As a novel signaling technology,the power splitting receiver(PSR)simultaneously employs both the coherent and non-coherent signal processing.In order to improve its communication performance,an intelligent reflecting ...As a novel signaling technology,the power splitting receiver(PSR)simultaneously employs both the coherent and non-coherent signal processing.In order to improve its communication performance,an intelligent reflecting surface(IRS)is introduced into its signal propagation path.Consequently,an IRSaided PSR is concerned for a point-to-point(P2P)data link,where both the single-antenna and multiantenna deployments on the receiver are discussed.We aim at maximizing the capacity of the concerned P2P data-link by jointly optimizing the passive beamforming of IRS and the splitting ratio of PSR,either in single-antenna or multi-antenna case.However,owing to the coupling of multiple variables,the optimization problems are non-convex and challenging,especially in the later multi-antenna case.The proposed alternating-approximating algorithm(A-A),aided by semi-definite relaxation(SDR)and successive convex approximation(SCA)methods,etc.,successfully overcomes these challenges.We compare the IRS-aided PSR system that optimized by our proposed algorithm to the systems without IRS or PSR,and the systems without joint optimization.The simulation results show that our proposal has a better performance.展开更多
The recent development in Lucknow shows that the amount of built mass may increase significantly soon,which may affect outdoor thermal comfort.This study aims to achieve a better alternative to the geometrical configu...The recent development in Lucknow shows that the amount of built mass may increase significantly soon,which may affect outdoor thermal comfort.This study aims to achieve a better alternative to the geometrical configuration of vertical surfaces that helps improve the outdoor thermal comfort level.The study primarily deals with the exploration of built forms by altering the planar forms,heights,and orientations to arrive at a better composition of vertical surfaces.144 typologies were finally generated,which were then simulated in ENVI-met.The results show that,with the I-shaped typology it is difficult to reduce solar access,whereas in terms of ventilation,the typology performed better than L-shaped and C-shaped typologies.For this reason,the hours of solar access,as well as wind speed,should be seen together while developing the built-form typology.Urban neighborhoods can be designed with streets and open spaces oriented primarily to northeast-southwest and northwest-southeast directions which allow the open spaces to be thermally more comfortable than the rest of the orientation.This research highlights the importance of varying building heights to enhance thermal comfort.The findings provide valuable insights for composite climate cities like lucknow and can serve as a framework for future design strategies aimed at mitigating outdoor thermal discomfort.It is therefore important for planners,urban designers,and architects to design considering the minimal impact of the upcoming development on the thermal comfort level.展开更多
This paper proposes the Unmanned Aerial Vehicle(UAV)-assisted Full-Duplex(FD)Integrated Sensing And Communication(ISAC)system.In this system,the UAV integrates sensing and communication functions,capable of receiving ...This paper proposes the Unmanned Aerial Vehicle(UAV)-assisted Full-Duplex(FD)Integrated Sensing And Communication(ISAC)system.In this system,the UAV integrates sensing and communication functions,capable of receiving transmission signals from Uplink(UL)users and echo signal from target,while communicating with Downlink(DL)users and simultaneously detecting target.With the objective of maximizing the Average Sum Rate(ASR)for both UL and DL users,a composite non-convex optimization problem is established,which is decomposed into sub-problems of communication scheduling optimization,transceiver beamforming design,and UAV trajectory optimization.An alternating iterative algorithm is proposed,employing relaxation optimization,extremum traversal search,augmented weighted minimum mean square error,and successive convex approximation methods to solve the aforementioned sub-problems.Simulation results demonstrate that,compared to the traditional UAV-assisted Half-Duplex(HD)ISAC scheme,the proposed FD ISAC scheme effectively improves the ASR.展开更多
With the widespread application of com-munication technology in the non-terrestrial network(NTN),the issue of the insecure communication due to the inherent openness of the NTN is increasingly being recognized.Consequ...With the widespread application of com-munication technology in the non-terrestrial network(NTN),the issue of the insecure communication due to the inherent openness of the NTN is increasingly being recognized.Consequently,safeguarding com-munication information in the NTN has emerged as a critical challenge.To address this issue,we pro-pose a beamforming and horizontal trajectory joint op-timization method for unmanned aerial vehicle(UAV)covert communications in the NTN.First,we formu-late an optimization problem that considers constraints such as the transmitting power and the distance.More-over,we employ the integrated communication and jamming(ICAJ)signal as Alice’s transmitting signal,further protecting the content of communication in-formation.Next,we construct two subproblems,and we propose an alternate optimization(AO)algorithm based on quadratic transform and penalty term method to solve the proposed two subproblems.Simulation re-sults demonstrate that the proposed method is effective and has better performance than benchmarks.展开更多
In this paper,an adaptive cubic regularisation algorithm based on affine scaling methods(ARCBASM)is proposed for solving nonlinear equality constrained programming with nonnegative constraints on variables.From the op...In this paper,an adaptive cubic regularisation algorithm based on affine scaling methods(ARCBASM)is proposed for solving nonlinear equality constrained programming with nonnegative constraints on variables.From the optimality conditions of the problem,we introduce appropriate affine matrix and construct an affine scaling ARC subproblem with linearized constraints.Composite step methods and reduced Hessian methods are applied to tackle the linearized constraints.As a result,a standard unconstrained ARC subproblem is deduced and its solution can supply sufficient decrease.The fraction to the boundary rule maintains the strict feasibility(for nonnegative constraints on variables)of every iteration point.Reflection techniques are employed to prevent the iterations from approaching zero too early.Under mild assumptions,global convergence of the algorithm is analysed.Preliminary numerical results are reported.展开更多
