adaptive

摘要： 在游戏玩家的推动下,人们开始对显示器的刷新率有了更多要求,市场上出现了很多144Hz乃至更高刷新率的显示器产品,为了解决高刷新率可能导致的游戏、视频画面撕裂等问题,各厂商也推出了自身的各种可变刷新率的同步技术。不过,这些产品在标准上并不统一,比如英伟达G-Sync,AMDFreeSync,VESA Adaptive Sync,三家的标准就存在一些互相不兼容的问题。2022年5月,VESA发布了全新的Adaptive Sync和Media Sync标准,希望为显示器的刷新率同步以及游戏玩家关注的高刷新率问题引入全新、系统的标准,解决市场上的混乱情况。

摘要： The surrogate model technology has a good performance in solving black-box optimization problems,which is widely used in multi-domain engineering optimization problems.The adaptive surrogate model is the mainstream research direction of surrogate model technology,which can realize model fitting and global optimization of engineering problems by infilling criteria.Based on the idea of the adaptive surrogate model,this paper proposes an efficient global optimization algorithm based on the local remodeling method(EGO-LR),which aims at improving the accuracy and optimization efficiency of the model.The proposed algorithm firstly constructs the expectation improvement(EI)function in the local area and optimizes it to get the update points.Secondly,the obtained update points are added to the global region until the global accuracy of the model meets the requirements.Then the differential evolution algorithm is used for global optimization.Sixteen benchmark functions are used to compare the EGO-LR algorithm with the existing algorithms.The results show that the EGO-LR algorithm can quickly converge to the accuracy requirements of the model and find the optimal value efficiently when facing complex problems with many local extrema and large variable spaces.The proposed algorithm is applied to the optimization design of the structural parameter of the impeller,and the outflow field analysis of the impeller is realized through finite element analysis.The optimization with the maximum fluid pressure(MP value)of the impeller as the objective function is completed,which effectively reduces the pressure value of the impeller under load.

摘要： This paper investigates the navigational performance of Global Positioning System(GPS)using the variational Bayesian(VB)based robust filter with interacting multiple model(IMM)adaptation as the navigation processor.The performance of the state estimation for GPS navigation processing using the family ofKalman filter(KF)may be degraded due to the fact that in practical situations the statistics of measurement noise might change.In the proposed algorithm,the adaptivity is achieved by estimating the timevarying noise covariance matrices based onVB learning using the probabilistic approach,where in each update step,both the system state and time-varying measurement noise were recognized as random variables to be estimated.The estimation is iterated recursively at each time to approximate the real joint posterior distribution of state using the VB learning.One of the two major classical adaptive Kalman filter(AKF)approaches that have been proposed for tuning the noise covariance matrices is the multiple model adaptive estimate(MMAE).The IMM algorithm uses two or more filters to process in parallel,where each filter corresponds to a different dynamic or measurement model.The robust Huber’s M-estimation-based extended Kalman filter(HEKF)algorithm integrates both merits of the Huber M-estimation methodology and EKF.The robustness is enhanced by modifying the filter update based on Huber’s M-estimation method in the filtering framework.The proposed algorithm,referred to as the interactive multi-model based variational Bayesian HEKF(IMM-VBHEKF),provides an effective way for effectively handling the errors with time-varying and outlying property of non-Gaussian interference errors,such as the multipath effect.Illustrative examples are given to demonstrate the navigation performance enhancement in terms of adaptivity and robustness at the expense of acceptable additional execution time.

摘要： 基于AP(Adaptive)AUTOSAR的方法论和诊断架构,二次开发了基于MDC300F平台的矿车自动驾驶诊断系统。利用MCDTool对二次开发的诊断功能进行了远程DoIP诊断测试,成功验证了矿车自动驾驶的诊断功能。

摘要： In recent years,Delay Tolerant Networks(DTN)have received more and more attention.At the same time,several existing DTN routing algorithms generally have disadvantages such as poor scalability and inability to perceive changes in the network environment.This paper proposes an AdaptiveSpray routing algorithm.The algorithm can dynamically control the initial maximum message copy number according to the cache occupancy rate of the node itself,and the cache occupancy rate is added as an impact factor to the calculation of the probability of each node meeting the destination node.In the forwarding phase,the node will first compare the meeting probability of itself and the meeting node to the destination node,and then choose different forwarding strategies.The simulation shows that the AdaptiveSpray algorithm proposed in this paper has obvious advantages compared with the existing routing algorithms in terms of message delivery rate and average delay.

摘要： Background In the smoothed particle hydrodynamics(SPH)fluid simulation method,the smoothing length affects not only the process of neighbor search but also the calculation accuracy of the pressure solver.Therefore,it plays a crucial role in ensuring the accuracy and stability of SPH.Methods In this study,an adaptive SPH fluid simulation method with a variable smoothing length is designed.In this method,the smoothing length is adaptively adjusted according to the ratio of the particle density to the weighted average of the density of the neighboring particles.Additionally,a neighbor search scheme and kernel function scheme are designed to solve the asymmetry problems caused by the variable smoothing length.Results The simulation efficiency of the proposed algorithm is comparable to that of some classical methods,and the variance of the number of neighboring particles is reduced.Thus,the visual effect is more similar to the corresponding physical reality.Conclusions The precision of the interpolation calculation performed in the SPH algorithm is improved using the adaptive-smoothing length scheme;thus,the stability of the algorithm is enhanced,and a larger timestep is possible.

