the mediating role of teacher self-efficacy.Drawing on social cognitive theory and organizational support theory,we hypothesized that organizational support would positively predict career adaptability through self-efficacy.A cross-sectional survey was conducted with 326 novice teachers(with 1–3 years of teaching experience)from 12 universities in Guangdong.Data were analyzed using correlation analysis,hierarchical regression,and bootstrap.Results showed that:(1)organizational support was positively associated with both self-efficacy(r=0.62,P<0.001)and career adaptability(r=0.58,P<0.001);(2)self-efficacy fully mediated the relationship between organizational support and career adaptability(indirect effect=0.24,95%CI[0.18,0.31]),with a partial reduction in the direct effect fromβ=0.35 toβ=0.17(P<0.05);(3)female teachers reported higher self-efficacy than males(P<0.05),and teachers with 2 years of experience showed significantly higher adaptability than those with 1 year(P<0.05).The findings highlight the critical role of self-efficacy in translating organizational support into adaptability,providing empirical evidence for universities to design targeted support strategies.展开更多
With the rapid evolution of artificial intelligence(AI)technologies,the medical industry is undergoing a profound transformation driven by data intelligence.As the foundational element for intelligent diagnosis,precis...With the rapid evolution of artificial intelligence(AI)technologies,the medical industry is undergoing a profound transformation driven by data intelligence.As the foundational element for intelligent diagnosis,precision prevention,and public health governance,medical data is characterized by massive volume,complex structure,diverse sources,high dimensionality,strong privacy,and high timeliness.Traditional data analysis methods are no longer sufficient to meet the comprehensive requirements of data security,intelligent processing,and decision support.Through techniques such as machine learning,deep learning,natural language processing,and multimodal fusion,AI provides robust technical support for medical data cleaning,governance,mining,and application.At the data level,intelligent algorithms enable the standardization,structuring,and interoperability of medical data,promoting information sharing across medical systems.At the model level,AI supports auxiliary diagnosis and precision treatment through image recognition,medical record analysis,and knowledge graph construction.At the system level,intelligent decision-support platforms continuously enhance the efficiency and accuracy of healthcare services.However,the widespread adoption of AI in medicine still faces challenges such as privacy protection,data security,model interpretability,and the lack of unified industry standards.Based on a systematic review of AI’s key supporting technologies in medical data processing and application,this paper focuses on the compliance challenges and adaptation strategies during industry integration and proposes an adaptation framework centered on“technological trustworthiness,data security,and industry collaboration.”The study provides theoretical and practical insights for promoting the standardized and sustainable development of AI in the healthcare industry.展开更多
This study explored the relationship between perceived social support and employment anxiety among Chinese college students,as well as the mediating and moderating effects of psychological resilience and career adapta...This study explored the relationship between perceived social support and employment anxiety among Chinese college students,as well as the mediating and moderating effects of psychological resilience and career adaptability on this relationship.A total of 1928 college students(females=1371,mean age=20.42,SD=1.05)completed the Perceived Social Support Scale,Employment Anxiety Questionnaire,Connor-Davidson Resilience Scale and Career Adapt-Abilities Scale.Mediation analysis results showed that psychological resilience mediated the relationship between perceived social support and employment anxiety for lower employment anxiety.Career adaptability moderated the mediating effect of psychological resilience for lower employment anxiety than with either of the variables alone.Thefindings are consistent with cognitive diathesis-stress theory and career construction theory which propose that individuals’cognitive structures and psychological predispositions interact with environmental stressors to shape their career development and psychological well-being.Essentially,students who have a robust social support system,high career adaptability,and are psychologically resilient are less likely to experience employment anxiety.展开更多