In this paper,we investigate the reconfigurable intelligent surface(RIS)-enabled multiple-input-single-output orthogonal frequency division multiplexing(MISO-OFDM)system under frequency-selective channels,and propose ...In this paper,we investigate the reconfigurable intelligent surface(RIS)-enabled multiple-input-single-output orthogonal frequency division multiplexing(MISO-OFDM)system under frequency-selective channels,and propose a low-complexity alternating optimization(AO)based joint beamforming and RIS phase shifts optimization algorithm to maximize the achievable rate.First,with fixed RIS phase shifts,we devise the optimal closedform transmit beamforming vectors corresponding to different subcarriers.Then,with given active beamforming vectors,near-optimal RIS reflection coefficients can be determined efficiently leveraging fractional programming(FP)combined with manifold optimization(MO)or majorization-minimization(MM)framework.Additionally,we also propose a heuristic RIS phase shifts design approach based on the sum of subcarrier gain maximization(SSGM)criterion requiring lower complexity.Numerical results indicate that the proposed MO/MM algorithm can achieve almost the same rate as the upper bound achieved by the semidefinite relaxation(SDR)algorithm,and the proposed SSGM based scheme is only slightly inferior to the upper bound while has much lower complexity.These results demonstrate the effectiveness of the proposed algorithms.展开更多
In order to obtain the remote center motion(RCM) mechanism with better performance indexes and avoid the collision of multi-manipulators in minimally invasive surgery(MIS), a novel multi-objective optimization model w...In order to obtain the remote center motion(RCM) mechanism with better performance indexes and avoid the collision of multi-manipulators in minimally invasive surgery(MIS), a novel multi-objective optimization model was presented. There were two optimization objectives: a global kinematic performance index and a comprehensive stiffness index. Other indexes to characterize the design requirements such as collision probability, workspace, mechanism parameter, mass, and wall thickness were considered as constraints. Angles between two adjacent joints and cross-section dimensions of links were chosen as the design variables. The non-dominated sorting genetic algorithm II(NSGA-II) was adopted to solve the complex multi-objective optimization problem. Then, a 3-degree of freedom(DoF) MIS robotic prototype based on optimization results has been built up. The experiments to test the spatial position change of the remote center point and to test the absolute position accuracy and repetitive position accuracy of the MIS robot were achieved, and the experimental results meet the requirements of MIS.展开更多
This paper investigates the anti-jamming communication scenario where an intelligent reflecting surface(IRS)is mounted on the unmanned aerial vehicle(UAV)to resist the malicious jamming attacks.Different from existing...This paper investigates the anti-jamming communication scenario where an intelligent reflecting surface(IRS)is mounted on the unmanned aerial vehicle(UAV)to resist the malicious jamming attacks.Different from existing works,we consider the dynamic deployment of IRS-UAV in the environment of the mobile user and unknown jammer.Therefore,a joint trajectory and passive beamforming optimization approach is proposed in the IRS-UAV enhanced networks.In detail,the optimization problem is firstly formulated into a Markov decision process(MDP).Then,a dueling double deep Q networks multi-step learning algorithm is proposed to tackle the complex and coupling decision-making problem.Finally,simulation results show that the proposed scheme can significantly improve the anti-jamming communication performance of the mobile user.展开更多
Tourism soundscape is a new field of tourism landscape research, soundscape designs offer new concepts for the landscape research and development. Taking China Dinosaur Land in Changzhou City for example, visitors'...Tourism soundscape is a new field of tourism landscape research, soundscape designs offer new concepts for the landscape research and development. Taking China Dinosaur Land in Changzhou City for example, visitors' perception about soundscape comfort in theme parks was studied. The researches found that acoustic comfort was infl uenced by objective parameters of sound and subjective perception of visitors, and when the soundscape volume stayed at a certain threshold value, visitors would gain the most satisfi ed acoustic comfort experience, and they were most sensitive to sound elements that able to convey cultural connotations of the theme park. On this basis, this paper adopted positive design, negative design, and zero design, and proposed the concepts of optimizing theme park soundscapes.展开更多
In this paper,a three-node transmission model is conceived,where the base station(BS)node leverages 3D beamforming,the reconfigurable intelligent surface(RIS)node can constructively reconfigure the wireless channel,th...In this paper,a three-node transmission model is conceived,where the base station(BS)node leverages 3D beamforming,the reconfigurable intelligent surface(RIS)node can constructively reconfigure the wireless channel,the user node only has a single antenna due to a limited price.Maximization of its downlink spectral efficiency is a joint optimization problem of three variables,namely phase-shift matrixΦof RIS,tilt angleθand beamforming vector w used in BS 3D beamforming.We solve this problem by employing the alternating optimization(AO)algorithm.But,in each iteration,a specific optimization order of firstlyΦ,secondlyθand finally w is proposed,which facilitates the search of optimalθin the way of narrowing its trust region and enabling unimodal property over the narrowed trust region.It finally results in a better combination of{Φ,θ,w}.展开更多
In order to implement the optimal design of the indoor thermal comfort based on the numerical modeling method, the numerical calculation platform is combined seamlessly with the data-processing platform, and an intera...In order to implement the optimal design of the indoor thermal comfort based on the numerical modeling method, the numerical calculation platform is combined seamlessly with the data-processing platform, and an interactive numerical calculation platform which includes the functions of numerical simulation and optimization is established. The artificial neural network （ANN） and the greedy strategy are introduced into the hill-climbing pattern heuristic search process, and the optimizing search direction can be predicted by using small samples; when searching along the direction using the greedy strategy, the optimal values can be quickly approached. Therefore, excessive external calling of the numerical modeling process can be avoided, and the optimization time is decreased obviously. The experimental results indicate that the satisfied output parameters of air conditioning can be quickly given out based on the interactive numerical calculation platform and the improved search method, and the optimization for indoor thermal comfort can be completed.展开更多
