To solve the weapon network system optimization problem against small raid objects with low attitude,the concept of direction probability and a new evaluation index system are proposed.By calculating the whole damagin...To solve the weapon network system optimization problem against small raid objects with low attitude,the concept of direction probability and a new evaluation index system are proposed.By calculating the whole damaging probability that changes with the defending angle,the efficiency of the whole weapon network system can be subtly described.With such method,we can avoid the inconformity of the description obtained from the traditional index systems.Three new indexes are also proposed,i.e.join index,overlap index and cover index,which help manage the relationship among several sub-weapon-networks.By normalizing the computation results with the Sigmoid function,the matching problem between the optimization algorithm and indexes is well settled.Also,the algorithm of improved marriage in honey bees optimization that proposed in our previous work is applied to optimize the embattlement problem.Simulation is carried out to show the efficiency of the proposed indexes and the optimization algorithm.展开更多
Well production optimization is a complex and time-consuming task in the oilfield development.The combination of reservoir numerical simulator with optimization algorithms is usually used to optimize well production.T...Well production optimization is a complex and time-consuming task in the oilfield development.The combination of reservoir numerical simulator with optimization algorithms is usually used to optimize well production.This method spends most of computing time in objective function evaluation by reservoir numerical simulator which limits its optimization efficiency.To improve optimization efficiency,a well production optimization method using streamline features-based objective function and Bayesian adaptive direct search optimization(BADS)algorithm is established.This new objective function,which represents the water flooding potential,is extracted from streamline features.It only needs to call the streamline simulator to run one time step,instead of calling the simulator to calculate the target value at the end of development,which greatly reduces the running time of the simulator.Then the well production optimization model is established and solved by the BADS algorithm.The feasibility of the new objective function and the efficiency of this optimization method are verified by three examples.Results demonstrate that the new objective function is positively correlated with the cumulative oil production.And the BADS algorithm is superior to other common algorithms in convergence speed,solution stability and optimization accuracy.Besides,this method can significantly accelerate the speed of well production optimization process compared with the objective function calculated by other conventional methods.It can provide a more effective basis for determining the optimal well production for actual oilfield development.展开更多
The growing demand for deployable phased-array antennas in space applications requires innovative solutions to optimize the folded configurations and reduce the computational complexity.Existing methods face limitatio...The growing demand for deployable phased-array antennas in space applications requires innovative solutions to optimize the folded configurations and reduce the computational complexity.Existing methods face limitations due to the low efficiency of traditional algorithms and the lack of effective constraint strategies,resulting in excessive solution spaces.This study proposes forward shannon entropy wave function collapse(FSE-WFC),a novel method for designing panel configurations of one-dimensional deployable phased-array antennas using the wave function collapse algorithm.This addresses two key challenges:the excessive number of panel layout options and high computational costs.First,it analyzes the relationship between the panel connection positions and the folded form to impose constraints on the panel combinations.It then calculates the information entropy of the potential configurations to identify low-entropy solutions,thereby narrowing the solution space.Finally,boundary constraints and interference check were applied to refine the results.This approach significantly reduced the calculation time while improving the folding state and envelope volume of the antenna.The results show that the FSE-WFC algorithm reduces the envelope area by 18.3%for a 350 mm high satellite and 9.0%for a 600 mm high satellite,while satisfying the connectivity constraints.As the first application of the wave-function collapse algorithm to antenna folding design,this study introduces an information entropy-based constraint generation method that provides an efficient solution for deployable antenna optimization.展开更多