To overcome the challenges associated with predicting gas extraction performance and mitigating the gradual decline in extraction volume,which adversely impacts gas utilization efficiency in mines,a gas extraction pur...To overcome the challenges associated with predicting gas extraction performance and mitigating the gradual decline in extraction volume,which adversely impacts gas utilization efficiency in mines,a gas extraction pure volume prediction model was developed using Support Vector Regression(SVR)and Random Forest(RF),with hyperparameters fine-tuned via the Genetic Algorithm(GA).Building upon this,an adaptive control model for gas extraction negative pressure was formulated to maximize the extracted gas volume within the pipeline network,followed by field validation experiments.Experimental results indicate that the GA-SVR model surpasses comparable models in terms of mean absolute error,root mean square error,and mean absolute percentage error.In the extraction process of bedding boreholes,the influence of negative pressure on gas extraction concentration diminishes over time,yet it remains a critical factor in determining the extracted pure volume.In contrast,throughout the entire extraction period of cross-layer boreholes,both extracted pure volume and concentration exhibit pronounced sensitivity to fluctuations in extraction negative pressure.Field experiments demonstrated that the adaptive controlmodel enhanced the average extracted gas volume by 5.08% in the experimental borehole group compared to the control group during the later extraction stage,with a more pronounced increase of 7.15% in the first 15 days.The research findings offer essential technical support for the efficient utilization and long-term sustainable development of mine gas resources.The research findings offer essential technical support for gas disaster mitigation and the sustained,efficient utilization of mine gas.展开更多
This paper proposes an attitude control strategy for a flexible satellite equipped with an orthogonal cluster of three-dimensional(3D)magnetically suspended wheels(MSWs).The mathematical model for the satellite incorp...This paper proposes an attitude control strategy for a flexible satellite equipped with an orthogonal cluster of three-dimensional(3D)magnetically suspended wheels(MSWs).The mathematical model for the satellite incorporating flexible appendages and an orthogonal cluster of magnetically suspended reaction wheel actuators is initially developed.After that,an adaptive attitude controller is designed with a switching surface of variable structure,an adaptive law for estimating inertia matrix uncertainty,and a fuzzy disturbance observer for estimating disturbance torques.Additionally,a Moore-Penrose-based steering law is proposed to derive the tilt angle commands of the orthogonal configuration of the 3D MSW to follow the designed control signal.Finally,numerical simulations are presented to validate the effectiveness of the proposed control strategy.展开更多
An adaptive blind support vector machine equalizer（ABSVME） is presented in this paper.The method is based upon least square support vector machine（LSSVM）,and stems from signal feature reconstruction idea.By oversa...An adaptive blind support vector machine equalizer（ABSVME） is presented in this paper.The method is based upon least square support vector machine（LSSVM）,and stems from signal feature reconstruction idea.By oversampling the output of a LSSVM equalizer and exploiting a reasonable decorrelation cost function design,the method achieves fine online channel tracing with Kumar express algorithm and static iterative learning algorithm incorporated.The method is verified through simulation and compared with other nonlinear equalizers.The results show that it provides excellent performance in nonlinear equalization and time-varying channel tracing.Although a constant module equalization algorithm requires that the signal has characteristic of constant module,this method has no such requirement.展开更多
The performance of data-driven models relies heavily on the amount and quality of training samples, so it might deteriorate significantly in the regions where samples are scarce. The objective of this paper is to deve...The performance of data-driven models relies heavily on the amount and quality of training samples, so it might deteriorate significantly in the regions where samples are scarce. The objective of this paper is to develop an online SVR model updating strategy to track the change in the process characteristics efficiently with affordable computational burden. This is achieved by adding a new sample that violates the Karush–Kuhn–Tucker conditions of the existing SVR model and by deleting the old sample that has the maximum distance with respect to the newly added sample in feature space. The benefits offered by such an updating strategy are exploited to develop an adaptive model-based control scheme, where model updating and control task perform alternately.The effectiveness of the adaptive controller is demonstrated by simulation study on a continuous stirred tank reactor. The results reveal that the adaptive MPC scheme outperforms its non-adaptive counterpart for largemagnitude set point changes and variations in process parameters.展开更多
