Reduced Q-matrix （Qr matrix） plays an important role in the rule space model （RSM） and the attribute hierarchy method （AHM）. Based on the attribute hierarchy, a valid/invalid item is defined. The judgment method...Reduced Q-matrix （Qr matrix） plays an important role in the rule space model （RSM） and the attribute hierarchy method （AHM）. Based on the attribute hierarchy, a valid/invalid item is defined. The judgment method of the valid/invalid item is developed on the relation between reachability matrix and valid items. And valid items are explained from the perspective of graph theory. An incremental augment algorithm for constructing Qr matrix is proposed based on the idea of incremental forward regression, and its validity is theoretically considered. Results of empirical tests are given in order to compare the performance of the incremental augment algo-rithm and the Tatsuoka algorithm upon the running time. Empirical evidence shows that the algorithm outper-forms the Tatsuoka algorithm, and the analysis of the two algorithms also show linear growth with respect to the number of valid items. Mathematical models with 10 attributes are built for the two algorithms by the linear regression analysis.展开更多
The purpose of the Combined Economic Emission Dispatch(CEED)of electric power is to offer the most exceptional schedule for production units,which must run with both low fuel costs and emission levels concurrently,the...The purpose of the Combined Economic Emission Dispatch(CEED)of electric power is to offer the most exceptional schedule for production units,which must run with both low fuel costs and emission levels concurrently,thereby meeting the lack of system equality and inequality constraints.Economic and emissions dispatching has become a primary and significant concern in power system networks.Consequences of using non-renewable fuels as input to exhaust power systems with toxic gas emissions and depleted resources for future generations.The optimal power allocation to generators serves as a solution to this problem.Emission dispatch reduces emissions while ignoring economic considerations.A collective strategy known as Combined Economic and Emission Dispatch is utilized to resolve the above-mentioned problems and investigate the trade-off relationship between fuel cost and emissions.Consequently,this work manages the Substantial Augmented Transformative Algorithm(SATA)to take care of the Combined Economic Emission Dispatch Problem(CEEDP)of warm units while fulfilling imperatives,for example,confines on generator limit,diminish the fuel cost,lessen the emission and decrease the force misfortune.SATA is a stochastic streamlining process that relies upon the development and knowledge of swarms.The goal is to minimize the total fuel cost of fossil-based thermal power generation units that generate and cause environmental pollution.The algorithm searches for solutions in the search space from the smallest to the largest in the case of forwarding search.The simulation of the proposed system is developed using MATLAB Simulink software.Simulation results show the effectiveness and practicability of this method in terms of economic and emission dispatching issues.The performance of the proposed system is compared with existing Artificial Bee Colony-Particle Swarm Optimization(ABC-PSO),Simulated Annealing(SA),and Differential Evolution(DE)methods.The fuel cost and gas emission of the proposed system are 128904$/hr and 138094.4652$/hr.展开更多
