The areas affected by the L1 transfer to L2,such as phonotactics and stress,appear to have different degrees of erasability through training and practice.This paper attempts a theoretical analysis to account for empir...The areas affected by the L1 transfer to L2,such as phonotactics and stress,appear to have different degrees of erasability through training and practice.This paper attempts a theoretical analysis to account for empirical observations of L1 transfer in diphthong-coda coalescence and in sentence stress for Chinese learners of English in an American accent training course.Using the framework and tableau method of Optimality Theory(Prince and Smolensky 1993),the phonological paradigm that views languages’differences as symptomatic of differences in rankings of a set of universal violable constraints,this paper posits the underlying ranking at work in(a)the segmental case where[aŋ]is the observed output for/aʊn/;(b)the suprasegmental case where no stress contrast is observed for a pair of phonologically similar sentences with contrastive stress.It is argued that,in the segmental case,the coalescence of the second vowel of a diphthong with an alveolar nasal coda results from the high ranking of markedness constraints,including Complex Syllable;and in the suprasegmental case,sentence stress is greatly affected by changes in the ranking of the constraint culminativity.Aside from shedding light on the understudied issue of diphthong-coda coalescence,this research also contributes to the discussion of the comparative erasability of L1 transfer for the two areas and demonstrates how a deduction-based theoretical method may actually have practical implications for guiding the design of L2 teaching methodology of English pronunciation as well as for promoting native English speakers’clearer understanding of Chinese learners of English on the global stage.展开更多
The small and scattered enterprise pattern in the county economy has formed numerous sporadic pollution sources, hindering the centralized treatment of the water environment, increasing the cost and difficulty of trea...The small and scattered enterprise pattern in the county economy has formed numerous sporadic pollution sources, hindering the centralized treatment of the water environment, increasing the cost and difficulty of treatment. How enterprises can make reasonable decisions on their water environment behavior based on the external environment and their own factors is of great significance for scientifically and effectively designing water environment regulation mechanisms. Based on optimal control theory, this study investigates the design of contractual mechanisms for water environmental regulation for small and medium-sized enterprises. The enterprise is regarded as an independent economic entity that can adopt optimal control strategies to maximize its own interests. Based on the participation of multiple subjects including the government, enterprises, and the public, an optimal control strategy model for enterprises under contractual water environmental regulation is constructed using optimal control theory, and a method for calculating the amount of unit pollutant penalties is derived. The water pollutant treatment cost data of a paper company is selected to conduct empirical numerical analysis on the model. The results show that the increase in the probability of government regulation and public participation, as well as the decrease in local government protection for enterprises, can achieve the same regulatory effect while reducing the number of administrative penalties per unit. Finally, the implementation process of contractual water environmental regulation for small and medium-sized enterprises is designed.展开更多
In practical combat scenarios,Hypersonic Glide Vehicles(HGV)face the challenge of evading Successive Pursuers from the Same Direction while satisfying the Homing Constraint(SPSDHC).To address this problem,this paper p...In practical combat scenarios,Hypersonic Glide Vehicles(HGV)face the challenge of evading Successive Pursuers from the Same Direction while satisfying the Homing Constraint(SPSDHC).To address this problem,this paper proposes a parameterized evasion guidance algorithm based on reinforcement learning.The three-player optimal evasion strategy is firstly analyzed and approximated by parametrization.The switching acceleration command of HGV optimal evasion strategy considering the upper limit of missile acceleration command is analyzed based on the optimal control theory.The terminal miss of HGV in the case of evading two missiles is analyzed,which means that the three-player optimal evasion strategy is a linear combination of two one-toone strategies.Then,a velocity control algorithm is proposed to increase the terminal miss by actively controlling the flight speed of the HGV based on the parametrized evasion strategy.The reinforcement learning method is used to implement the strategy in real time and a reward function is designed by deducing homing strategy for the HGV to approach the target,which ensures that the HGV satisfies the homing constraint.Experimental results demonstrate the feasibility and robustness of the proposed parameterized evasion strategy,which enables the HGV to generate maximum terminal miss and satisfy homing constraint when facing single or double missiles.展开更多
