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拖拉机用柴油机主轴瓦技术分析 预览
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作者 单士睿 董晨煜 《农机化研究》 北大核心 2020年第8期260-263,268共5页
对拖拉机所用的某大功率高性能高速柴油机(以下简称“NY128柴油机”)在实际运行过程中出现的主轴瓦拉瓦故障进行了细致的技术分析,进而提出了解决该柴油机拉瓦严重故障的途径。通过提高柴油机关键零部件清洁度,优化部件及整机装配工艺,... 对拖拉机所用的某大功率高性能高速柴油机(以下简称“NY128柴油机”)在实际运行过程中出现的主轴瓦拉瓦故障进行了细致的技术分析,进而提出了解决该柴油机拉瓦严重故障的途径。通过提高柴油机关键零部件清洁度,优化部件及整机装配工艺,调整完善柴油机出厂试验等方面的优化处理,从而从根本上解决拖拉机用柴油机主轴承轴瓦拉瓦的严重问题。 展开更多
关键词 拖拉机 NY128柴油机 拉瓦 优化
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Heterogeneous Parallel Algorithm Design and Performance Optimization for WENO on the Sunway TaihuLight Supercomputer
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作者 Jianqiang Huang Wentao Han +1 位作者 Xiaoying Wang Wenguang Chen 《清华大学学报自然科学版(英文版)》 EI CAS CSCD 2020年第1期56-67,共12页
A Weighted Essentially Non-Oscillatory scheme(WENO) is a solution to hyperbolic conservation laws,suitable for solving high-density fluid interface instability with strong intermittency. These problems have a large an... A Weighted Essentially Non-Oscillatory scheme(WENO) is a solution to hyperbolic conservation laws,suitable for solving high-density fluid interface instability with strong intermittency. These problems have a large and complex flow structure. To fully utilize the computing power of High Performance Computing(HPC) systems, it is necessary to develop specific methodologies to optimize the performance of applications based on the particular system’s architecture. The Sunway TaihuLight supercomputer is currently ranked as the fastest supercomputer in the world. This article presents a heterogeneous parallel algorithm design and performance optimization of a high-order WENO on Sunway TaihuLight. We analyzed characteristics of kernel functions, and proposed an appropriate heterogeneous parallel model. We also figured out the best division strategy for computing tasks,and implemented the parallel algorithm on Sunway TaihuLight. By using access optimization, data dependency elimination, and vectorization optimization, our parallel algorithm can achieve up to 172× speedup on one single node, and additional 58× speedup on 64 nodes, with nearly linear scalability. 展开更多
关键词 parallel ALGORITHMS WEIGHTED Essentially Non-Oscillatory scheme(WENO) optimization MANY-CORE Sunway TaihuLight
偏心切割式苹果采摘装置设计与试验 预览
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作者 宋怀波 张阳 +1 位作者 黄俊华 石富磊 《农机化研究》 北大核心 2020年第5期94-99,共6页
苹果采摘是苹果生产作业中最耗时费力的环节,实现苹果快速采摘是现代化采摘作业的重要途径。本研究设计的偏心切割式苹果采摘装置主要由偏心式采摘头、可拆卸伸缩杆和缓冲下落通道3部分构成:偏心式采摘头采用刀片偏心旋转实现果柄的切割... 苹果采摘是苹果生产作业中最耗时费力的环节,实现苹果快速采摘是现代化采摘作业的重要途径。本研究设计的偏心切割式苹果采摘装置主要由偏心式采摘头、可拆卸伸缩杆和缓冲下落通道3部分构成:偏心式采摘头采用刀片偏心旋转实现果柄的切割;伸缩杆采用可拆卸设计,实现不同高度苹果的采摘;缓冲下落通道采用内置缓冲布条的布制通道构成,以防止苹果在跌落过程中的损伤。在西北农林科技大学北校区园艺场随机选择5棵苹果树进行了采摘性能田间采摘试验,共采摘苹果150个。试验结果表明:该装置的采摘成功率为92.00%,苹果采摘受损率平均为4.70%。该苹果采摘装置的设计与试验为其它同类型的水果采摘装置的设计与改进提供了参考,有利于提升辅助人工的水果采摘装备研发水平。 展开更多
关键词 苹果 采摘 偏心切割 优化 校核
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光滑双向渐进结构优化法拓扑优化连续体结构频率和动刚度 预览
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作者 滕晓艳 毛炳坤 江旭东 《农业工程学报》 EI CAS CSCD 北大核心 2019年第7期55-61,共7页
针对双向渐进结构优化(bi-directional evolutionary structural optimization,BESO)方法的单元过删除问题,提出了光滑双向渐进结构优化(smooth bi-directional evolutionary structural optimization,SBESO)方法,通过引入权重函数更新... 针对双向渐进结构优化(bi-directional evolutionary structural optimization,BESO)方法的单元过删除问题,提出了光滑双向渐进结构优化(smooth bi-directional evolutionary structural optimization,SBESO)方法,通过引入权重函数更新单元的质量与刚度矩阵,控制单元删除率以使低效单元逐渐从设计域中删除。以连续体结构固有频率最大化为目标,提出了一种基于SBESO的频率优化方法,对比分析了常函数、线性函数和正弦函数等不同权重函数对连续体结构优化的影响。将等效静载荷(equivalent static loads,ESL)方法与SBESO方法相融合,提出了动载荷作用下连续体结构的动刚度优化方法。数值算例表明,SBESO方法通过调节单元删除率和权重函数,控制低效单元在结构设计域中逐渐被删除,有效抑制了单元的过删除问题。采用线性和正弦权重函数,更有利于获得连续体结构的频率最优拓扑解。随单元删除率的减少,动刚度最优拓扑解的结构边界逐渐光滑,而且逼近于同一构形。由此,所提出的SBESO方法完善了BESO方法的优化准则,对于解决连续体结构动力学优化设计问题具有较为重要的理论意义。 展开更多
关键词 优化 模型 光滑双向渐进结构优化 频率优化 等效静载荷 动刚度优化
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Solving multi-scenario cardinality constrained optimization problems via multi-objective evolutionary algorithms
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作者 Xing ZHOU Huaimin WANG +2 位作者 Wei PENG Bo DING Rui WANG 《中国科学:信息科学(英文版)》 SCIE EI CSCD 2019年第9期73-90,共18页