To realize automatic modeling and dynamic simulation of the educational assembling-type robot with open structure, a general dynamic model for the educational assembling-type robot and a fast simulation algorithm are ...To realize automatic modeling and dynamic simulation of the educational assembling-type robot with open structure, a general dynamic model for the educational assembling-type robot and a fast simulation algorithm are put forward. First, the educational robot system is abstracted to a multibody system and a general dynamic model of the educational robot is constructed by the Newton-Euler method. Then the dynamic model is simplified by a combination of components with fixed connections according to the structural characteristics of the educational robot. Secondly, in order to obtain a high efficiency simulation algorithm, based on the sparse matrix technique, the augmentation algorithm and the direct projective constraint stabilization algorithm are improved. Finally, a numerical example is given. The results show that the model and the fast algorithm are valid and effective. This study lays a dynamic foundation for realizing the simulation platform of the educational robot.展开更多
检索增强生成(retrieval-augmented generation,RAG)技术因具有为大语言模型(large language model,LLM)提供模型外知识的能力而受到人们的关注,然而绝大多数方法都难以同时兼顾局部的细节知识和原文中不连续的多跳知识。针对上述问题,...检索增强生成(retrieval-augmented generation,RAG)技术因具有为大语言模型(large language model,LLM)提供模型外知识的能力而受到人们的关注,然而绝大多数方法都难以同时兼顾局部的细节知识和原文中不连续的多跳知识。针对上述问题,提出基于聚类重组和预解析的检索增强生成方法。在索引阶段,首先通过聚类算法将不连续的相关知识组合成新分块,以提高多跳知识的检索能力;然后基于提示工程对各知识分块进行预解析生成更细粒度的新分块,以提高检索阶段的召回率。在检索阶段,将召回的所有新分块还原为原文分块,并连同查询语句输入给大语言模型以得到最终答案。在数据集QuALITY上对所提出的方法进行了评估,通过消融实验和开源基线对比实验验证了方法的有效性,并在公开的评测排行榜上取得了最佳效果。本文分析结果可为RAG的索引和检索技术提供参考。展开更多
针对现有图像水印检测算法计算效率低、参数量大且真伪判别准确性不足等问题,提出了一种基于改进生成对抗网络(GAN)的图像水印检测算法。该算法包括DSD-GAN和DCG-GAN两个模型,分别用于水印存在性检测和水印真伪判别。DSD-GAN模型通过引...针对现有图像水印检测算法计算效率低、参数量大且真伪判别准确性不足等问题,提出了一种基于改进生成对抗网络(GAN)的图像水印检测算法。该算法包括DSD-GAN和DCG-GAN两个模型,分别用于水印存在性检测和水印真伪判别。DSD-GAN模型通过引入深度可分离卷积和空洞卷积优化判别器,有效降低了模型的参数量,并提升了计算效率,显著提高了水印存在性检测的速度与精度。DCG-GAN模型则结合生成器生成高质量的伪造水印,并通过灰狼优化算法(Grey Wolf Optimization,GWO)优化判别器参数,进一步提升了水印真伪判别的准确性。两个模型的协同工作流程使得水印存在性检测与真伪判别得以高效实现。实验结果表明:DSD-GAN模型在确保水印不可见性和鲁棒性的同时,在水印存在性检测任务中取得了99.58%的准确率,具有优异的检测性能;DCG-GAN模型在水印真伪判别任务中,PSNR和NC指标表现优秀,且在不同嵌入强度下的准确率始终高于0.50,保障了水印的不可见性与鲁棒性。与现有算法相比,该方案在显著降低参数量的同时提升了运行效率,为复杂场景下的图像水印检测提供了一种高效可行的解决方案。展开更多
The guidance and control for UAV aerial refueling docking based on dynamic inversion with L1 adaptive augmentation is studied.In order to improve the tracking performance of UAV aerial refueling docking,aguidance algo...The guidance and control for UAV aerial refueling docking based on dynamic inversion with L1 adaptive augmentation is studied.In order to improve the tracking performance of UAV aerial refueling docking,aguidance algorithm is developed to satisfy the tracking requirement of position and velocity,and it generates the UAV flight control loop commands.In flight control loop,based on the 6-DOF nonlinear model,the angular rate loop and the attitude loop are separated based on time-scale principle and the control law is designed using dynamic inversion.The throttle control is also derived from dynamic inversion method.Moreover,an L1 adaptive augmentation is developed to compensate for the undesirable effects of modeling uncertainty and disturbance.Nonlinear digital simulations are carried out.The results show that the guidance and control system has good tracking performance and robustness in achieving accurate aerial refueling docking.展开更多
Nonlinear errors always exist in data obtained from tracker in augmented reality （AR）, which badly influence the effect of AR. This paper proposes to rectify the errors using BP neural network. As BP neural network ...Nonlinear errors always exist in data obtained from tracker in augmented reality （AR）, which badly influence the effect of AR. This paper proposes to rectify the errors using BP neural network. As BP neural network is prone to getting into local extrema and convergence is slow, genetic algorithm is employed to optimize the initial weights and threshold of neural network. This paper discusses how to set the crucial parameters in the algorithm. Experimental results show that the method ensures that the neural network achieves global convergence quickly and correctly. Tracking precision of AR system is improved after the tracker is rectified, and the third dimension of AR system is enhanced.展开更多