Spillover of trypanosomiasis parasites from wildlife to domestic livestock and humans remains a major challenge world over.With the disease targeted for elimination by 2030,assessing the impact of control strategies i...Spillover of trypanosomiasis parasites from wildlife to domestic livestock and humans remains a major challenge world over.With the disease targeted for elimination by 2030,assessing the impact of control strategies in communities where there are human-cattle-wildlife interactions is therefore essential.A compartmental framework incorporating tsetse flies,humans,cattle,wildlife and various disease control strategies is developed and analyzed.The reproduction is derived and its sensitivity to different model parameters is investigated.Meanwhile,the optimal control theory is used to identify a combination of control strategies capable of minimizing the infected human and cattle population over time at minimal costs of implementation.The results indicates that tsetse fly mortality rate is strongly and negatively correlated to the reproduction number.It is also established that tsetse fly feeding rate in strongly and positively correlated to the reproduction number.Simulation results indicates that time dependent control strategies can significantly reduce the infections.Overall,the study shows that screening and treatment of humans may not lead to disease elimination.Combining this strategy with other strategies such as screening and treatment of cattle and vector control strategies will result in maximum reduction of tsetse fly population and disease elimination.展开更多
This paper aims to offer an optimality-theoretic account of citation tones and tone sandhi in disyllabic sequences in Chengdu Dialect （CD henceforth）. It shows that the constraint ranking ＊[H,hl].T〉〉IDENT-LT〉〉 ...This paper aims to offer an optimality-theoretic account of citation tones and tone sandhi in disyllabic sequences in Chengdu Dialect （CD henceforth）. It shows that the constraint ranking ＊[H,hl].T〉〉IDENT-LT〉〉 ＊[H,lh],＊[L,1h]〉〉 IDENT-RT〉〉 ＊[H,hl] is able to account for the tone sandhi phenomena of disyllabic sequences in CD.展开更多
Urban agglomerations are spatial entities that promote the development of ‘new urbanization' processes within China. In this context, the concept of ‘multiscale urban agglomeration spaces' encompasses three ...Urban agglomerations are spatial entities that promote the development of ‘new urbanization' processes within China. In this context, the concept of ‘multiscale urban agglomeration spaces' encompasses three linked levels: macroscale urban agglomerations, mesoscale cities, and microscale urban centers. Applying a series of multidisciplinary integrated research methods drawn from geography, urban planning, and architecture, this paper reveals two intensive utilization laws that can be generalized to apply to multiscale urban agglomeration spaces, top-to-bottom ‘positive transmission' linkage and inside-to-outside ‘negative transmission' movement. This paper also proposes optimization transmission theory and policy decision technical pathways that can be applied to these three urban agglomeration spatial scales. Specific technical pathways of transmission include intensive expansion and simulated decision-making in macroscale urban agglomerations, ecology, production, and living space intensive layout and dynamic decision-making in mesoscale cities, and four cores(i.e., ‘single, ring, axis, and pole core') progressive linkage and intensive optimization decision-making in microscale urban centers. The theory and technical pathways proposed in this paper solve the technical problem of optimization and provide intensive methods that can be applied not only at the individual level but also at multiple scales in urban agglomeration spaces. This study also advances a series of comprehensive technical solutions that can be applied to both compact and smart growth cities as well as to urban agglomerations. Solid theoretical support is provided for the optimization of Chinese land development, urbanization, agricultural development, and ecological security.展开更多
This paper built a combined heat and power（CHP） dispatch model for wind-CHP system with solid heat storage device（SHS） aiming at minimizing system coal consumption, and set system demand-supply balance and units＇...This paper built a combined heat and power（CHP） dispatch model for wind-CHP system with solid heat storage device（SHS） aiming at minimizing system coal consumption, and set system demand-supply balance and units＇ operation conditions as the operation constraints. Furthermore, robust stochastic optimization theory was used to describe wind power output uncertainty. The simulation result showed that SHS increased CHP peak-valley shifting capability and reduced abandoned wind rate from 12% to 6%, and reduced 5% coal consumption, compared with the original system operation by flexible charging electric power and heating. The payback period of employing SHS in wind-CHP system is far shorter than SHS expected service life.展开更多
In view of some distinctive characteristics of the early-stage flame image, a corresponding method of characteristic extraction is presented. Also introduced is the application of the improved BP algorithm based on th...In view of some distinctive characteristics of the early-stage flame image, a corresponding method of characteristic extraction is presented. Also introduced is the application of the improved BP algorithm based on the optimization theory to identifying fire image characteristics. First the optimization of BP neural network adopting Levenberg-Marquardt algorithm with the property of quadratic convergence is discussed, and then a new system of fire image identification is devised. Plenty of experiments and field tests have proved that this system can detect the early-stage fire flame quickly and reliably.展开更多