Cardinality constrained optimization problems(CCOPs) are fixed-size subset selection problems with applications in several fields. CCOPs comprising multiple scenarios, such as cardinality values that form an interval,... Cardinality constrained optimization problems(CCOPs) are fixed-size subset selection problems with applications in several fields. CCOPs comprising multiple scenarios, such as cardinality values that form an interval, can be defined as multi-scenario CCOPs(MSCCOPs). An MSCCOP is expected to optimize the objective value of each cardinality to support decision-making processes. When the computation is conducted using traditional optimization algorithms, an MSCCOP often requires several passes(algorithmic runs) to obtain all the(near-)optima, where each pass handles a specific cardinality. Such separate passes abandon most of the knowledge(including the potential superior solution structures) learned in one pass that can also be used to improve the results of other passes. By considering this situation, we propose a generic transformation strategy that can be referred to as the Mucard strategy, which converts an MSCCOP into a low-dimensional multi-objective optimization problem(MOP) to simultaneously obtain all the(near-)optima of the MSCCOP in a single algorithmic run. In essence, the Mucard strategy combines separate passes that deal with distinct variable spaces into a single pass, enabling knowledge reuse and knowledge interchange of each cardinality among genetic individuals. The performance of the Mucard strategy was demonstrated using two typical MSCCOPs. For a given number of evolved individuals, the Mucard strategy improved the accuracy of the obtained solutions because of the in-process knowledge than that obtained by untransformed evolutionary algorithms, while reducing the average runtime. Furthermore, the equivalence between the optimal solutions of the transformed MOP and the untransformed MSCCOP can be theoretically proved. 展开更多
关键词 EVOLUTIONARY computation multi-objective OPTIMIZATION cardinality-constrained OPTIMIZATION PROBLEM multiple scenarios transformation P-MEDIAN PROBLEM PORTFOLIO OPTIMIZATION PROBLEM
Convergence Analysis of a New MaxMin-SOMO Algorithm
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作者 Atlas Khan Yan-Peng Qu Zheng-Xue Li 《国际自动化与计算杂志:英文版》 EI CSCD 2019年第4期534-542,共9页
The convergence analysis of MaxMin-SOMO algorithm is presented. The SOM-based optimization (SOMO) is an optimization algorithm based on the self-organizing map (SOM) in order to find a winner in the network. Generally... The convergence analysis of MaxMin-SOMO algorithm is presented. The SOM-based optimization (SOMO) is an optimization algorithm based on the self-organizing map (SOM) in order to find a winner in the network. Generally, through a competitive learning process, the SOMO algorithm searches for the minimum of an objective function. The MaxMin-SOMO algorithm is the generalization of SOMO with two winners for simultaneously finding two winning neurons i.e., first winner stands for minimum and second one for maximum of the objective function. In this paper, the convergence analysis of the MaxMin-SOMO is presented. More specifically, we prove that the distance between neurons decreases at each iteration and finally converge to zero. The work is verified with the experimental results. 展开更多
关键词 OPTIMIZATION self ORGANIZING map (SOM) SOM-based OPTIMIZATION (SOMO) ALGORITHM particle swarm OPTIMIZATION (PSO) genetic algorithms (GAs)
DESCENT DIRECTION STOCHASTIC APPROXIMATION ALGORITHM WITH ADAPTIVE STEP SIZES
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作者 Zorana Luzanin Irena Stojkovska Milena Kresoja 《计算数学:英文版》 SCIE CSCD 2019年第1期76-94,共19页