develop a mentation This paper considers the priority facility primal-dual 3-approximation algorithm for procedure, the authors further improve the location problem with penalties： The authors this problem. Combining...develop a mentation This paper considers the priority facility primal-dual 3-approximation algorithm for procedure, the authors further improve the location problem with penalties： The authors this problem. Combining with the greedy aug- previous ratio 3 to 1.8526.展开更多
In this paper, a new augmented Lagrangian penalty function for constrained optimization problems is studied. The dual properties of the augmented Lagrangian objective penalty function for constrained optimization prob...In this paper, a new augmented Lagrangian penalty function for constrained optimization problems is studied. The dual properties of the augmented Lagrangian objective penalty function for constrained optimization problems are proved. Under some conditions, the saddle point of the augmented Lagrangian objective penalty function satisfies the first-order Karush-Kuhn-Tucker (KKT) condition. Especially, when the KKT condition holds for convex programming its saddle point exists. Based on the augmented Lagrangian objective penalty function, an algorithm is developed for finding a global solution to an inequality constrained optimization problem and its global convergence is also proved under some conditions.展开更多
The standalone Global Positioning System (GPS) does not meet the higher accuracy requirements needed for approach and landing phase of an aircraft. To meet the Category-I Precision Approach (CAT-I PA) requirements of ...The standalone Global Positioning System (GPS) does not meet the higher accuracy requirements needed for approach and landing phase of an aircraft. To meet the Category-I Precision Approach (CAT-I PA) requirements of civil aviation, satellite based augmentation system (SBAS) has been planned by various countries including USA, Europe, Japan and India. The Indian SBAS is named as GPS Aided Geo Augmented Navigation (GAGAN). The GAGAN network consists of several dual frequency GPS receivers located at various airports around the Indian subcontinent. The ionospheric delay, which is a function of the total electron content (TEC), is one of the main sources of error affecting GPS/SBAS accuracy. A dual frequency GPS receiver can be used to estimate the TEC. However, line-of-sight TEC derived from dual frequency GPS data is corrupted by the instrumental biases of the GPS receiver and satellites. The estimation of receiver instrumental bias is particularly important for obtaining accurate estimates of ionospheric delay. In this paper, two prominent techniques based on Kalman filter and Self-Calibration Of pseudo Range Error (SCORE) algorithm are used for estimation of instrumental biases. The estimated instrumental bias and TEC results for the GPS Aided Geo Augmented Navigation (GAGAN) station at Hyderabad (78.47°E, 17.45°N), India are presented.展开更多
基金Supported by the National Natural Science Foundation of China (30860084,60673014,60263005)the Backbone Young Teachers Foundation of Fujian Normal University(2008100244)the Department of Education Foundation of Fujian Province (ZA09047)~~
文摘Reduced Q-matrix （Qr matrix） plays an important role in the rule space model （RSM） and the attribute hierarchy method （AHM）. Based on the attribute hierarchy, a valid/invalid item is defined. The judgment method of the valid/invalid item is developed on the relation between reachability matrix and valid items. And valid items are explained from the perspective of graph theory. An incremental augment algorithm for constructing Qr matrix is proposed based on the idea of incremental forward regression, and its validity is theoretically considered. Results of empirical tests are given in order to compare the performance of the incremental augment algo-rithm and the Tatsuoka algorithm upon the running time. Empirical evidence shows that the algorithm outper-forms the Tatsuoka algorithm, and the analysis of the two algorithms also show linear growth with respect to the number of valid items. Mathematical models with 10 attributes are built for the two algorithms by the linear regression analysis.