Network virtualization(NV) is widely considered as a key component of the future network and promises to allow multiple virtual networks(VNs) with different protocols to coexist on a shared substrate network(SN). One ...Network virtualization(NV) is widely considered as a key component of the future network and promises to allow multiple virtual networks(VNs) with different protocols to coexist on a shared substrate network(SN). One main challenge in NV is virtual network embedding(VNE). VNE is a NPhard problem. Previous VNE algorithms in the literature are mostly heuristic, while the remaining algorithms are exact. Heuristic algorithms aim to find a feasible embedding of each VN, not optimal or sub-optimal, in polynomial time. Though presenting the optimal or sub-optimal embedding per VN, exact algorithms are too time-consuming in smallscaled networks, not to mention moderately sized networks. To make a trade-off between the heuristic and the exact, this paper presents an effective algorithm, labeled as VNE-RSOT(Restrictive Selection and Optimization Theory), to solve the VNE problem. The VNERSOT can embed virtual nodes and links per VN simultaneously. The restrictive selection contributes to selecting candidate substrate nodes and paths and largely cuts down on the number of integer variables, used in the following optimization theory approach. The VNE-RSOT fights to minimize substrate resource consumption and accommodates more VNs. To highlight the efficiency of VNERSOT, a simulation against typical and stateof-art heuristic algorithms and a pure exact algorithm is made. Numerical results reveal that virtual network request(VNR) acceptance ratio of VNE-RSOT is, at least, 10% higher than the best-behaved heuristic. Other metrics, such as the execution time, are also plotted to emphasize and highlight the efficiency of VNE-RSOT.展开更多
In determining the replenishment policy for an inventory system, some researchers advocated that the iterative method of Newton could be applied to the derivative of the total cost function in order to get the optimal...In determining the replenishment policy for an inventory system, some researchers advocated that the iterative method of Newton could be applied to the derivative of the total cost function in order to get the optimal solution. But this approach requires calculation of the second derivative of the function. Avoiding this complex computation we use another iterative method presented by the second author. One of the goals of this paper is to present a unified convergence theory of this method. Then we give a numerical example to show the application of our theory.展开更多
The q-profile control problem in the ramp-up phase of plasma discharges is consid- ered in this work. The magnetic diffusion partial differential equation （PDE） models the dynamics of the poloidal magnetic flux prof...The q-profile control problem in the ramp-up phase of plasma discharges is consid- ered in this work. The magnetic diffusion partial differential equation （PDE） models the dynamics of the poloidal magnetic flux profile, which is used in this work to formulate a PDE-constrained op-timization problem under a quasi-static assumption. The minimum surface theory and constrained numeric optimization are then applied to achieve suboptimal solutions. Since the transient dy- namics is pre-given by the minimum surface theory, then this method can dramatically accelerate the solution process. In order to be robust under external uncertainties in real implementations, PID （proportional-integral-derivative） controllers are used to force the actuators to follow the computational input trajectories. It has the potential to implement in real-time for long time discharges by combining this method with the magnetic equilibrium update.展开更多
In this paper, two important problems in the gait planning of dynamic walking of biped robot, i.e., finding inverse kinematic solution and constructing joint trajectories, are studied in detail by adopting complex opt...In this paper, two important problems in the gait planning of dynamic walking of biped robot, i.e., finding inverse kinematic solution and constructing joint trajectories, are studied in detail by adopting complex optimization theory. The optimization algorithm for finding the inverse kinematic solution is developed, the construction method of joint trajectories is given, and the gait planning method of dynamic walking of biped robots is proposed.展开更多
Using the dynamic optimization theory, we described a decision-making model for farmer choosing land use when there are several different kinds of uses for land. To obtain an empirical model that could be easily appli...Using the dynamic optimization theory, we described a decision-making model for farmer choosing land use when there are several different kinds of uses for land. To obtain an empirical model that could be easily applied, decision rules for farmer with a single static expectation were given.展开更多