Sinter is the core raw material for blast furnaces.Flue pressure,which is an important state parameter,affects sinter quality.In this paper,flue pressure prediction and optimization were studied based on the shapley a...Sinter is the core raw material for blast furnaces.Flue pressure,which is an important state parameter,affects sinter quality.In this paper,flue pressure prediction and optimization were studied based on the shapley additive explanation(SHAP)to predict the flue pressure and take targeted adjustment measures.First,the sintering process data were collected and processed.A flue pressure prediction model was then constructed after comparing different feature selection methods and model algorithms using SHAP+extremely random-ized trees(ET).The prediction accuracy of the model within the error range of±0.25 kPa was 92.63%.SHAP analysis was employed to improve the interpretability of the prediction model.The effects of various sintering operation parameters on flue pressure,the relation-ship between the numerical range of key operation parameters and flue pressure,the effect of operation parameter combinations on flue pressure,and the prediction process of the flue pressure prediction model on a single sample were analyzed.A flue pressure optimization module was also constructed and analyzed when the prediction satisfied the judgment conditions.The operating parameter combination was then pushed.The flue pressure was increased by 5.87%during the verification process,achieving a good optimization effect.展开更多
Present of wind power is sporadically and cannot be utilized as the only fundamental load of energy sources.This paper proposes a wind-solar hybrid energy storage system(HESS)to ensure a stable supply grid for a longe...Present of wind power is sporadically and cannot be utilized as the only fundamental load of energy sources.This paper proposes a wind-solar hybrid energy storage system(HESS)to ensure a stable supply grid for a longer period.A multi-objective genetic algorithm(MOGA)and state of charge(SOC)region division for the batteries are introduced to solve the objective function and configuration of the system capacity,respectively.MATLAB/Simulink was used for simulation test.The optimization results show that for a 0.5 MW wind power and 0.5 MW photovoltaic system,with a combination of a 300 Ah lithium battery,a 200 Ah lead-acid battery,and a water storage tank,the proposed strategy reduces the system construction cost by approximately 18,000 yuan.Additionally,the cycle count of the electrochemical energy storage systemincreases from4515 to 4660,while the depth of discharge decreases from 55.37%to 53.65%,achieving shallow charging and discharging,thereby extending battery life and reducing grid voltage fluctuations significantly.The proposed strategy is a guide for stabilizing the grid connection of wind and solar power generation,capability allocation,and energy management of energy conservation systems.展开更多
In this paper,we propose a three-term conjugate gradient method for solving unconstrained optimization problems based on the Hestenes-Stiefel(HS)conjugate gradient method and Polak-Ribiere-Polyak(PRP)conjugate gradien...In this paper,we propose a three-term conjugate gradient method for solving unconstrained optimization problems based on the Hestenes-Stiefel(HS)conjugate gradient method and Polak-Ribiere-Polyak(PRP)conjugate gradient method.Under the condition of standard Wolfe line search,the proposed search direction is the descent direction.For general nonlinear functions,the method is globally convergent.Finally,numerical results show that the proposed method is efficient.展开更多
With the increasing complexity of the current electromagnetic environment,excessive microwave radi-ation not only does harm to human health but also forms various electromagnetic interference to so-phisticated electro...With the increasing complexity of the current electromagnetic environment,excessive microwave radi-ation not only does harm to human health but also forms various electromagnetic interference to so-phisticated electronic instruments.Therefore,the design and preparation of electromagnetic absorbing composites represent an efficient approach to mitigate the current hazards of electromagnetic radiation.However,traditional electromagnetic absorbers are difficult to satisfy the demands of actual utilization in the face of new challenges,and emerging absorbents have garnered increasing attention due to their structure and performance-based advantages.In this review,several emerging composites of Mxene-based,biochar-based,chiral,and heat-resisting are discussed in detail,including their synthetic strategy,structural superiority and regulation method,and final optimization of electromagnetic absorption ca-pacity.These insights provide a comprehensive reference for the future development of new-generation electromagnetic-wave absorption composites.Moreover,the potential development directions of these emerging absorbers have been proposed as well.展开更多
In the area of reservoir engineering,the optimization of oil and gas production is a complex task involving a myriad of interconnected decision variables shaping the production system's infrastructure.Traditionall...In the area of reservoir engineering,the optimization of oil and gas production is a complex task involving a myriad of interconnected decision variables shaping the production system's infrastructure.Traditionally,this optimization process was centered on a single objective,such as net present value,return on investment,cumulative oil production,or cumulative water production.However,the inherent complexity of reservoir exploration necessitates a departure from this single-objective approach.Mul-tiple conflicting production and economic indicators must now be considered to enable more precise and robust decision-making.In response to this challenge,researchers have embarked on a journey to explore field development optimization of multiple conflicting criteria,employing the formidable tools of multi-objective optimization algorithms.These algorithms delve into the intricate terrain of production strategy design,seeking to strike a delicate balance between the often-contrasting objectives.Over the years,a plethora of these algorithms have emerged,ranging from a priori methods to a posteriori approach,each offering unique insights and capabilities.This survey endeavors to encapsulate,catego-rize,and scrutinize these invaluable contributions to field development optimization,which grapple with the complexities of multiple conflicting objective functions.Beyond the overview of existing methodologies,we delve into the persisting challenges faced by researchers and practitioners alike.Notably,the application of multi-objective optimization techniques to production optimization is hin-dered by the resource-intensive nature of reservoir simulation,especially when confronted with inherent uncertainties.As a result of this survey,emerging opportunities have been identified that will serve as catalysts for pivotal research endeavors in the future.As intelligent and more efficient algo-rithms continue to evolve,the potential for addressing hitherto insurmountable field development optimization obstacles becomes increasingly viable.This discussion on future prospects aims to inspire critical research,guiding the way toward innovative solutions in the ever-evolving landscape of oil and gas production optimization.展开更多