There are differences between the different individuals of learning. Adaptive learning support system is a learning system, which provides the learning supports suitable for the characteristics of the individuals acco...There are differences between the different individuals of learning. Adaptive learning support system is a learning system, which provides the learning supports suitable for the characteristics of the individuals according to the differences in the learning of individuals. In this paper, through the analysis on the adaptive learning support system, a system framework based on SOA is proposed and the research methods of the metadata model are emphatically discussed.展开更多
The start-up current control of the high-speed brushless DC（HS-BLDC） motor is a challenging research topic. To effectively control the start-up current of the sensorless HS-BLDC motor, an adaptive control method is ...The start-up current control of the high-speed brushless DC（HS-BLDC） motor is a challenging research topic. To effectively control the start-up current of the sensorless HS-BLDC motor, an adaptive control method is proposed based on the adaptive neural network（ANN）inverse system and the two degrees of freedom（2-DOF） internal model controller（IMC）. The HS-BLDC motor is identified by the online least squares support vector machine（OLS-SVM） algorithm to regulate the ANN inverse controller parameters in real time. A pseudo linear system is developed by introducing the constructed real-time inverse system into the original HS-BLDC motor system. Based on the characteristics of the pseudo linear system, an extra closed-loop feedback control strategy based on the 2-DOF IMC is proposed to improve the transient response performance and enhance the stability of the control system. The simulation and experimental results show that the proposed control method is effective and perfect start-up current tracking performance is achieved.展开更多
In order to establish an adaptive turbo-shaft engine model with high accuracy, a new modeling method based on parameter selection （PS） algorithm and multi-input multi-output recursive reduced least square support ve...In order to establish an adaptive turbo-shaft engine model with high accuracy, a new modeling method based on parameter selection （PS） algorithm and multi-input multi-output recursive reduced least square support vector regression （MRR-LSSVR） machine is proposed. Firstly, the PS algorithm is designed to choose the most reasonable inputs of the adaptive module. During this process, a wrapper criterion based on least square support vector regression （LSSVR） machine is adopted, which can not only reduce computational complexity but also enhance generalization performance. Secondly, with the input variables determined by the PS algorithm, a mapping model of engine parameter estimation is trained off-line using MRR-LSSVR, which has a satisfying accuracy within 5＆. Finally, based on a numerical simulation platform of an integrated helicopter/ turbo-shaft engine system, an adaptive turbo-shaft engine model is developed and tested in a certain flight envelope. Under the condition of single or multiple engine components being degraded, many simulation experiments are carried out, and the simulation results show the effectiveness and validity of the proposed adaptive modeling method.展开更多
As a primary defense technique, intrusion detection becomes more and more significant since the security of the networks is one of the most critical issues in the world. We present an adaptive collaboration intrusion ...As a primary defense technique, intrusion detection becomes more and more significant since the security of the networks is one of the most critical issues in the world. We present an adaptive collaboration intrusion detection method to improve the safety of a network. A self-adaptive and collaborative intrusion detection model is built by applying the Environmentsclasses, agents, roles, groups, and objects(E-CARGO) model. The objects, roles, agents, and groups are designed by using decision trees(DTs) and support vector machines(SVMs), and adaptive scheduling mechanisms are set up. The KDD CUP 1999 data set is used to verify the effectiveness of the method. The experimental results demonstrate the feasibility and efficiency of the proposed collaborative and adaptive intrusion detection method. Also, the proposed method is shown to be more predominant than the methods that use a set of single type support vector machine(SVM) in terms of detection precision rate and recall rate.展开更多
基金funded by the Science and Technology Project of State Grid Corporation,grant number 5500-202329500A-3-2-ZN,funding data 2023.10–2025.12.