Respiratory variables, including tidal volume and respiratory rate, display significant variability. The probability density function (PDF) of respiratory variables has been shown to contain clinical information and c...Respiratory variables, including tidal volume and respiratory rate, display significant variability. The probability density function (PDF) of respiratory variables has been shown to contain clinical information and can predict the risk for exacerbation in asthma. However, it is uncertain why this PDF plays a major role in predicting the dynamic conditions of the respiratory system. This paper introduces a stochastic optimal control model for noisy spontaneous breathing, and obtains a Shrödinger’s wave equation as the motion equation that can produce a PDF as a solution. Based on the lobules-bronchial tree model of the lung system, the tidal volume variable was expressed by a polar coordinate, by use of which the Shrödinger’s wave equation of inter-breath intervals (IBIs) was obtained. Through the wave equation of IBIs, the respiratory rhythm generator was characterized by the potential function including the PDF and the parameter concerning the topographical distribution of regional pulmonary ventilations. The stochastic model in this study was assumed to have a common variance parameter in the state variables, which would originate from the variability in metabolic energy at the cell level. As a conclusion, the PDF of IBIs would become a marker of neuroplasticity in the respiratory rhythm generator through Shr?dinger’s wave equation for IBIs.展开更多
The evaluation of urban flood-waterlogged vulnerability is very important to the safety of urban flood control. In this paper, the evaluation of consolidated index is used. Respectively, AHP and entropy method calcula...The evaluation of urban flood-waterlogged vulnerability is very important to the safety of urban flood control. In this paper, the evaluation of consolidated index is used. Respectively, AHP and entropy method calculate the subjective and objective weight of the evaluation indicators, and combine them by game theory. So we can obtain synthetic weight based on objective and subjective weights. The evaluation of urban flood-waterlogged vulnerability as target layer, a single variable multi-objective fuzzy optimization model is established. We use the model to evaluate flood-waterlogged vulnerability of 13 prefecture-level city in Hunan, and compare it with other evaluation method. The results show that the evaluation method has certain adaptability and reliability, and it＇ s helpfid to the construction planning of urban flood control.展开更多
We present an optimal and robust quantum control method for efficient population transfer in asymmetric double quantum-dot molecules.We derive a long-duration control scheme that allows for highly efficient population...We present an optimal and robust quantum control method for efficient population transfer in asymmetric double quantum-dot molecules.We derive a long-duration control scheme that allows for highly efficient population transfer by accurately controlling the amplitude of a narrow-bandwidth pulse.To overcome fluctuations in control field parameters,we employ a frequency-domain quantum optimal control theory method to optimize the spectral phase of a single pulse with broad bandwidth while preserving the spectral amplitude.It is shown that this spectral-phase-only optimization approach can successfully identify robust and optimal control fields,leading to efficient population transfer to the target state while concurrently suppressing population transfer to undesired states.The method demonstrates resilience to fluctuations in control field parameters,making it a promising approach for reliable and efficient population transfer in practical applications.展开更多
The millimeter-Wave(mmWave)communication with the advantages of abundant bandwidth and immunity to interference has been deemed a promising technology to greatly improve network capacity.However,due to such characteri...The millimeter-Wave(mmWave)communication with the advantages of abundant bandwidth and immunity to interference has been deemed a promising technology to greatly improve network capacity.However,due to such characteristics of mmWave,as short transmission distance,high sensitivity to the blockage,and large propagation path loss,handover issues(including trigger condition and target beam selection)become much complicated.In this paper,we design a novel handover scheme to optimize the overall system throughput as well as the total system delay while guaranteeing the Quality of Service(QoS)of each User Equipment(UE).Specifically,the proposed handover scheme called O-MAPPO integrates the Reinforcement Learning(RL)algorithm and optimization theory.The RL algorithm known as Multi-Agent Proximal Policy Optimization(MAPPO)plays a role in determining handover trigger conditions.Further,we propose an optimization problem in conjunction with MAPPO to select the target base station.The aim is to evaluate and optimize the system performance of total throughput and delay while guaranteeing the QoS of each UE after the handover decision is made.The numerical results show the overall system throughput and delay with our method are slightly worse than that with the exhaustive search method but much better than that using another typical RL algorithm Deep Deterministic Policy Gradient(DDPG).展开更多