A stochastic approximation (SA)algorithm with new adaptive step sizes for solving unconstrained minimization problems in noisy environment is proposed.New adaptive step size scheme uses ordered statistics of fixed num... A stochastic approximation (SA)algorithm with new adaptive step sizes for solving unconstrained minimization problems in noisy environment is proposed.New adaptive step size scheme uses ordered statistics of fixed number of previous noisy function values as a criterion for accepting good and rejecting bad steps.The scheine allows the algorithm to move in bigger steps and avoid steps proportional to 1/k when it is expected that larger steps will improve the performance.An algorithin with the new adaptive scheme is defined for a general descent direction.The ahnost sure convergence is established.The performance of new algorithm is tested on a set of standard test problems and compared with relevant algorithms.Numerical results support theoretical expectations and verify efficiency of the algorithm regardless of chosen search direction and noise level.Numerical results on probleins arising in machine learning are also presented.Linear regression problem is considered using real data set.The results suggest that the proposed algorithln shows proinise. 展开更多
关键词 UNCONSTRAINED OPTIMIZATION STOCHASTIC OPTIMIZATION STOCHASTIC APPROXIMATION NOISY function Adaptive step size DESCENT direction Linear regression model
Robust Topology Optimization of Vehicle Suspension Control Arm 预览
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作者 Xiaokai Chen Cheng Zhang Qinghai Zhao 《北京理工大学学报:英文版》 EI CAS 2019年第3期626-634,共9页
A robust topology optimization design framework is developed to solve lightweight structural design problems under uncertain conditions. To enhance the calculation accuracy and flexibility of the statistical moments o... A robust topology optimization design framework is developed to solve lightweight structural design problems under uncertain conditions. To enhance the calculation accuracy and flexibility of the statistical moments of robust analysis, number theory integral method is applied to sample point selection and weight assignment. Both the structure topology optimization and number theory integral methods are combined to form a new robust topology optimization method. A suspension control arm problem is provided as a demonstration of robust topology optimization methods under loading uncertainties. Based on the results of deterministic and robust topology optimization, it is demonstrated that the proposed robust topology optimization method can produce a more robust design than that obtained by deterministic topology optimization. It is also found that this new approach is easy to apply in the existing commercial topology optimization software and thus feasible in practical engineering problems. 展开更多
关键词 ROBUST TOPOLOGY OPTIMIZATION (RTO) number theory INTEGRAL SUSPENSION control arm uncertainty DETERMINISTIC TOPOLOGY OPTIMIZATION (DTO)
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Taking into Account of Functional Constraints in Optimization of Modes of Power Systems by Genetic Algorithms 预览
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作者 Gayibov Tulkin Shernazarovich Latipov Sherkhon Shuxratovich 《工程(英文)(1947-3931)》 2019年第4期240-246,共7页
The development of the capabilities of computational tools has created up new possibilities for the effective use of a number of classical mathematical methods and algorithms for solving many important problems in the... The development of the capabilities of computational tools has created up new possibilities for the effective use of a number of classical mathematical methods and algorithms for solving many important problems in the power engineering. In particular, a set of algorithms are developed to optimize the modes of electric power systems based on genetic algorithms. At the same time, the issues of taking into account functional constraints in solving such problems by genetic algorithms need to be improved. In accordance with it in this article the problems of taking into account of different constraints in optimization of modes of power systems using genetic algorithms are considered. The algorithm of optimization by genetic algorithm taking into account of functional constraints in forms of equality and inequality by penalty functions is proposed. The results of research of proposed algorithm’s efficiency in example of optimization of mode of power system with 8 buses, 4 thermal power plants and 3 transmission lines with controlled power flow are presented. 展开更多
关键词 OPTIMIZATION POWER System POWER Plant Objective Function CONSTRAINT