文摘Aiming at the problems of large fluctuation of output active power and poor control performance in the process of frequency support of an energy-storage-type static-var-generator(ESVG),the adaptive adjustment control method for its active-loop parameters is used to realize thewind-farmfrequency support,which has become the current research hotspot.Taking the ESVG with a supercapacitor on the DC side as the research object,the influence trend of the change of virtual rotation inertia and virtual damping coefficient on its virtual angular velocity and power angle is analyzed.Then,the constraint relationship between the equivalent virtual inertia time constant of the supercapacitor and the virtual rotation inertia of the ESVG is clarified.Then,combined with the second-order response characteristics of the ESVG power control loop,the selection principles of the frequency modulation coefficient,the virtual rotation inertia,and the virtual damping coefficient are determined.An ESVG adjustment control method,considering the adaptive adjustment of the active loop parameters of the supercapacitor equivalent inertia,is proposed.While ensuring the frequency support capability of the ESVG,the fluctuation degree of its output active power and the virtual angular velocity are suppressed,and the proposed adjustment method also improves the stability of the ESVG control system and the frequency support capability for the wind farm.Finally,the simulation verifies the correctness of the theoretical analysis and the effectiveness of the proposed strategy.
基金financial support provided by the National Natural Science Foundation of China(Nos.61174037 and 61021002)the Aeronautical Science Foundation of China(No.20140177002)
文摘For the terminal guidance problem of missiles intercepting maneuvering targets in the three-dimensional space, the design of guidance laws for non-decoupling three-dimensional engage- ment geometry is studied. Firstly, by introducing a finite time integral sliding mode manifold, a novel guidance law based on the integral sliding mode control is presented with the target acceler- ation as a known bounded external disturbance. Then, an improved adaptive guidance law based on the integral sliding mode control without the information of the upper bound on the target accel- eration is developed, where the upper bound of the target acceleration is estimated online by a designed adaptive law. The both presented guidance laws can make sure that the elevation angular rate of the line-of-sight and the azimuth angular rate of the line-of-sight converge to zero in finite time. In the end, the results of the guidance performance for the proposed guidance laws are pre- sented by numerical simulations. Although the designed guidance laws are developed for the con- stant speed missiles, the simulation results for the time-varying speed missiles are also shown to further confirm the designed guidance laws.
基金co-supported by the National Natural Science Foundation of China (No. 61333003)the China Aerospace Science and Technology Innovation Foundation (No. JZ20160008)
文摘To intercept maneuvering targets at desired impact angles, a three-dimensional terminal guidance problem is investigated in this study. Because of a short terminal guidance time, a finitetime impact angle control guidance law is developed using the fast nonsingular terminal sliding mode control theory. However, the guidance law requires the upper bound of lumped uncertainty including target acceleration, which may not be accurately obtained. Therefore, by adopting a novel reaching law, an adaptive sliding mode guidance law is provided to release the drawback. At the same time, this method can accelerate the convergence rate and weaken the chattering phenomenon to a certain extent. In addition, another novel adaptive guidance law is also derived; this ensures systems asymptotic and finite-time stability without the knowledge of perturbations bounds.Numerical simulations have demonstrated that all the three guidance laws have effective performances and outperform the traditional terminal guidance laws.
基金supported by the National Natural Science Foundation of China(61803357)。
文摘The traditional guidance law only guarantees the accuracy of attacking a target.However,the look angle and acceleration constraints are indispensable in applications.A new adaptive three-dimensional proportional navigation(PN)guidance law is proposed based on convex optimization.Decomposition of the three-dimensional space is carried out to establish threedimensional kinematic engagements.The constraints and the performance index are disposed by using the convex optimization method.PN guidance gains can be obtained by solving the optimization problem.This solution is more rapid and programmatic than the traditional method and provides a foundation for future online guidance methods,which is of great value for engineering applications.
基金sponsored by the National Natural Science Foundation of China(No.52106057)the National Major Science and Technology Projects of China(No.2017-Ⅱ-0001-0013)+2 种基金Fundamental Research Funds for the Central Universities of China(No.D5000210483)the Foundation of State Level Key Laboratory of Airfoil and Cascade Aerodynamics of China(Nos.D5150210006 and D5050210015)the Innovation Foundation for Doctor Dissertation of Northwestern Polytechnical University of China(No.CX2023012).