Multi-objective optimization for the optimum shape design is introduced in aerodynamics using the Game theory. Based on the control theory, the employed optimizer and the negative feedback are used to implement the co...Multi-objective optimization for the optimum shape design is introduced in aerodynamics using the Game theory. Based on the control theory, the employed optimizer and the negative feedback are used to implement the constraints. All the constraints are satisfied implicitly and automatically in the design. Furthermore,the above methodology is combined with a formulation derived from the Game theory to treat multi-point airfoil optimization. Airfoil shapes are optimized according to various aerodynamics criteria. In the symmetric Nash game, each “player” is responsible for one criterion, and the Nash equilibrium provides a solution to the multipoint optimization. Design results confirm the efficiency of the method.展开更多
文摘The areas affected by the L1 transfer to L2,such as phonotactics and stress,appear to have different degrees of erasability through training and practice.This paper attempts a theoretical analysis to account for empirical observations of L1 transfer in diphthong-coda coalescence and in sentence stress for Chinese learners of English in an American accent training course.Using the framework and tableau method of Optimality Theory(Prince and Smolensky 1993),the phonological paradigm that views languages’differences as symptomatic of differences in rankings of a set of universal violable constraints,this paper posits the underlying ranking at work in(a)the segmental case where[aŋ]is the observed output for/aʊn/;(b)the suprasegmental case where no stress contrast is observed for a pair of phonologically similar sentences with contrastive stress.It is argued that,in the segmental case,the coalescence of the second vowel of a diphthong with an alveolar nasal coda results from the high ranking of markedness constraints,including Complex Syllable;and in the suprasegmental case,sentence stress is greatly affected by changes in the ranking of the constraint culminativity.Aside from shedding light on the understudied issue of diphthong-coda coalescence,this research also contributes to the discussion of the comparative erasability of L1 transfer for the two areas and demonstrates how a deduction-based theoretical method may actually have practical implications for guiding the design of L2 teaching methodology of English pronunciation as well as for promoting native English speakers’clearer understanding of Chinese learners of English on the global stage.
文摘The small and scattered enterprise pattern in the county economy has formed numerous sporadic pollution sources, hindering the centralized treatment of the water environment, increasing the cost and difficulty of treatment. How enterprises can make reasonable decisions on their water environment behavior based on the external environment and their own factors is of great significance for scientifically and effectively designing water environment regulation mechanisms. Based on optimal control theory, this study investigates the design of contractual mechanisms for water environmental regulation for small and medium-sized enterprises. The enterprise is regarded as an independent economic entity that can adopt optimal control strategies to maximize its own interests. Based on the participation of multiple subjects including the government, enterprises, and the public, an optimal control strategy model for enterprises under contractual water environmental regulation is constructed using optimal control theory, and a method for calculating the amount of unit pollutant penalties is derived. The water pollutant treatment cost data of a paper company is selected to conduct empirical numerical analysis on the model. The results show that the increase in the probability of government regulation and public participation, as well as the decrease in local government protection for enterprises, can achieve the same regulatory effect while reducing the number of administrative penalties per unit. Finally, the implementation process of contractual water environmental regulation for small and medium-sized enterprises is designed.
基金supported by the National Natural Science Foundation of China(No.62103014)。
文摘In practical combat scenarios,Hypersonic Glide Vehicles(HGV)face the challenge of evading Successive Pursuers from the Same Direction while satisfying the Homing Constraint(SPSDHC).To address this problem,this paper proposes a parameterized evasion guidance algorithm based on reinforcement learning.The three-player optimal evasion strategy is firstly analyzed and approximated by parametrization.The switching acceleration command of HGV optimal evasion strategy considering the upper limit of missile acceleration command is analyzed based on the optimal control theory.The terminal miss of HGV in the case of evading two missiles is analyzed,which means that the three-player optimal evasion strategy is a linear combination of two one-toone strategies.Then,a velocity control algorithm is proposed to increase the terminal miss by actively controlling the flight speed of the HGV based on the parametrized evasion strategy.The reinforcement learning method is used to implement the strategy in real time and a reward function is designed by deducing homing strategy for the HGV to approach the target,which ensures that the HGV satisfies the homing constraint.Experimental results demonstrate the feasibility and robustness of the proposed parameterized evasion strategy,which enables the HGV to generate maximum terminal miss and satisfy homing constraint when facing single or double missiles.