Recently,genetic algorithms(GAs) have been applied to multi-modal dynamic optimization(MDO).In this kind of optimization,an algorithm is required not only to find the multiple optimal solutions but also to locate a dy...Recently,genetic algorithms(GAs) have been applied to multi-modal dynamic optimization(MDO).In this kind of optimization,an algorithm is required not only to find the multiple optimal solutions but also to locate a dynamically changing optimum.Our fuzzy genetic sharing(FGS) approach is based on a novel genetic algorithm with dynamic niche sharing(GADNS).FGS finds the optimal solutions,while maintaining the diversity of the population.For this,FGS uses several strategies.First,an unsupervised fuzzy clustering method is used to track multiple optima and perform GADNS.Second,a modified tournament selection is used to control selection pressure.Third,a novel mutation with an adaptive mutation rate is used to locate unexplored search areas.The effectiveness of FGS in dynamic environments is demonstrated using the generalized dynamic benchmark generator(GDBG).展开更多
In this paper, we establish a second-order sufficient condition for constrained optimization problems of a class of so called t-stable functions in terms of the first-order and the second-order Dini type directional d...In this paper, we establish a second-order sufficient condition for constrained optimization problems of a class of so called t-stable functions in terms of the first-order and the second-order Dini type directional derivatives. The result extends the corresponding result of [D. Bednarik and K. Pastor, Math. Program. Ser. A, 113（2008）, 283-298] to constrained optimization problems.展开更多
针对大跨度斜拉桥的索力优化问题,该文基于径向基神经网络(Radial Basis Function Neural Network,RBFNN)拟合响应面,提出了一种考虑斜拉索可靠度指标的索力优化方法。通过RBFNN训练拟合结构隐式功能函数,建立求解可靠度指标的RBFNN响...针对大跨度斜拉桥的索力优化问题,该文基于径向基神经网络(Radial Basis Function Neural Network,RBFNN)拟合响应面,提出了一种考虑斜拉索可靠度指标的索力优化方法。通过RBFNN训练拟合结构隐式功能函数,建立求解可靠度指标的RBFNN响应面模型,采用改进粒子群算法对考虑可靠度指标的索力优化模型进行寻优求解。研究结果表明:RBFNN可以精确预测结构响应并拟合结构隐式功能函数,20个测试集的平均拟合误差仅为3.25%;改进粒子群算法对索力优化问题具有良好的适应性。相较于标准粒子群算法,改进后的算法收敛精度更高,收敛速度更快,优化后整体索力分布趋势与原索力分布趋势大致相同,采用优化索力计算得到的跨中位置斜拉索可靠度指标明显提升,各斜拉索平均可靠度增幅达3%左右,主梁线形得到大幅改善,最大挠度降幅高达36%。展开更多
We proposed and demonstrated the ultra-compact 1310/1550 nm wavelength multiplexer/demultiplexer assisted by subwavelength grating(SWG)using particle swarm optimization(PSO)algorithm in silicon-on-insulator(SOI)platfo...We proposed and demonstrated the ultra-compact 1310/1550 nm wavelength multiplexer/demultiplexer assisted by subwavelength grating(SWG)using particle swarm optimization(PSO)algorithm in silicon-on-insulator(SOI)platform.Through the self-imaging effect of multimode interference(MMI)coupler,the demultiplexing function for 1310 nm and 1550 nm wavelengths is implemented.After that,three parallel SWG-based slots are inserted into the MMI section so that the effective refractive index of the modes can be engineered and thus the beat length can be adjusted.Importantly,these three SWG slots significantly reduce the length of the device,which is much shorter than the length of traditional MMI-based wavelength demultiplexers.Ultimately,by using the PSO algorithm,the equivalent refractive index and width of the SWG in a certain range are optimized to achieve the best performance of the wavelength demultiplexer.It has been verified that the device footprint is only 2×30.68μm^(2),and 1 dB bandwidths of larger than 120 nm are acquired at 1310 nm and 1550 nm wavelengths.Meanwhile,the transmitted spectrum shows that the insertion loss(IL)values are below 0.47 dB at both wavelengths when the extinction ratio(ER)values are above 12.65 dB.This inverse design approach has been proved to be efficient in increasing bandwidth and reducing device length.展开更多
针对全变分模型(total variation,TV)以图像的梯度信息作为去噪的尺度参数,未考虑图像局部纹理的方向性的缺点,提出了一种基于图像局部方向特性的自适应全变分去噪模型(Adaptive directional total variation,ADTV),并推导出该模型的迭...针对全变分模型(total variation,TV)以图像的梯度信息作为去噪的尺度参数,未考虑图像局部纹理的方向性的缺点,提出了一种基于图像局部方向特性的自适应全变分去噪模型(Adaptive directional total variation,ADTV),并推导出该模型的迭代数值求解过程。在该模型中,首先,计算出图像局部方向的角度矩阵。然后,构造与图像纹理方向一致的椭圆区域代替TV模型的圆形区域。最后,通过优化最小化算法迭代求解以获得去噪后图像。通过对比实验证明,本文提出的模型取得了更高的峰值信噪比,去噪过程中更好地增强了图像的细节信息。展开更多
基金Sponsored by Beijing Priority Laboratory Fund of China(SYS10070522)
文摘To solve the weapon network system optimization problem against small raid objects with low attitude,the concept of direction probability and a new evaluation index system are proposed.By calculating the whole damaging probability that changes with the defending angle,the efficiency of the whole weapon network system can be subtly described.With such method,we can avoid the inconformity of the description obtained from the traditional index systems.Three new indexes are also proposed,i.e.join index,overlap index and cover index,which help manage the relationship among several sub-weapon-networks.By normalizing the computation results with the Sigmoid function,the matching problem between the optimization algorithm and indexes is well settled.Also,the algorithm of improved marriage in honey bees optimization that proposed in our previous work is applied to optimize the embattlement problem.Simulation is carried out to show the efficiency of the proposed indexes and the optimization algorithm.