Single-pixel imaging(SPI)enables efficient sensing in challenging conditions.However,the requirement for numerous samplings constrains its practicality.We address the challenge of high-quality SPI reconstruction at ul...Single-pixel imaging(SPI)enables efficient sensing in challenging conditions.However,the requirement for numerous samplings constrains its practicality.We address the challenge of high-quality SPI reconstruction at ultra-low sampling rates.We develop an alternative optimization with physics and a data-driven diffusion network(APD-Net).It features alternative optimization driven by the learned task-agnostic natural image prior and the task-specific physics prior.During the training stage,APD-Net harnesses the power of diffusion models to capture data-driven statistics of natural signals.In the inference stage,the physics prior is introduced as corrective guidance to ensure consistency between the physics imaging model and the natural image probability distribution.Through alternative optimization,APD-Net reconstructs data-efficient,high-fidelity images that are statistically and physically compliant.To accelerate reconstruction,initializing images with the inverse SPI physical model reduces the need for reconstruction inference from 100 to 30 steps.Through both numerical simulations and real prototype experiments,APD-Net achieves high-quality,full-color reconstructions of complex natural images at a low sampling rate of 1%.In addition,APD-Net’s tuning-free nature ensures robustness across various imaging setups and sampling rates.Our research offers a broadly applicable approach for various applications,including but not limited to medical imaging and industrial inspection.展开更多
Hybrid beamforming(HBF)has become an attractive and important technology in massive multiple-input multiple-output(MIMO)millimeter-wave(mmWave)systems.There are different hybrid architectures in HBF depending on diffe...Hybrid beamforming(HBF)has become an attractive and important technology in massive multiple-input multiple-output(MIMO)millimeter-wave(mmWave)systems.There are different hybrid architectures in HBF depending on different connection strategies of the phase shifter network between antennas and radio frequency chains.This paper investigates HBF optimization with different hybrid architectures in broadband point-to-point mmWave MIMO systems.The joint hybrid architecture and beamforming optimization problem is divided into two sub-problems.First,we transform the spectral efficiency maximization problem into an equivalent weighted mean squared error minimization problem,and propose an algorithm based on the manifold optimization method for the hybrid beamformer with a fixed hybrid architecture.The overlapped subarray architecture which balances well between hardware costs and system performance is investigated.We further propose an algorithm to dynamically partition antenna subarrays and combine it with the HBF optimization algorithm.Simulation results are presented to demonstrate the performance improvement of our proposed algorithms.展开更多
Considering the uncertainty of grid connection of electric vehicle charging stations and the uncertainty of new energy and residential electricity load,a spatio-temporal decoupling strategy of dynamic reactive power o...Considering the uncertainty of grid connection of electric vehicle charging stations and the uncertainty of new energy and residential electricity load,a spatio-temporal decoupling strategy of dynamic reactive power optimization based on clustering-local relaxation-correction is proposed.Firstly,the k-medoids clustering algorithm is used to divide the reduced power scene into periods.Then,the discrete variables and continuous variables are optimized in the same period of time.Finally,the number of input groups of parallel capacitor banks(CB)in multiple periods is fixed,and then the secondary static reactive power optimization correction is carried out by using the continuous reactive power output device based on the static reactive power compensation device(SVC),the new energy grid-connected inverter,and the electric vehicle charging station.According to the characteristics of the model,a hybrid optimization algorithm with a cross-feedback mechanism is used to solve different types of variables,and an improved artificial hummingbird algorithm based on tent chaotic mapping and adaptive mutation is proposed to improve the solution efficiency.The simulation results show that the proposed decoupling strategy can obtain satisfactory optimization resultswhile strictly guaranteeing the dynamic constraints of discrete variables,and the hybrid algorithm can effectively solve the mixed integer nonlinear optimization problem.展开更多
基金supported by National Key R&D Program of China with Grant number 2019YFB1803400in part by Sichuan Science and Technology Program under Grant 2024NSFSC0472。
文摘As a novel signaling technology,the power splitting receiver(PSR)simultaneously employs both the coherent and non-coherent signal processing.In order to improve its communication performance,an intelligent reflecting surface(IRS)is introduced into its signal propagation path.Consequently,an IRSaided PSR is concerned for a point-to-point(P2P)data link,where both the single-antenna and multiantenna deployments on the receiver are discussed.We aim at maximizing the capacity of the concerned P2P data-link by jointly optimizing the passive beamforming of IRS and the splitting ratio of PSR,either in single-antenna or multi-antenna case.However,owing to the coupling of multiple variables,the optimization problems are non-convex and challenging,especially in the later multi-antenna case.The proposed alternating-approximating algorithm(A-A),aided by semi-definite relaxation(SDR)and successive convex approximation(SCA)methods,etc.,successfully overcomes these challenges.We compare the IRS-aided PSR system that optimized by our proposed algorithm to the systems without IRS or PSR,and the systems without joint optimization.The simulation results show that our proposal has a better performance.