文摘Spillover of trypanosomiasis parasites from wildlife to domestic livestock and humans remains a major challenge world over.With the disease targeted for elimination by 2030,assessing the impact of control strategies in communities where there are human-cattle-wildlife interactions is therefore essential.A compartmental framework incorporating tsetse flies,humans,cattle,wildlife and various disease control strategies is developed and analyzed.The reproduction is derived and its sensitivity to different model parameters is investigated.Meanwhile,the optimal control theory is used to identify a combination of control strategies capable of minimizing the infected human and cattle population over time at minimal costs of implementation.The results indicates that tsetse fly mortality rate is strongly and negatively correlated to the reproduction number.It is also established that tsetse fly feeding rate in strongly and positively correlated to the reproduction number.Simulation results indicates that time dependent control strategies can significantly reduce the infections.Overall,the study shows that screening and treatment of humans may not lead to disease elimination.Combining this strategy with other strategies such as screening and treatment of cattle and vector control strategies will result in maximum reduction of tsetse fly population and disease elimination.
文摘This paper aims to offer an optimality-theoretic account of citation tones and tone sandhi in disyllabic sequences in Chengdu Dialect （CD henceforth）. It shows that the constraint ranking ＊[H,hl].T〉〉IDENT-LT〉〉 ＊[H,lh],＊[L,1h]〉〉 IDENT-RT〉〉 ＊[H,hl] is able to account for the tone sandhi phenomena of disyllabic sequences in CD.
基金Under the auspices of Major Program of the National Natural Science Foundation of China ‘Coupled mechanisms and interactive coercing effects between urbanization and eco-environment in mega-urban agglomerations’(No.41590842)
文摘Urban agglomerations are spatial entities that promote the development of ‘new urbanization' processes within China. In this context, the concept of ‘multiscale urban agglomeration spaces' encompasses three linked levels: macroscale urban agglomerations, mesoscale cities, and microscale urban centers. Applying a series of multidisciplinary integrated research methods drawn from geography, urban planning, and architecture, this paper reveals two intensive utilization laws that can be generalized to apply to multiscale urban agglomeration spaces, top-to-bottom ‘positive transmission' linkage and inside-to-outside ‘negative transmission' movement. This paper also proposes optimization transmission theory and policy decision technical pathways that can be applied to these three urban agglomeration spatial scales. Specific technical pathways of transmission include intensive expansion and simulated decision-making in macroscale urban agglomerations, ecology, production, and living space intensive layout and dynamic decision-making in mesoscale cities, and four cores(i.e., ‘single, ring, axis, and pole core') progressive linkage and intensive optimization decision-making in microscale urban centers. The theory and technical pathways proposed in this paper solve the technical problem of optimization and provide intensive methods that can be applied not only at the individual level but also at multiple scales in urban agglomeration spaces. This study also advances a series of comprehensive technical solutions that can be applied to both compact and smart growth cities as well as to urban agglomerations. Solid theoretical support is provided for the optimization of Chinese land development, urbanization, agricultural development, and ecological security.
基金Supported by the Fundamental Research Funds for the National Science Foundation of China(71573084)
文摘This paper built a combined heat and power（CHP） dispatch model for wind-CHP system with solid heat storage device（SHS） aiming at minimizing system coal consumption, and set system demand-supply balance and units＇ operation conditions as the operation constraints. Furthermore, robust stochastic optimization theory was used to describe wind power output uncertainty. The simulation result showed that SHS increased CHP peak-valley shifting capability and reduced abandoned wind rate from 12% to 6%, and reduced 5% coal consumption, compared with the original system operation by flexible charging electric power and heating. The payback period of employing SHS in wind-CHP system is far shorter than SHS expected service life.
文摘In view of some distinctive characteristics of the early-stage flame image, a corresponding method of characteristic extraction is presented. Also introduced is the application of the improved BP algorithm based on the optimization theory to identifying fire image characteristics. First the optimization of BP neural network adopting Levenberg-Marquardt algorithm with the property of quadratic convergence is discussed, and then a new system of fire image identification is devised. Plenty of experiments and field tests have proved that this system can detect the early-stage fire flame quickly and reliably.