基金supported partly by the National Science and Technology Major Project of China(Grant No.2016ZX05025-001006)Major Science and Technology Project of CNPC(Grant No.ZD2019-183-007)
文摘Well production optimization is a complex and time-consuming task in the oilfield development.The combination of reservoir numerical simulator with optimization algorithms is usually used to optimize well production.This method spends most of computing time in objective function evaluation by reservoir numerical simulator which limits its optimization efficiency.To improve optimization efficiency,a well production optimization method using streamline features-based objective function and Bayesian adaptive direct search optimization(BADS)algorithm is established.This new objective function,which represents the water flooding potential,is extracted from streamline features.It only needs to call the streamline simulator to run one time step,instead of calling the simulator to calculate the target value at the end of development,which greatly reduces the running time of the simulator.Then the well production optimization model is established and solved by the BADS algorithm.The feasibility of the new objective function and the efficiency of this optimization method are verified by three examples.Results demonstrate that the new objective function is positively correlated with the cumulative oil production.And the BADS algorithm is superior to other common algorithms in convergence speed,solution stability and optimization accuracy.Besides,this method can significantly accelerate the speed of well production optimization process compared with the objective function calculated by other conventional methods.It can provide a more effective basis for determining the optimal well production for actual oilfield development.
基金Supported by National Natural Science Foundation of China(Grant Nos.52105035,62203094)Special Central Funds for Guiding Local Scientific and Technological Development(Grant No.236Z1801G)+2 种基金Higher Education Youth Top Talent Project of Hebei Province of China(Grant No.BJK2024042)Natural Science Foundation of Hebei Province of China(Grant Nos.E2021203109,F2023501021)Graduate Student Innovation Capability Training and Support Project of Hebei Province(Grant No.CXZZBS2024053).
文摘The growing demand for deployable phased-array antennas in space applications requires innovative solutions to optimize the folded configurations and reduce the computational complexity.Existing methods face limitations due to the low efficiency of traditional algorithms and the lack of effective constraint strategies,resulting in excessive solution spaces.This study proposes forward shannon entropy wave function collapse(FSE-WFC),a novel method for designing panel configurations of one-dimensional deployable phased-array antennas using the wave function collapse algorithm.This addresses two key challenges:the excessive number of panel layout options and high computational costs.First,it analyzes the relationship between the panel connection positions and the folded form to impose constraints on the panel combinations.It then calculates the information entropy of the potential configurations to identify low-entropy solutions,thereby narrowing the solution space.Finally,boundary constraints and interference check were applied to refine the results.This approach significantly reduced the calculation time while improving the folding state and envelope volume of the antenna.The results show that the FSE-WFC algorithm reduces the envelope area by 18.3%for a 350 mm high satellite and 9.0%for a 600 mm high satellite,while satisfying the connectivity constraints.As the first application of the wave-function collapse algorithm to antenna folding design,this study introduces an information entropy-based constraint generation method that provides an efficient solution for deployable antenna optimization.