文摘To overcome the limitations posed by three-dimensional corner separation,this paper proposes a novel flow control technology known as passive End-Wall(EW)self-adaptive jet.Two single EW slotted schemes(EWS1 and EWS2),alongside a combined(COM)scheme featuring double EW slots,were investigated.The results reveal that the EW slot,driven by pressure differentials between the pressure and suction sides,can generate an adaptive jet with escalating velocity as the operational load increases.This high-speed jet effectively re-excites the local low-energy fluid,thereby mitigating the corner separation.Notably,the EWS1 slot,positioned near the blade leading edge,exhibits relatively low jet velocities at negative incidence angles,causing jet separation and exacerbating the corner separation.Besides,the EWS2 slot is close to the blade trailing edge,resulting in massive low-energy fluid accumulating and separating before the slot outlet at positive incidence angles.In contrast,the COM scheme emerges as the most effective solution for comprehensive corner separation control.It can significantly reduce the total pressure loss and improve the static pressure coefficient for the ORI blade at 0°-4° incidence angles,while causing minimal negative impact on the aerodynamic performance at negative incidence angles.Therefore,the corner stall is delayed,and the available incidence angle range is broadened from -10°--2°to -10°-4°.This holds substantial promise for advancing the aerodynamic performance,operational stability,and load capacity of future highly loaded compressors.
文摘Prediction of primary quality variables in real time with adaptation capability for varying process conditions is a critical task in process industries.This article focuses on the development of non-linear adaptive soft sensors for prediction of naphtha initial boiling point(IBP)and end boiling point(EBP)in crude distillation unit.In this work,adaptive inferential sensors with linear and non-linear local models are reported based on recursive just in time learning(JITL)approach.The different types of local models designed are locally weighted regression(LWR),multiple linear regression(MLR),partial least squares regression(PLS)and support vector regression(SVR).In addition to model development,the effect of relevant dataset size on model prediction accuracy and model computation time is also investigated.Results show that the JITL model based on support vector regression with iterative single data algorithm optimization(ISDA)local model(JITL-SVR:ISDA)yielded best prediction accuracy in reasonable computation time.
基金supported by the National Natural Science Committee of China-Liaoning Provincial People's Government Joint Fund(U1908204)National Natural Science Foundation of China(21876006,21976009,and 21961160743)+2 种基金Foundation on the Creative Research Team Construction Promotion Project of Beijing Municipal Institutions(IDHT20190503)Natural Science Foundation of Beijing Municipal Commission of Education(KM201710005004)Development Program for the Youth Outstanding-Notch Talent of Beijing Municipal Commission of Education(CIT&TCD201904019)。
文摘Developing the alternative supported noble metal catalysts with low cost,high catalytic efficiency,and good resistance toward carbon dioxide and water vapor is critically demanded for the oxidative removal of volatile organic compounds(VOCs).In this work,we prepared the mesoporous chromia-supported bimetallic Co and Ni single-atom(Co_(1)Ni_(1)/meso-Cr_(2)O_(3))and bimetallic Co and Ni nanoparticle(Co_(NP)Ni_(NP)/mesoCr_(2)O_(3))catalysts adopting the one-pot polyvinyl pyrrolidone(PVP)-and polyvinyl alcohol(PVA)-protecting approaches,respectively.The results indicate that the Co_(1)Ni_(1)/meso-Cr_(2)O_(3)catalyst exhibited the best catalytic activity for n-hexane(C_(6)H_(14))combustion(T_(50%)and T_(90%)were 239 and 263℃ at a space velocity of 40,000 mL g^(-1)h^(-1);apparent activation energy and specific reaction rate at 260℃ were 54.7 kJ mol^(-1)and 4.3×10^(-7)mol g^(-1)_(cat)s^(-1),respectively),which was associated with its higher(Cr^(5+)+Cr^(6+))amount,large n-hexane adsorption capacity,and good lattice oxygen mobility that could enhance the deep oxidation of n-hexane,in which Ni_(1) was beneficial for the enhancements in surface lattice oxygen mobility and low-temperature reducibility,while Co_(1) preferred to generate higher contents of the high-valence states of chromium and surface oxygen species as well as adsorption and activation of n-hexane.n-Hexane combustion takes place via the Mars van Krevelen(MvK)mechanism,and its reaction pathways are as follows:n-hexane→olefins or 3-hexyl hydroperoxide→3-hexanone,2-hexanone or 2,5-dimethyltetrahydrofuran→2-methyloxirane or 2-ethyl-oxetane→acrylic acid→CO_x→CO_(2)and H_(2)O.