文摘The purpose of the Combined Economic Emission Dispatch(CEED)of electric power is to offer the most exceptional schedule for production units,which must run with both low fuel costs and emission levels concurrently,thereby meeting the lack of system equality and inequality constraints.Economic and emissions dispatching has become a primary and significant concern in power system networks.Consequences of using non-renewable fuels as input to exhaust power systems with toxic gas emissions and depleted resources for future generations.The optimal power allocation to generators serves as a solution to this problem.Emission dispatch reduces emissions while ignoring economic considerations.A collective strategy known as Combined Economic and Emission Dispatch is utilized to resolve the above-mentioned problems and investigate the trade-off relationship between fuel cost and emissions.Consequently,this work manages the Substantial Augmented Transformative Algorithm(SATA)to take care of the Combined Economic Emission Dispatch Problem(CEEDP)of warm units while fulfilling imperatives,for example,confines on generator limit,diminish the fuel cost,lessen the emission and decrease the force misfortune.SATA is a stochastic streamlining process that relies upon the development and knowledge of swarms.The goal is to minimize the total fuel cost of fossil-based thermal power generation units that generate and cause environmental pollution.The algorithm searches for solutions in the search space from the smallest to the largest in the case of forwarding search.The simulation of the proposed system is developed using MATLAB Simulink software.Simulation results show the effectiveness and practicability of this method in terms of economic and emission dispatching issues.The performance of the proposed system is compared with existing Artificial Bee Colony-Particle Swarm Optimization(ABC-PSO),Simulated Annealing(SA),and Differential Evolution(DE)methods.The fuel cost and gas emission of the proposed system are 128904$/hr and 138094.4652$/hr.
基金Hexa-Type Elites Peak Program of Jiangsu Province(No.2008144)Qing Lan Project of Jiangsu ProvinceFund for Excellent Young Teachers of Southeast University
文摘To realize automatic modeling and dynamic simulation of the educational assembling-type robot with open structure, a general dynamic model for the educational assembling-type robot and a fast simulation algorithm are put forward. First, the educational robot system is abstracted to a multibody system and a general dynamic model of the educational robot is constructed by the Newton-Euler method. Then the dynamic model is simplified by a combination of components with fixed connections according to the structural characteristics of the educational robot. Secondly, in order to obtain a high efficiency simulation algorithm, based on the sparse matrix technique, the augmentation algorithm and the direct projective constraint stabilization algorithm are improved. Finally, a numerical example is given. The results show that the model and the fast algorithm are valid and effective. This study lays a dynamic foundation for realizing the simulation platform of the educational robot.
文摘检索增强生成(retrieval-augmented generation,RAG)技术因具有为大语言模型(large language model,LLM)提供模型外知识的能力而受到人们的关注,然而绝大多数方法都难以同时兼顾局部的细节知识和原文中不连续的多跳知识。针对上述问题,提出基于聚类重组和预解析的检索增强生成方法。在索引阶段,首先通过聚类算法将不连续的相关知识组合成新分块,以提高多跳知识的检索能力;然后基于提示工程对各知识分块进行预解析生成更细粒度的新分块,以提高检索阶段的召回率。在检索阶段,将召回的所有新分块还原为原文分块,并连同查询语句输入给大语言模型以得到最终答案。在数据集QuALITY上对所提出的方法进行了评估,通过消融实验和开源基线对比实验验证了方法的有效性,并在公开的评测排行榜上取得了最佳效果。本文分析结果可为RAG的索引和检索技术提供参考。
文摘针对现有图像水印检测算法计算效率低、参数量大且真伪判别准确性不足等问题,提出了一种基于改进生成对抗网络(GAN)的图像水印检测算法。该算法包括DSD-GAN和DCG-GAN两个模型,分别用于水印存在性检测和水印真伪判别。DSD-GAN模型通过引入深度可分离卷积和空洞卷积优化判别器,有效降低了模型的参数量,并提升了计算效率,显著提高了水印存在性检测的速度与精度。DCG-GAN模型则结合生成器生成高质量的伪造水印,并通过灰狼优化算法(Grey Wolf Optimization,GWO)优化判别器参数,进一步提升了水印真伪判别的准确性。两个模型的协同工作流程使得水印存在性检测与真伪判别得以高效实现。实验结果表明:DSD-GAN模型在确保水印不可见性和鲁棒性的同时,在水印存在性检测任务中取得了99.58%的准确率,具有优异的检测性能;DCG-GAN模型在水印真伪判别任务中,PSNR和NC指标表现优秀,且在不同嵌入强度下的准确率始终高于0.50,保障了水印的不可见性与鲁棒性。与现有算法相比,该方案在显著降低参数量的同时提升了运行效率,为复杂场景下的图像水印检测提供了一种高效可行的解决方案。
基金supported by the National Natural Science Foundation of China(No.61273050)the Aeronautical Science Foundation of China(No.20121352026)