文摘Recently,genetic algorithms(GAs) have been applied to multi-modal dynamic optimization(MDO).In this kind of optimization,an algorithm is required not only to find the multiple optimal solutions but also to locate a dynamically changing optimum.Our fuzzy genetic sharing(FGS) approach is based on a novel genetic algorithm with dynamic niche sharing(GADNS).FGS finds the optimal solutions,while maintaining the diversity of the population.For this,FGS uses several strategies.First,an unsupervised fuzzy clustering method is used to track multiple optima and perform GADNS.Second,a modified tournament selection is used to control selection pressure.Third,a novel mutation with an adaptive mutation rate is used to locate unexplored search areas.The effectiveness of FGS in dynamic environments is demonstrated using the generalized dynamic benchmark generator(GDBG).
基金The Graduate Students Innovate Scientific Research Program (YJSCX2008-158HLJ) of Heilongjiang Provincesupported by the Distinguished Young Scholar Foundation (JC200707) of Heilongjiang Province of China
文摘In this paper, we establish a second-order sufficient condition for constrained optimization problems of a class of so called t-stable functions in terms of the first-order and the second-order Dini type directional derivatives. The result extends the corresponding result of [D. Bednarik and K. Pastor, Math. Program. Ser. A, 113（2008）, 283-298] to constrained optimization problems.
文摘针对大跨度斜拉桥的索力优化问题,该文基于径向基神经网络(Radial Basis Function Neural Network,RBFNN)拟合响应面,提出了一种考虑斜拉索可靠度指标的索力优化方法。通过RBFNN训练拟合结构隐式功能函数,建立求解可靠度指标的RBFNN响应面模型,采用改进粒子群算法对考虑可靠度指标的索力优化模型进行寻优求解。研究结果表明:RBFNN可以精确预测结构响应并拟合结构隐式功能函数,20个测试集的平均拟合误差仅为3.25%;改进粒子群算法对索力优化问题具有良好的适应性。相较于标准粒子群算法,改进后的算法收敛精度更高,收敛速度更快,优化后整体索力分布趋势与原索力分布趋势大致相同,采用优化索力计算得到的跨中位置斜拉索可靠度指标明显提升,各斜拉索平均可靠度增幅达3%左右,主梁线形得到大幅改善,最大挠度降幅高达36%。
基金supported by the National Natural Science Foundation of China(No.61505160)the Innovation Capability Support Program of Shaanxi(No.2018KJXX-042)+2 种基金the Natural Science Basic Research Program of Shaanxi(No.2019JM-084)the State Key Laboratory of Transient Optics and Photonics(No.SKLST202108)the Graduate Innovation and Practical Ability Training Project of Xi’an Shiyou University(No.YCS22213190)。
文摘We proposed and demonstrated the ultra-compact 1310/1550 nm wavelength multiplexer/demultiplexer assisted by subwavelength grating(SWG)using particle swarm optimization(PSO)algorithm in silicon-on-insulator(SOI)platform.Through the self-imaging effect of multimode interference(MMI)coupler,the demultiplexing function for 1310 nm and 1550 nm wavelengths is implemented.After that,three parallel SWG-based slots are inserted into the MMI section so that the effective refractive index of the modes can be engineered and thus the beat length can be adjusted.Importantly,these three SWG slots significantly reduce the length of the device,which is much shorter than the length of traditional MMI-based wavelength demultiplexers.Ultimately,by using the PSO algorithm,the equivalent refractive index and width of the SWG in a certain range are optimized to achieve the best performance of the wavelength demultiplexer.It has been verified that the device footprint is only 2×30.68μm^(2),and 1 dB bandwidths of larger than 120 nm are acquired at 1310 nm and 1550 nm wavelengths.Meanwhile,the transmitted spectrum shows that the insertion loss(IL)values are below 0.47 dB at both wavelengths when the extinction ratio(ER)values are above 12.65 dB.This inverse design approach has been proved to be efficient in increasing bandwidth and reducing device length.
文摘针对全变分模型(total variation,TV)以图像的梯度信息作为去噪的尺度参数,未考虑图像局部纹理的方向性的缺点,提出了一种基于图像局部方向特性的自适应全变分去噪模型(Adaptive directional total variation,ADTV),并推导出该模型的迭代数值求解过程。在该模型中,首先,计算出图像局部方向的角度矩阵。然后,构造与图像纹理方向一致的椭圆区域代替TV模型的圆形区域。最后,通过优化最小化算法迭代求解以获得去噪后图像。通过对比实验证明,本文提出的模型取得了更高的峰值信噪比,去噪过程中更好地增强了图像的细节信息。