文摘The recent development in Lucknow shows that the amount of built mass may increase significantly soon,which may affect outdoor thermal comfort.This study aims to achieve a better alternative to the geometrical configuration of vertical surfaces that helps improve the outdoor thermal comfort level.The study primarily deals with the exploration of built forms by altering the planar forms,heights,and orientations to arrive at a better composition of vertical surfaces.144 typologies were finally generated,which were then simulated in ENVI-met.The results show that,with the I-shaped typology it is difficult to reduce solar access,whereas in terms of ventilation,the typology performed better than L-shaped and C-shaped typologies.For this reason,the hours of solar access,as well as wind speed,should be seen together while developing the built-form typology.Urban neighborhoods can be designed with streets and open spaces oriented primarily to northeast-southwest and northwest-southeast directions which allow the open spaces to be thermally more comfortable than the rest of the orientation.This research highlights the importance of varying building heights to enhance thermal comfort.The findings provide valuable insights for composite climate cities like lucknow and can serve as a framework for future design strategies aimed at mitigating outdoor thermal discomfort.It is therefore important for planners,urban designers,and architects to design considering the minimal impact of the upcoming development on the thermal comfort level.
基金supported in part by Sub Project of National Key Research and Development Plan in 2020.NO.2020YFC1511704Beijing Information Science&Technology University.NO.2020KYNH212,NO.2021CGZH302+1 种基金Beijing Science and Technology Project(Grant No.Z211100004421009)in part by the National Natural Science Foundation of China(Grant No.62301058).
文摘This paper proposes the Unmanned Aerial Vehicle(UAV)-assisted Full-Duplex(FD)Integrated Sensing And Communication(ISAC)system.In this system,the UAV integrates sensing and communication functions,capable of receiving transmission signals from Uplink(UL)users and echo signal from target,while communicating with Downlink(DL)users and simultaneously detecting target.With the objective of maximizing the Average Sum Rate(ASR)for both UL and DL users,a composite non-convex optimization problem is established,which is decomposed into sub-problems of communication scheduling optimization,transceiver beamforming design,and UAV trajectory optimization.An alternating iterative algorithm is proposed,employing relaxation optimization,extremum traversal search,augmented weighted minimum mean square error,and successive convex approximation methods to solve the aforementioned sub-problems.Simulation results demonstrate that,compared to the traditional UAV-assisted Half-Duplex(HD)ISAC scheme,the proposed FD ISAC scheme effectively improves the ASR.
基金supported in part by the National Natural Science Foundation of China under Grant U2441250 and 62231027in part by Natural Science Basic Research Programof Shaanxi under Grant 2024JC-JCQN-63+2 种基金in part by InnovationCapability Support Program of Shaanxi under Grant2024RS-CXTD-01in part by New Technology Research University Cooperation Project under Grant SKX242010031in part by the FundamentalResearch Funds for the Central Universities and theInnovation Fund of Xidian University under GrantYJSJ25007.
文摘With the widespread application of com-munication technology in the non-terrestrial network(NTN),the issue of the insecure communication due to the inherent openness of the NTN is increasingly being recognized.Consequently,safeguarding com-munication information in the NTN has emerged as a critical challenge.To address this issue,we pro-pose a beamforming and horizontal trajectory joint op-timization method for unmanned aerial vehicle(UAV)covert communications in the NTN.First,we formu-late an optimization problem that considers constraints such as the transmitting power and the distance.More-over,we employ the integrated communication and jamming(ICAJ)signal as Alice’s transmitting signal,further protecting the content of communication in-formation.Next,we construct two subproblems,and we propose an alternate optimization(AO)algorithm based on quadratic transform and penalty term method to solve the proposed two subproblems.Simulation re-sults demonstrate that the proposed method is effective and has better performance than benchmarks.
基金Supported by the National Natural Science Foundation of China(12071133)Natural Science Foundation of Henan Province(252300421993)Key Scientific Research Project of Higher Education Institutions in Henan Province(25B110005)。
文摘In this paper,an adaptive cubic regularisation algorithm based on affine scaling methods(ARCBASM)is proposed for solving nonlinear equality constrained programming with nonnegative constraints on variables.From the optimality conditions of the problem,we introduce appropriate affine matrix and construct an affine scaling ARC subproblem with linearized constraints.Composite step methods and reduced Hessian methods are applied to tackle the linearized constraints.As a result,a standard unconstrained ARC subproblem is deduced and its solution can supply sufficient decrease.The fraction to the boundary rule maintains the strict feasibility(for nonnegative constraints on variables)of every iteration point.Reflection techniques are employed to prevent the iterations from approaching zero too early.Under mild assumptions,global convergence of the algorithm is analysed.Preliminary numerical results are reported.
基金supported in part by the National Natural Science Foundation of China under Grants 61971126 and 61921004ZTE CorporationState Key Laboratory of Mobile Network and Mobile Multimedia Technology.