文摘The guidance and control for UAV aerial refueling docking based on dynamic inversion with L1 adaptive augmentation is studied.In order to improve the tracking performance of UAV aerial refueling docking,aguidance algorithm is developed to satisfy the tracking requirement of position and velocity,and it generates the UAV flight control loop commands.In flight control loop,based on the 6-DOF nonlinear model,the angular rate loop and the attitude loop are separated based on time-scale principle and the control law is designed using dynamic inversion.The throttle control is also derived from dynamic inversion method.Moreover,an L1 adaptive augmentation is developed to compensate for the undesirable effects of modeling uncertainty and disturbance.Nonlinear digital simulations are carried out.The results show that the guidance and control system has good tracking performance and robustness in achieving accurate aerial refueling docking.
基金Project supported by Science Foundation of Shanghai Municipal Commission of Science and Technology (Grant No .025115008)
文摘Nonlinear errors always exist in data obtained from tracker in augmented reality （AR）, which badly influence the effect of AR. This paper proposes to rectify the errors using BP neural network. As BP neural network is prone to getting into local extrema and convergence is slow, genetic algorithm is employed to optimize the initial weights and threshold of neural network. This paper discusses how to set the crucial parameters in the algorithm. Experimental results show that the method ensures that the neural network achieves global convergence quickly and correctly. Tracking precision of AR system is improved after the tracker is rectified, and the third dimension of AR system is enhanced.
基金supported by the National Natural Science Foundation of China under Grant No.11371001
文摘develop a mentation This paper considers the priority facility primal-dual 3-approximation algorithm for procedure, the authors further improve the location problem with penalties： The authors this problem. Combining with the greedy aug- previous ratio 3 to 1.8526.
文摘In this paper, a new augmented Lagrangian penalty function for constrained optimization problems is studied. The dual properties of the augmented Lagrangian objective penalty function for constrained optimization problems are proved. Under some conditions, the saddle point of the augmented Lagrangian objective penalty function satisfies the first-order Karush-Kuhn-Tucker (KKT) condition. Especially, when the KKT condition holds for convex programming its saddle point exists. Based on the augmented Lagrangian objective penalty function, an algorithm is developed for finding a global solution to an inequality constrained optimization problem and its global convergence is also proved under some conditions.
文摘The standalone Global Positioning System (GPS) does not meet the higher accuracy requirements needed for approach and landing phase of an aircraft. To meet the Category-I Precision Approach (CAT-I PA) requirements of civil aviation, satellite based augmentation system (SBAS) has been planned by various countries including USA, Europe, Japan and India. The Indian SBAS is named as GPS Aided Geo Augmented Navigation (GAGAN). The GAGAN network consists of several dual frequency GPS receivers located at various airports around the Indian subcontinent. The ionospheric delay, which is a function of the total electron content (TEC), is one of the main sources of error affecting GPS/SBAS accuracy. A dual frequency GPS receiver can be used to estimate the TEC. However, line-of-sight TEC derived from dual frequency GPS data is corrupted by the instrumental biases of the GPS receiver and satellites. The estimation of receiver instrumental bias is particularly important for obtaining accurate estimates of ionospheric delay. In this paper, two prominent techniques based on Kalman filter and Self-Calibration Of pseudo Range Error (SCORE) algorithm are used for estimation of instrumental biases. The estimated instrumental bias and TEC results for the GPS Aided Geo Augmented Navigation (GAGAN) station at Hyderabad (78.47°E, 17.45°N), India are presented.