摘要： 阿科玛领投了Adaptive3D的B轮投资,Adaptive3D是一家创新公司,也是优质的增材制造光聚合物树脂供应商。这项投资补充了阿科玛在UV液体树脂材料设计方面的专业知识和加速3D打印制造技术发展的承诺。

摘要： Combining the advantages of numerical simulation with experimental testing,real-time dynamic substructure(RTDS)testing provides a new experimental method for the investigation of engineered structures.However,not all unmodeled parts can be physically tested,as testing is often limited by the capacity of the test facility.Model updating is a good option to improve the modeling accuracy for numerical substructures in RTDS.In this study,a model updating method is introduced,which has great performance in describing this nonlinearity.In order to determine the optimal parameters in this model,an Unscented Kalman Filter(UKF)-based algorithm was applied to extract the knowledge contained in the sensors data.All the parameters that need to be identified are listed as the extended state variables,and the identification was achieved via the step-by-step state prediction and state update process.Effectiveness of the proposed method was verified through a group of experimental data,and results showed good agreement.Furthermore,the proposed method was compared with the Extended Kalman Filter(EKF)-based method,and better accuracy was easily found.The proposed parameter identification method has great applicability for structural objects with nonlinear behaviors and could be extended to research in other engineering fields.

摘要： In recent years, variable selection based on penalty likelihood methods has aroused great concern. Based on the Gibbs sampling algorithm of asymmetric Laplace distribution, this paper considers the quantile regression with adaptive Lasso and Lasso penalty from a Bayesian point of view. Under the non-Bayesian and Bayesian framework, several regularization quantile regression methods are systematically compared for error terms with different distributions and heteroscedasticity. Under the error term of asymmetric Laplace distribution, statistical simulation results show that the Bayesian regularized quantile regression is superior to other distributions in all quantiles. And based on the asymmetric Laplace distribution, the Bayesian regularized quantile regression approach performs better than the non-Bayesian approach in parameter estimation and prediction. Through real data analyses, we also confirm the above conclusions.

摘要： To deal with the problem that the initial velocity of the bullet is difficult to increase,the research on the super-high initial velocity propulsion in the barrel weapon with an adaptive pressure-maintaining chamber are conducted.Considering the law of gun-powder burning and the flow characteristics of gun-powder gas in multi-chamber,the scheme of super-high initial velocity propulsion with an adaptive pressure-maintaining chamber is designed,the ballistic model of the barrel weapon with super-high velocity bullet propulsion is established.The research results show that the technical scheme can greatly increase the initial velocity of the bullet with the peak pressure keeping nearly the same as the tradition barrel weapon.The research results can provide a theoretical foundation to significantly increase the initial velocity in barrel weapons using solid propellants,and have an important reference value to comprehensively increase the power of the barrel weapons.

摘要： The design of a driving control system for high-speed telescopic boom lift truck was presented inthis paper. The PID controller was used to control the speed of the vehicle. A predictive filter was designed onthe basis of theory of the adaptive filter, which was used to predicate the system pressure difference of the vehide in the target status. The driving control system realized the combine-control of engine and variablepump, enhanced the controllability of vehicle, and optimized the working condition of engine.

摘要： This paper proposes a neuron-based adaptive PID algorithm for the gas collector's pressure control ofcoke oven. The parameters of PID controller can be adjusted by on-line learning. The numerical simulation resultswith Matlab/Simulink are shown the novel algorithm is effective. Compared with conventional PID, the proposedmethod is more robust. The neuron-based adaptive PID algorithm has been successfully applied to control the gascollector in coke oven. The algorithm can improve the disturbance rejection robust of the gas collector controlsystem, and obtain good control performance under the industrial environment.

摘要： 本发明公开了一种Adaptive AUTOSAR平台参数的标定方法及系统，该方法包括：开发一个用于与标定工具通信的程序，运行于需要标定的设备上；标定工具将标定数据传输给该程序，该程序将标定数据以一种特定的格式文件存储在内存当中；对于参数需要标定的Adaptive Application，启动时会将需要标定的数据从该种特定的格式文件中读取到Adaptive Application中，并赋值给指定的变量，完成参数标定。本发明提出的Adaptive AUTOSAR的标定方案，不需要额外的增加硬件，也不需要使用Hypervisor技术运行Classic AUTOSAR，能够直接在Adaptive AUTOSAR架构中实现，简化开发工作和成本。

摘要： 本发明提供一种基于AUTOSARAdaptive的服务调用链追踪方法、系统、计算机及存储介质，基于AUTOSARAdaptive的服务调用链追踪方法，调用链追踪工具生成包含唯一标识的调用链信息报文，将SOME/IP信息报文的信息添加至调用链信息报文中，发送调用链信息报文；调用链追踪工具将包含调用链信息的服务日志予以标识，生成第一服务日志；调用链追踪工具通过接收到的SOME/IP信息报文查找对应接收到的调用链信息报文，调用链追踪工具储存包含接收到的调用链信息报文的服务日志，形成第二服务日志；调用链追踪工具追踪第一服务日志及第二服务日志，建立服务调用的多叉树数据结构。通过采用上述方法，可以清晰明了的对故障进行相应问题节点的快送定位，更加方便的确定服务依赖关系。

摘要： 本实用新型公开了射频链路切换技术领域的一种用于Adaptivity和DFS测试的新型射频链路切换装置，包括Ant Port接口P1，所述Ant Port接口P1串接有3dB衰减器M1，所述3dB衰减器M1的另一端与射频同轴开关S1中的一个端口串接，所述射频同轴开关S1中的另两个端口分别并接有6dB功分器D1和6dB功分器D2，所述6dB功分器D1中的1号端口与射频同轴开关S3中的一个端口串接，所述6dB功分器D1中的2号端口串接有定向耦合器C2、10dB衰减器M5和6dB功分器D3，本实用新型整合了Adaptivity和DFS测试链路装置，通过同轴开关自动选择链路，使得测试环境搭建变得省时省力。