基金supported by the Teaching Quality and Teaching Reform Project of Dongguan City University(JY2022022301).
文摘This study examines how organizational support influences the career adaptability of novice university teachers in Guangdong,China,and the mediating role of teacher self-efficacy.Drawing on social cognitive theory and organizational support theory,we hypothesized that organizational support would positively predict career adaptability through self-efficacy.A cross-sectional survey was conducted with 326 novice teachers(with 1–3 years of teaching experience)from 12 universities in Guangdong.Data were analyzed using correlation analysis,hierarchical regression,and bootstrap.Results showed that:(1)organizational support was positively associated with both self-efficacy(r=0.62,P<0.001)and career adaptability(r=0.58,P<0.001);(2)self-efficacy fully mediated the relationship between organizational support and career adaptability(indirect effect=0.24,95%CI[0.18,0.31]),with a partial reduction in the direct effect fromβ=0.35 toβ=0.17(P<0.05);(3)female teachers reported higher self-efficacy than males(P<0.05),and teachers with 2 years of experience showed significantly higher adaptability than those with 1 year(P<0.05).The findings highlight the critical role of self-efficacy in translating organizational support into adaptability,providing empirical evidence for universities to design targeted support strategies.
文摘With the rapid evolution of artificial intelligence(AI)technologies,the medical industry is undergoing a profound transformation driven by data intelligence.As the foundational element for intelligent diagnosis,precision prevention,and public health governance,medical data is characterized by massive volume,complex structure,diverse sources,high dimensionality,strong privacy,and high timeliness.Traditional data analysis methods are no longer sufficient to meet the comprehensive requirements of data security,intelligent processing,and decision support.Through techniques such as machine learning,deep learning,natural language processing,and multimodal fusion,AI provides robust technical support for medical data cleaning,governance,mining,and application.At the data level,intelligent algorithms enable the standardization,structuring,and interoperability of medical data,promoting information sharing across medical systems.At the model level,AI supports auxiliary diagnosis and precision treatment through image recognition,medical record analysis,and knowledge graph construction.At the system level,intelligent decision-support platforms continuously enhance the efficiency and accuracy of healthcare services.However,the widespread adoption of AI in medicine still faces challenges such as privacy protection,data security,model interpretability,and the lack of unified industry standards.Based on a systematic review of AI’s key supporting technologies in medical data processing and application,this paper focuses on the compliance challenges and adaptation strategies during industry integration and proposes an adaptation framework centered on“technological trustworthiness,data security,and industry collaboration.”The study provides theoretical and practical insights for promoting the standardized and sustainable development of AI in the healthcare industry.
基金Research on the Factors Influencing“Slow Employment”of College Students from the Perspective of CIP Theory in the 2023 Academic Research Project(Provincial and Ministerial Project Cultivation Project)of Zhejiang Agricultural Business College(KY202336)2024 Annual Special Task Project of Humanities and Social Science Research of the Ministry of Education“Research on the Psychological Mechanism and Effective Coping Strategies of“Social Anxiety”among College Students”(Research on College Counselors)(24JDSZ3017)“Major Humanities and Social Sciences Research Projects in Zhejiang”Higher Education Institutions(2024GH082).
文摘This study explored the relationship between perceived social support and employment anxiety among Chinese college students,as well as the mediating and moderating effects of psychological resilience and career adaptability on this relationship.A total of 1928 college students(females=1371,mean age=20.42,SD=1.05)completed the Perceived Social Support Scale,Employment Anxiety Questionnaire,Connor-Davidson Resilience Scale and Career Adapt-Abilities Scale.Mediation analysis results showed that psychological resilience mediated the relationship between perceived social support and employment anxiety for lower employment anxiety.Career adaptability moderated the mediating effect of psychological resilience for lower employment anxiety than with either of the variables alone.Thefindings are consistent with cognitive diathesis-stress theory and career construction theory which propose that individuals’cognitive structures and psychological predispositions interact with environmental stressors to shape their career development and psychological well-being.Essentially,students who have a robust social support system,high career adaptability,and are psychologically resilient are less likely to experience employment anxiety.