文摘In this paper,we investigate the reconfigurable intelligent surface(RIS)-enabled multiple-input-single-output orthogonal frequency division multiplexing(MISO-OFDM)system under frequency-selective channels,and propose a low-complexity alternating optimization(AO)based joint beamforming and RIS phase shifts optimization algorithm to maximize the achievable rate.First,with fixed RIS phase shifts,we devise the optimal closedform transmit beamforming vectors corresponding to different subcarriers.Then,with given active beamforming vectors,near-optimal RIS reflection coefficients can be determined efficiently leveraging fractional programming(FP)combined with manifold optimization(MO)or majorization-minimization(MM)framework.Additionally,we also propose a heuristic RIS phase shifts design approach based on the sum of subcarrier gain maximization(SSGM)criterion requiring lower complexity.Numerical results indicate that the proposed MO/MM algorithm can achieve almost the same rate as the upper bound achieved by the semidefinite relaxation(SDR)algorithm,and the proposed SSGM based scheme is only slightly inferior to the upper bound while has much lower complexity.These results demonstrate the effectiveness of the proposed algorithms.
基金Project(SS2012AA041601)supported by the National High Technology Research and Development Program of ChinaProject(81201150)supported by the National Natural Science Foundation of China
文摘In order to obtain the remote center motion(RCM) mechanism with better performance indexes and avoid the collision of multi-manipulators in minimally invasive surgery(MIS), a novel multi-objective optimization model was presented. There were two optimization objectives: a global kinematic performance index and a comprehensive stiffness index. Other indexes to characterize the design requirements such as collision probability, workspace, mechanism parameter, mass, and wall thickness were considered as constraints. Angles between two adjacent joints and cross-section dimensions of links were chosen as the design variables. The non-dominated sorting genetic algorithm II(NSGA-II) was adopted to solve the complex multi-objective optimization problem. Then, a 3-degree of freedom(DoF) MIS robotic prototype based on optimization results has been built up. The experiments to test the spatial position change of the remote center point and to test the absolute position accuracy and repetitive position accuracy of the MIS robot were achieved, and the experimental results meet the requirements of MIS.
基金This work was supported in part by the National Natural Science Foundation of China(No.61971474,No.61771488)in part by the Beijing Nova Program under Grant Z201100006820121in part by China Postdoctoral Science Foundation Funded Project under Grant 2019T120071.
文摘This paper investigates the anti-jamming communication scenario where an intelligent reflecting surface(IRS)is mounted on the unmanned aerial vehicle(UAV)to resist the malicious jamming attacks.Different from existing works,we consider the dynamic deployment of IRS-UAV in the environment of the mobile user and unknown jammer.Therefore,a joint trajectory and passive beamforming optimization approach is proposed in the IRS-UAV enhanced networks.In detail,the optimization problem is firstly formulated into a Markov decision process(MDP).Then,a dueling double deep Q networks multi-step learning algorithm is proposed to tackle the complex and coupling decision-making problem.Finally,simulation results show that the proposed scheme can significantly improve the anti-jamming communication performance of the mobile user.
基金Sponsored by National Social Science Foundation Program(11CGL054)Philosophical and Social Science Foundation of Jiangsu Provincial Department of Education(2011SJD630039)
文摘Tourism soundscape is a new field of tourism landscape research, soundscape designs offer new concepts for the landscape research and development. Taking China Dinosaur Land in Changzhou City for example, visitors' perception about soundscape comfort in theme parks was studied. The researches found that acoustic comfort was infl uenced by objective parameters of sound and subjective perception of visitors, and when the soundscape volume stayed at a certain threshold value, visitors would gain the most satisfi ed acoustic comfort experience, and they were most sensitive to sound elements that able to convey cultural connotations of the theme park. On this basis, this paper adopted positive design, negative design, and zero design, and proposed the concepts of optimizing theme park soundscapes.
基金supported by the National Key R&D Program of China under Grant 2019YFB1803400partly by National Natural Science Foundation of China under Grant 62071394.
文摘In this paper,a three-node transmission model is conceived,where the base station(BS)node leverages 3D beamforming,the reconfigurable intelligent surface(RIS)node can constructively reconfigure the wireless channel,the user node only has a single antenna due to a limited price.Maximization of its downlink spectral efficiency is a joint optimization problem of three variables,namely phase-shift matrixΦof RIS,tilt angleθand beamforming vector w used in BS 3D beamforming.We solve this problem by employing the alternating optimization(AO)algorithm.But,in each iteration,a specific optimization order of firstlyΦ,secondlyθand finally w is proposed,which facilitates the search of optimalθin the way of narrowing its trust region and enabling unimodal property over the narrowed trust region.It finally results in a better combination of{Φ,θ,w}.
基金Sponsored by the National Program"973"Project (2005CB623906)
文摘In order to implement the optimal design of the indoor thermal comfort based on the numerical modeling method, the numerical calculation platform is combined seamlessly with the data-processing platform, and an interactive numerical calculation platform which includes the functions of numerical simulation and optimization is established. The artificial neural network （ANN） and the greedy strategy are introduced into the hill-climbing pattern heuristic search process, and the optimizing search direction can be predicted by using small samples; when searching along the direction using the greedy strategy, the optimal values can be quickly approached. Therefore, excessive external calling of the numerical modeling process can be avoided, and the optimization time is decreased obviously. The experimental results indicate that the satisfied output parameters of air conditioning can be quickly given out based on the interactive numerical calculation platform and the improved search method, and the optimization for indoor thermal comfort can be completed.