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Solution of Second-Order Ordinary Differential Equations via Simulated Annealing 预览
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作者 Abdulazeez Bilesanmi Ashiribo Senapon Wusu Akinwale Lewis Olutimo 《最优化(英文)》 2019年第1期32-37,共6页
In this paper, we approach the problem of obtaining approximate solution of second-order initial value problems by converting it to an optimization problem. It is assumed that the solution can be approximated by a pol... In this paper, we approach the problem of obtaining approximate solution of second-order initial value problems by converting it to an optimization problem. It is assumed that the solution can be approximated by a polynomial. The coefficients of the polynomial are then optimized using simulated annealing technique. Numerical examples with good results show the accuracy of the proposed approach compared with some existing methods. 展开更多
关键词 SIMULATED ANNEALING SECOND-ORDER Ordinary DIFFERENTIAL EQUATION POLYNOMIAL Optimization
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Soft-sensing modeling and intelligent optimal control strategy for distillation yield rate of atmospheric distillation oil refining process
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作者 Zheng Wang Cheng Shao Li Zhu 《中国化学工程学报:英文版》 SCIE EI CAS CSCD 2019年第5期1113-1124,共12页
It is a challenge to conserve energy for the large-scale petrochemical enterprises due to complex production process and energy diversification. As critical energy consumption equipment of atmospheric distillation oil... It is a challenge to conserve energy for the large-scale petrochemical enterprises due to complex production process and energy diversification. As critical energy consumption equipment of atmospheric distillation oil refining process, the atmospheric distillation column is paid more attention to save energy. In this paper, the optimal problem of energy utilization efficiency of the atmospheric distillation column is solved by defining a new energy efficiency indicator - the distillation yield rate of unit energy consumption from the perspective of material flow and energy flow, and a soft-sensing model for this new energy efficiency indicator with respect to the multiple working conditions and intelligent optimizing control strategy are suggested for both increasing distillation yield and decreasing energy consumption in oil refining process. It is found that the energy utilization efficiency level of the atmospheric distillation column depends closely on the typical working conditions of the oil refining process, which result by changing the outlet temperature, the overhead temperature, and the bottom liquid level of the atmospheric pressure tower. The fuzzy C-means algorithm is used to classify the typical operation conditions of atmospheric distillation in oil refining process. Furthermore, the LSSVM method optimized with the improved particle swarm optimization is used to model the distillation rate of unit energy consumption. Then online optimization of oil refining process is realized by optimizing the outlet temperature, the overhead temperature with IPSO again. Simulation comparative analyses are made by empirical data to verify the effectiveness of the proposed solution. 展开更多
关键词 Energy efficiency OPTIMIZATION CRUDE oil DISTILLATION Particle WARM OPTIMIZATION Fuzzy C-MEANS algorithm Working condition
Shape design of arch dams under load uncertainties with robust optimization
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作者 Fengjie TAN Tom LAHMER 《结构与土木工程前沿:英文版》 EI CSCD 2019年第4期852-862,共11页