基金funded by the National Key Research and Development Program of China,grant number:2023YFF0615404.
文摘To overcome the challenges associated with predicting gas extraction performance and mitigating the gradual decline in extraction volume,which adversely impacts gas utilization efficiency in mines,a gas extraction pure volume prediction model was developed using Support Vector Regression(SVR)and Random Forest(RF),with hyperparameters fine-tuned via the Genetic Algorithm(GA).Building upon this,an adaptive control model for gas extraction negative pressure was formulated to maximize the extracted gas volume within the pipeline network,followed by field validation experiments.Experimental results indicate that the GA-SVR model surpasses comparable models in terms of mean absolute error,root mean square error,and mean absolute percentage error.In the extraction process of bedding boreholes,the influence of negative pressure on gas extraction concentration diminishes over time,yet it remains a critical factor in determining the extracted pure volume.In contrast,throughout the entire extraction period of cross-layer boreholes,both extracted pure volume and concentration exhibit pronounced sensitivity to fluctuations in extraction negative pressure.Field experiments demonstrated that the adaptive controlmodel enhanced the average extracted gas volume by 5.08% in the experimental borehole group compared to the control group during the later extraction stage,with a more pronounced increase of 7.15% in the first 15 days.The research findings offer essential technical support for the efficient utilization and long-term sustainable development of mine gas resources.The research findings offer essential technical support for gas disaster mitigation and the sustained,efficient utilization of mine gas.
基金Project supported by the National Natural Science Foundation of China(Nos.W2433004 and 12472015)the Research Fund of the State Key Laboratory of Mechanics and Control of Mechanical Structures(Nanjing University of Aeronautics and Astronautics)(No.MCMS-I-0122K01).
文摘This paper proposes an attitude control strategy for a flexible satellite equipped with an orthogonal cluster of three-dimensional(3D)magnetically suspended wheels(MSWs).The mathematical model for the satellite incorporating flexible appendages and an orthogonal cluster of magnetically suspended reaction wheel actuators is initially developed.After that,an adaptive attitude controller is designed with a switching surface of variable structure,an adaptive law for estimating inertia matrix uncertainty,and a fuzzy disturbance observer for estimating disturbance torques.Additionally,a Moore-Penrose-based steering law is proposed to derive the tilt angle commands of the orthogonal configuration of the 3D MSW to follow the designed control signal.Finally,numerical simulations are presented to validate the effectiveness of the proposed control strategy.
基金Supported by the National Natural Science Foundation of China(60772056)the Postdoctoral Science Foundation of China(20070421094)
文摘An adaptive blind support vector machine equalizer（ABSVME） is presented in this paper.The method is based upon least square support vector machine（LSSVM）,and stems from signal feature reconstruction idea.By oversampling the output of a LSSVM equalizer and exploiting a reasonable decorrelation cost function design,the method achieves fine online channel tracing with Kumar express algorithm and static iterative learning algorithm incorporated.The method is verified through simulation and compared with other nonlinear equalizers.The results show that it provides excellent performance in nonlinear equalization and time-varying channel tracing.Although a constant module equalization algorithm requires that the signal has characteristic of constant module,this method has no such requirement.