基金supported by the General Program of the National Natural Science Foundation of China(No.52274326)the China Baowu Low Carbon Metallurgy Innovation Foundation(No.BWLCF202109)the Seventh Batch of Ten Thousand Talents Plan of China(No.ZX20220553).
文摘Sinter is the core raw material for blast furnaces.Flue pressure,which is an important state parameter,affects sinter quality.In this paper,flue pressure prediction and optimization were studied based on the shapley additive explanation(SHAP)to predict the flue pressure and take targeted adjustment measures.First,the sintering process data were collected and processed.A flue pressure prediction model was then constructed after comparing different feature selection methods and model algorithms using SHAP+extremely random-ized trees(ET).The prediction accuracy of the model within the error range of±0.25 kPa was 92.63%.SHAP analysis was employed to improve the interpretability of the prediction model.The effects of various sintering operation parameters on flue pressure,the relation-ship between the numerical range of key operation parameters and flue pressure,the effect of operation parameter combinations on flue pressure,and the prediction process of the flue pressure prediction model on a single sample were analyzed.A flue pressure optimization module was also constructed and analyzed when the prediction satisfied the judgment conditions.The operating parameter combination was then pushed.The flue pressure was increased by 5.87%during the verification process,achieving a good optimization effect.
基金supported by a Horizontal Project on the Development of a Hybrid Energy Storage Simulation Model for Wind Power Based on an RT-LAB Simulation System(PH2023000190)the Inner Mongolia Natural Science Foundation Project and the Optimization of Exergy Efficiency of a Hybrid Energy Storage System with Crossover Control for Wind Power(2023JQ04).
文摘Present of wind power is sporadically and cannot be utilized as the only fundamental load of energy sources.This paper proposes a wind-solar hybrid energy storage system(HESS)to ensure a stable supply grid for a longer period.A multi-objective genetic algorithm(MOGA)and state of charge(SOC)region division for the batteries are introduced to solve the objective function and configuration of the system capacity,respectively.MATLAB/Simulink was used for simulation test.The optimization results show that for a 0.5 MW wind power and 0.5 MW photovoltaic system,with a combination of a 300 Ah lithium battery,a 200 Ah lead-acid battery,and a water storage tank,the proposed strategy reduces the system construction cost by approximately 18,000 yuan.Additionally,the cycle count of the electrochemical energy storage systemincreases from4515 to 4660,while the depth of discharge decreases from 55.37%to 53.65%,achieving shallow charging and discharging,thereby extending battery life and reducing grid voltage fluctuations significantly.The proposed strategy is a guide for stabilizing the grid connection of wind and solar power generation,capability allocation,and energy management of energy conservation systems.
基金Supported by the Science and Technology Project of Guangxi(Guike AD23023002)。
文摘In this paper,we propose a three-term conjugate gradient method for solving unconstrained optimization problems based on the Hestenes-Stiefel(HS)conjugate gradient method and Polak-Ribiere-Polyak(PRP)conjugate gradient method.Under the condition of standard Wolfe line search,the proposed search direction is the descent direction.For general nonlinear functions,the method is globally convergent.Finally,numerical results show that the proposed method is efficient.
基金supported by the Surface Project of Local De-velopment in Science and Technology Guided by Central Govern-ment(No.2021ZYD0041)the National Natural Science Founda-tion of China(Nos.52377026 and 52301192)+3 种基金the Natural Science Foundation of Shandong Province(No.ZR2019YQ24)the Taishan Scholars and Young Experts Program of Shandong Province(No.tsqn202103057)the Special Financial of Shandong Province(Struc-tural Design of High-efficiency Electromagnetic Wave-absorbing Composite Materials and Construction of Shandong Provincial Tal-ent Teams)the“Sanqin Scholars”Innovation Teams Project of Shaanxi Province(Clean Energy Materials and High-Performance Devices Innovation Team of Shaanxi Dongling Smelting Co.,Ltd.).
文摘With the increasing complexity of the current electromagnetic environment,excessive microwave radi-ation not only does harm to human health but also forms various electromagnetic interference to so-phisticated electronic instruments.Therefore,the design and preparation of electromagnetic absorbing composites represent an efficient approach to mitigate the current hazards of electromagnetic radiation.However,traditional electromagnetic absorbers are difficult to satisfy the demands of actual utilization in the face of new challenges,and emerging absorbents have garnered increasing attention due to their structure and performance-based advantages.In this review,several emerging composites of Mxene-based,biochar-based,chiral,and heat-resisting are discussed in detail,including their synthetic strategy,structural superiority and regulation method,and final optimization of electromagnetic absorption ca-pacity.These insights provide a comprehensive reference for the future development of new-generation electromagnetic-wave absorption composites.Moreover,the potential development directions of these emerging absorbers have been proposed as well.