Due to an increased need in hydro-electricity, water storage, and flood protection, it is assumed that a series of new dams will be build throughout the world. The focus of this paper is on the non-probabilistic-based... Due to an increased need in hydro-electricity, water storage, and flood protection, it is assumed that a series of new dams will be build throughout the world. The focus of this paper is on the non-probabilistic-based design of new arch-type dams by applying means of robust design optimization (RDO). This type of optimization takes into account uncertainties in the loads and in the material properties of the structure. As classical procedures of probabilistic-based optimization under uncertainties, such as RDO and reliability-based design optimization (RBDO), are in general computationally expensive and rely on estimates of the system’s response variance, we will not follow a full-probabilistic approach but work with predefined confidence levels. This leads to a bi-level optimization program where the volume of the dam is optimized under the worst combination of the uncertain parameters. As a result, robust and reliable designs are obtained and the result is independent from any assumptions on stochastic properties of the random variables in the model. The optimization of an arch-type dam is realized here by a robust optimization method under load uncertainty, where hydraulic and thermal loads are considered. The load uncertainty is modeled as an ellipsoidal expression. Comparing with any traditional deterministic optimization method, which only concerns the minimum objective value and offers a solution candidate close to limit-states, the RDO method provides a robust solution against uncertainty. To reduce the computational cost, a ranking strategy and an approximation model are further involved to do a preliminary screening. By this means, the robust design can generate an improved arch dam structure that ensures both safety and serviceability during its lifetime. 展开更多
关键词 ARCH DAM shape OPTIMIZATION robust OPTIMIZATION LOAD uncertainty APPROXIMATION model
The Optimization of Manufacturing Resources Allocation Considering the Geographical Distribution 预览
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作者 Ceyuan Liang Lijun He Guangyu Zhu 《哈尔滨工业大学学报:英文版》 EI CAS 2019年第4期78-88,共11页
From the perspective of the geographical distribution, considering production fare, supply chain information and quality rating of the manufacturing resource(MR), a manufacturing resource allocation(MRA) model conside... From the perspective of the geographical distribution, considering production fare, supply chain information and quality rating of the manufacturing resource(MR), a manufacturing resource allocation(MRA) model considering the geographical distribution in cloud manufacturing(CM) environment is built. The model includes two stages, preliminary selection stage and optimal selection stage. The membership function is used to select MRs from cloud resource pool(CRP) in the first stage, and then the candidate resource pool is built. In the optimal selection stage, a multi-objective optimization algorithm, particle swarm optimization(PSO) based on the method of relative entropy of fuzzy sets(REFS_PSO), is used to select optimal MRs from the candidate resource pool, and an optimal manufacturing resource supply chain is obtained at last. To verify the performance of REFS_PSO, NSGA-Ⅱ and PSO based on random weighting(RW_PSO) are selected as the comparison algorithms. They all are used to select optimal MRs at the second stage. The experimental results show solution obtained by REFS_PSO is the best. The model and the method proposed are appropriate for MRA in CM. 展开更多
关键词 cloud manufacturing resource OPTIMIZATION ALLOCATION Fuzzy SETS RELATIVE ENTROPY many-objective OPTIMIZATION supply chain
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Optimized cellular automaton for stand delineation 预览
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作者 Timo Pukkala 《林业研究:英文版》 CAS CSCD 2019年第1期107-119,共13页
Forest inventories based on remote sensing often interpret stand characteristics for small raster cells instead of traditional stand compartments.This is the case for instance in the Lidar-based and multi-source fores... Forest inventories based on remote sensing often interpret stand characteristics for small raster cells instead of traditional stand compartments.This is the case for instance in the Lidar-based and multi-source forest inventories of Finland where the interpretation units are 16 m×16 m grid cells.Using these cells as simulation units in forest planning would lead to very large planning problems.This difficulty could be alleviated by aggregating the grid cells into larger homogeneous segments before