基金supported by the National Basic Research Program of China (973 Program) under Grant 2013CB329104the National Natural Science Foundation of China under Grant 61372124 and 61427801the Key Projects of Natural Science Foundation of Jiangsu University under Grant 11KJA510001
文摘Network virtualization(NV) is widely considered as a key component of the future network and promises to allow multiple virtual networks(VNs) with different protocols to coexist on a shared substrate network(SN). One main challenge in NV is virtual network embedding(VNE). VNE is a NPhard problem. Previous VNE algorithms in the literature are mostly heuristic, while the remaining algorithms are exact. Heuristic algorithms aim to find a feasible embedding of each VN, not optimal or sub-optimal, in polynomial time. Though presenting the optimal or sub-optimal embedding per VN, exact algorithms are too time-consuming in smallscaled networks, not to mention moderately sized networks. To make a trade-off between the heuristic and the exact, this paper presents an effective algorithm, labeled as VNE-RSOT(Restrictive Selection and Optimization Theory), to solve the VNE problem. The VNERSOT can embed virtual nodes and links per VN simultaneously. The restrictive selection contributes to selecting candidate substrate nodes and paths and largely cuts down on the number of integer variables, used in the following optimization theory approach. The VNE-RSOT fights to minimize substrate resource consumption and accommodates more VNs. To highlight the efficiency of VNERSOT, a simulation against typical and stateof-art heuristic algorithms and a pure exact algorithm is made. Numerical results reveal that virtual network request(VNR) acceptance ratio of VNE-RSOT is, at least, 10% higher than the best-behaved heuristic. Other metrics, such as the execution time, are also plotted to emphasize and highlight the efficiency of VNE-RSOT.
文摘In determining the replenishment policy for an inventory system, some researchers advocated that the iterative method of Newton could be applied to the derivative of the total cost function in order to get the optimal solution. But this approach requires calculation of the second derivative of the function. Avoiding this complex computation we use another iterative method presented by the second author. One of the goals of this paper is to present a unified convergence theory of this method. Then we give a numerical example to show the application of our theory.
基金supported partially by the US NSF CAREER award program (ECCS-0645086)National Natural Science Foundation of China (No.F030119)+2 种基金Zhejiang Provincial Natural Science Foundation of China (Nos.Y1110354, Y6110751)the Fundamental Research Funds for the Central Universities of China (No.1A5000-172210101)the Natural Science Foundation of Ningbo (No.2010A610096)
文摘The q-profile control problem in the ramp-up phase of plasma discharges is consid- ered in this work. The magnetic diffusion partial differential equation （PDE） models the dynamics of the poloidal magnetic flux profile, which is used in this work to formulate a PDE-constrained op-timization problem under a quasi-static assumption. The minimum surface theory and constrained numeric optimization are then applied to achieve suboptimal solutions. Since the transient dy- namics is pre-given by the minimum surface theory, then this method can dramatically accelerate the solution process. In order to be robust under external uncertainties in real implementations, PID （proportional-integral-derivative） controllers are used to force the actuators to follow the computational input trajectories. It has the potential to implement in real-time for long time discharges by combining this method with the magnetic equilibrium update.
文摘In this paper, two important problems in the gait planning of dynamic walking of biped robot, i.e., finding inverse kinematic solution and constructing joint trajectories, are studied in detail by adopting complex optimization theory. The optimization algorithm for finding the inverse kinematic solution is developed, the construction method of joint trajectories is given, and the gait planning method of dynamic walking of biped robots is proposed.
文摘Using the dynamic optimization theory, we described a decision-making model for farmer choosing land use when there are several different kinds of uses for land. To obtain an empirical model that could be easily applied, decision rules for farmer with a single static expectation were given.