基金the support of EPIC - Energy Production Innovation Center, hosted by the University of Campinas (UNICAMP) and sponsored by Equinor Brazil and FAPESP - Sao Paulo Research Foundation (2021/04878- 7 and 2017/15736-3)financed in part by the Coordenacao de Aperfeicoamento de Pessoal de Nível Superior Brasil (CAPES) - Financing Code 001
文摘In the area of reservoir engineering,the optimization of oil and gas production is a complex task involving a myriad of interconnected decision variables shaping the production system's infrastructure.Traditionally,this optimization process was centered on a single objective,such as net present value,return on investment,cumulative oil production,or cumulative water production.However,the inherent complexity of reservoir exploration necessitates a departure from this single-objective approach.Mul-tiple conflicting production and economic indicators must now be considered to enable more precise and robust decision-making.In response to this challenge,researchers have embarked on a journey to explore field development optimization of multiple conflicting criteria,employing the formidable tools of multi-objective optimization algorithms.These algorithms delve into the intricate terrain of production strategy design,seeking to strike a delicate balance between the often-contrasting objectives.Over the years,a plethora of these algorithms have emerged,ranging from a priori methods to a posteriori approach,each offering unique insights and capabilities.This survey endeavors to encapsulate,catego-rize,and scrutinize these invaluable contributions to field development optimization,which grapple with the complexities of multiple conflicting objective functions.Beyond the overview of existing methodologies,we delve into the persisting challenges faced by researchers and practitioners alike.Notably,the application of multi-objective optimization techniques to production optimization is hin-dered by the resource-intensive nature of reservoir simulation,especially when confronted with inherent uncertainties.As a result of this survey,emerging opportunities have been identified that will serve as catalysts for pivotal research endeavors in the future.As intelligent and more efficient algo-rithms continue to evolve,the potential for addressing hitherto insurmountable field development optimization obstacles becomes increasingly viable.This discussion on future prospects aims to inspire critical research,guiding the way toward innovative solutions in the ever-evolving landscape of oil and gas production optimization.
基金upported by the National Natural Science Foundation of China(Grant No.62305184)the Major Key Project of Pengcheng Laboratory(Grant No.PCL2024A1)+1 种基金the Basic and Applied Basic Research Foundation of Guangdong Province(Grant No.2023A1515012932)the Science,Technology and Innovation Commission of Shenzhen Municipality(Grant No.WDZC20220818100259004).
文摘Single-pixel imaging(SPI)enables efficient sensing in challenging conditions.However,the requirement for numerous samplings constrains its practicality.We address the challenge of high-quality SPI reconstruction at ultra-low sampling rates.We develop an alternative optimization with physics and a data-driven diffusion network(APD-Net).It features alternative optimization driven by the learned task-agnostic natural image prior and the task-specific physics prior.During the training stage,APD-Net harnesses the power of diffusion models to capture data-driven statistics of natural signals.In the inference stage,the physics prior is introduced as corrective guidance to ensure consistency between the physics imaging model and the natural image probability distribution.Through alternative optimization,APD-Net reconstructs data-efficient,high-fidelity images that are statistically and physically compliant.To accelerate reconstruction,initializing images with the inverse SPI physical model reduces the need for reconstruction inference from 100 to 30 steps.Through both numerical simulations and real prototype experiments,APD-Net achieves high-quality,full-color reconstructions of complex natural images at a low sampling rate of 1%.In addition,APD-Net’s tuning-free nature ensures robustness across various imaging setups and sampling rates.Our research offers a broadly applicable approach for various applications,including but not limited to medical imaging and industrial inspection.
基金supported by ZTE Industry-University-Institute Cooperation Funds,the Natural Science Foundation of Shanghai under Grant No.23ZR1407300the National Natural Science Foundation of China un⁃der Grant No.61771147.
文摘Hybrid beamforming(HBF)has become an attractive and important technology in massive multiple-input multiple-output(MIMO)millimeter-wave(mmWave)systems.There are different hybrid architectures in HBF depending on different connection strategies of the phase shifter network between antennas and radio frequency chains.This paper investigates HBF optimization with different hybrid architectures in broadband point-to-point mmWave MIMO systems.The joint hybrid architecture and beamforming optimization problem is divided into two sub-problems.First,we transform the spectral efficiency maximization problem into an equivalent weighted mean squared error minimization problem,and propose an algorithm based on the manifold optimization method for the hybrid beamformer with a fixed hybrid architecture.The overlapped subarray architecture which balances well between hardware costs and system performance is investigated.We further propose an algorithm to dynamically partition antenna subarrays and combine it with the HBF optimization algorithm.Simulation results are presented to demonstrate the performance improvement of our proposed algorithms.
基金funded by the“Research and Application Project of Collaborative Optimization Control Technology for Distribution Station Area for High Proportion Distributed PV Consumption(4000-202318079A-1-1-ZN)”of the Headquarters of the State Grid Corporation.
文摘Considering the uncertainty of grid connection of electric vehicle charging stations and the uncertainty of new energy and residential electricity load,a spatio-temporal decoupling strategy of dynamic reactive power optimization based on clustering-local relaxation-correction is proposed.Firstly,the k-medoids clustering algorithm is used to divide the reduced power scene into periods.Then,the discrete variables and continuous variables are optimized in the same period of time.Finally,the number of input groups of parallel capacitor banks(CB)in multiple periods is fixed,and then the secondary static reactive power optimization correction is carried out by using the continuous reactive power output device based on the static reactive power compensation device(SVC),the new energy grid-connected inverter,and the electric vehicle charging station.According to the characteristics of the model,a hybrid optimization algorithm with a cross-feedback mechanism is used to solve different types of variables,and an improved artificial hummingbird algorithm based on tent chaotic mapping and adaptive mutation is proposed to improve the solution efficiency.The simulation results show that the proposed decoupling strategy can obtain satisfactory optimization resultswhile strictly guaranteeing the dynamic constraints of discrete variables,and the hybrid algorithm can effectively solve the mixed integer nonlinear optimization problem.