基金Supported by the National Basic Research Program of China(2012CB720500)Postdoctoral Science Foundation of China(2013M541964)Fundamental Research Funds for the Central Universities(13CX05021A)
文摘The performance of data-driven models relies heavily on the amount and quality of training samples, so it might deteriorate significantly in the regions where samples are scarce. The objective of this paper is to develop an online SVR model updating strategy to track the change in the process characteristics efficiently with affordable computational burden. This is achieved by adding a new sample that violates the Karush–Kuhn–Tucker conditions of the existing SVR model and by deleting the old sample that has the maximum distance with respect to the newly added sample in feature space. The benefits offered by such an updating strategy are exploited to develop an adaptive model-based control scheme, where model updating and control task perform alternately.The effectiveness of the adaptive controller is demonstrated by simulation study on a continuous stirred tank reactor. The results reveal that the adaptive MPC scheme outperforms its non-adaptive counterpart for largemagnitude set point changes and variations in process parameters.
文摘There are differences between the different individuals of learning. Adaptive learning support system is a learning system, which provides the learning supports suitable for the characteristics of the individuals according to the differences in the learning of individuals. In this paper, through the analysis on the adaptive learning support system, a system framework based on SOA is proposed and the research methods of the metadata model are emphatically discussed.
基金co-supported by the National Major Project for the Development and Application of Scientific Instrument Equipment of China (No. 2012YQ040235)
文摘The start-up current control of the high-speed brushless DC（HS-BLDC） motor is a challenging research topic. To effectively control the start-up current of the sensorless HS-BLDC motor, an adaptive control method is proposed based on the adaptive neural network（ANN）inverse system and the two degrees of freedom（2-DOF） internal model controller（IMC）. The HS-BLDC motor is identified by the online least squares support vector machine（OLS-SVM） algorithm to regulate the ANN inverse controller parameters in real time. A pseudo linear system is developed by introducing the constructed real-time inverse system into the original HS-BLDC motor system. Based on the characteristics of the pseudo linear system, an extra closed-loop feedback control strategy based on the 2-DOF IMC is proposed to improve the transient response performance and enhance the stability of the control system. The simulation and experimental results show that the proposed control method is effective and perfect start-up current tracking performance is achieved.
基金co-supported by Aeronautical Science Foundation of China (No. 2010ZB52011)Funding of Jiangsu Innovation Program for Graduate Education (No.CXLX11_0213)
文摘In order to establish an adaptive turbo-shaft engine model with high accuracy, a new modeling method based on parameter selection （PS） algorithm and multi-input multi-output recursive reduced least square support vector regression （MRR-LSSVR） machine is proposed. Firstly, the PS algorithm is designed to choose the most reasonable inputs of the adaptive module. During this process, a wrapper criterion based on least square support vector regression （LSSVR） machine is adopted, which can not only reduce computational complexity but also enhance generalization performance. Secondly, with the input variables determined by the PS algorithm, a mapping model of engine parameter estimation is trained off-line using MRR-LSSVR, which has a satisfying accuracy within 5＆. Finally, based on a numerical simulation platform of an integrated helicopter/ turbo-shaft engine system, an adaptive turbo-shaft engine model is developed and tested in a certain flight envelope. Under the condition of single or multiple engine components being degraded, many simulation experiments are carried out, and the simulation results show the effectiveness and validity of the proposed adaptive modeling method.
基金supported in part by the National Natural Science Foundation of China(61772141,61673123)Guangdong Provincial Science&Technology Project(2015B090901016,2016B010108007)+1 种基金Guangdong Education Department Project(Guangdong Higher Education letter 2015[133])the Guangzhou Science&Technology Project(201508010067,201604020145201604046017,and 2016201604030034)
文摘As a primary defense technique, intrusion detection becomes more and more significant since the security of the networks is one of the most critical issues in the world. We present an adaptive collaboration intrusion detection method to improve the safety of a network. A self-adaptive and collaborative intrusion detection model is built by applying the Environmentsclasses, agents, roles, groups, and objects(E-CARGO) model. The objects, roles, agents, and groups are designed by using decision trees(DTs) and support vector machines(SVMs), and adaptive scheduling mechanisms are set up. The KDD CUP 1999 data set is used to verify the effectiveness of the method. The experimental results demonstrate the feasibility and efficiency of the proposed collaborative and adaptive intrusion detection method. Also, the proposed method is shown to be more predominant than the methods that use a set of single type support vector machine(SVM) in terms of detection precision rate and recall rate.