文摘Respiratory variables, including tidal volume and respiratory rate, display significant variability. The probability density function (PDF) of respiratory variables has been shown to contain clinical information and can predict the risk for exacerbation in asthma. However, it is uncertain why this PDF plays a major role in predicting the dynamic conditions of the respiratory system. This paper introduces a stochastic optimal control model for noisy spontaneous breathing, and obtains a Shrödinger’s wave equation as the motion equation that can produce a PDF as a solution. Based on the lobules-bronchial tree model of the lung system, the tidal volume variable was expressed by a polar coordinate, by use of which the Shrödinger’s wave equation of inter-breath intervals (IBIs) was obtained. Through the wave equation of IBIs, the respiratory rhythm generator was characterized by the potential function including the PDF and the parameter concerning the topographical distribution of regional pulmonary ventilations. The stochastic model in this study was assumed to have a common variance parameter in the state variables, which would originate from the variability in metabolic energy at the cell level. As a conclusion, the PDF of IBIs would become a marker of neuroplasticity in the respiratory rhythm generator through Shr?dinger’s wave equation for IBIs.
文摘The evaluation of urban flood-waterlogged vulnerability is very important to the safety of urban flood control. In this paper, the evaluation of consolidated index is used. Respectively, AHP and entropy method calculate the subjective and objective weight of the evaluation indicators, and combine them by game theory. So we can obtain synthetic weight based on objective and subjective weights. The evaluation of urban flood-waterlogged vulnerability as target layer, a single variable multi-objective fuzzy optimization model is established. We use the model to evaluate flood-waterlogged vulnerability of 13 prefecture-level city in Hunan, and compare it with other evaluation method. The results show that the evaluation method has certain adaptability and reliability, and it＇ s helpfid to the construction planning of urban flood control.
基金This work was supported by the National Natural Science Foundations of China(Grant Nos.12275033,61973317,and 12274470)the Natural Science Foundation of Hunan Province for Distinguished Young Scholars(Grant No.2022JJ10070)+1 种基金the Natural Science Foundation of Hunan Province(Grant No.2022JJ30582)the Scientific Research Fund of Hunan Provincial Education Department(Grant No.20A025).
文摘We present an optimal and robust quantum control method for efficient population transfer in asymmetric double quantum-dot molecules.We derive a long-duration control scheme that allows for highly efficient population transfer by accurately controlling the amplitude of a narrow-bandwidth pulse.To overcome fluctuations in control field parameters,we employ a frequency-domain quantum optimal control theory method to optimize the spectral phase of a single pulse with broad bandwidth while preserving the spectral amplitude.It is shown that this spectral-phase-only optimization approach can successfully identify robust and optimal control fields,leading to efficient population transfer to the target state while concurrently suppressing population transfer to undesired states.The method demonstrates resilience to fluctuations in control field parameters,making it a promising approach for reliable and efficient population transfer in practical applications.
文摘The millimeter-Wave(mmWave)communication with the advantages of abundant bandwidth and immunity to interference has been deemed a promising technology to greatly improve network capacity.However,due to such characteristics of mmWave,as short transmission distance,high sensitivity to the blockage,and large propagation path loss,handover issues(including trigger condition and target beam selection)become much complicated.In this paper,we design a novel handover scheme to optimize the overall system throughput as well as the total system delay while guaranteeing the Quality of Service(QoS)of each User Equipment(UE).Specifically,the proposed handover scheme called O-MAPPO integrates the Reinforcement Learning(RL)algorithm and optimization theory.The RL algorithm known as Multi-Agent Proximal Policy Optimization(MAPPO)plays a role in determining handover trigger conditions.Further,we propose an optimization problem in conjunction with MAPPO to select the target base station.The aim is to evaluate and optimize the system performance of total throughput and delay while guaranteeing the QoS of each UE after the handover decision is made.The numerical results show the overall system throughput and delay with our method are slightly worse than that with the exhaustive search method but much better than that using another typical RL algorithm Deep Deterministic Policy Gradient(DDPG).
文摘Multi-objective optimization for the optimum shape design is introduced in aerodynamics using the Game theory. Based on the control theory, the employed optimizer and the negative feedback are used to implement the constraints. All the constraints are satisfied implicitly and automatically in the design. Furthermore,the above methodology is combined with a formulation derived from the Game theory to treat multi-point airfoil optimization. Airfoil shapes are optimized according to various aerodynamics criteria. In the symmetric Nash game, each “player” is responsible for one criterion, and the Nash equilibrium provides a solution to the multipoint optimization. Design results confirm the efficiency of the method.