planning calculations.This study developed a cellular automaton(CA)for aggregating grid cells into larger calculation units,which in this study were called stands.The criteria used in stand delineation were the shape and size of the stands,and homogeneity of stand attributes within the stand.The stand attributes were:main site type(upland or peatland forest),site fertility,mean tree diameter,mean tree height and stand basal area.In the CA,each cell was joined to one of its adjacent stands for several iterations,until the cells formed a compact layout of homogeneous stands.The CA had several parameters.Due to high number possible parameter combinations,particle swarm optimization was used to find the optimal set of parameter values.Parameter optimization aimed at minimizing within-stand variation and maximizing between-stand variation in stand attributes.When the CA was optimized without any restrictions for its parameters,the resulting stand delineation consisted of small and irregular stands.A clean layout of larger and compact stands was obtained when the CA parameters were optimized with constrained parameter values and so that the layout was penalized as a function of the number of small stands(<0.1 ha).However,there was within-stand variation in fertility class due to small-scale variation in the data.The stands delineated by the CA explained 66–87%of variation in stand basal area,mean tree height and mean diameter,and 41–92%of variation in the fertility class of the site.It was concluded that the CA develope 展开更多
关键词 Forest planning Particle SWARM OPTIMIZATION RASTER data SEGMENTATION Spatial OPTIMIZATION
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AI for 5G:research directions and paradigms
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作者 Xiaohu YOU Chuan ZHANG +2 位作者 Xiaosi TAN Shi JIN Hequan WU 《中国科学:信息科学(英文版)》 SCIE EI CSCD 2019年第2期1-13,共13页
Wireless communication technologies such as fifth generation mobile networks(5 G)will not only provide an increase of 1000 times in Internet traffic in the next decade but will also offer the underlying technologies t... Wireless communication technologies such as fifth generation mobile networks(5 G)will not only provide an increase of 1000 times in Internet traffic in the next decade but will also offer the underlying technologies to entire industries to support Internet of things(IOT)technologies.Compared to existing mobile communication techniques,5 G has more varied applications and its corresponding system design is more complicated.The resurgence of artificial intelligence(AI)techniques offers an alternative option that is possibly superior to traditional ideas and performance.Typical and potential research directions related to the promising contributions that can be achieved through AI must be identified,evaluated,and investigated.To this end,this study provides an overview that first combs through several promising research directions in AI for 5 G technologies based on an understanding of the key technologies in 5 G.In addition,the study focuses on providing design paradigms including 5 G network optimization,optimal resource allocation,5 G physical layer unified acceleration,end-to-end physical layer joint optimization,and so on. 展开更多
关键词 5G mobile communication AI techniques network OPTIMIZATION resource ALLOCATION UNIFIED ACCELERATION END-TO-END joint OPTIMIZATION
Dubins Waypoint Navigation of Small-Class Unmanned Aerial Vehicles 预览
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作者 Larry M. Silverberg Dahan Xu 《最优化(英文)》 2019年第2期59-72,共14页
This paper considers a variation on the Dubins path problem and proposes an improved waypoint navigation (WN) algorithm called Dubins waypoint navigation (DWN). Based on the Dubins path problem, an algorithm is develo... This paper considers a variation on the Dubins path problem and proposes an improved waypoint navigation (WN) algorithm called Dubins waypoint navigation (DWN). Based on the Dubins path problem, an algorithm is developed that is updated in real-time with a horizon of three waypoints. The purpose of DWN is to overcome a problem that we find in existing WN for small-class fixed-wing unmanned aerial vehicles (UAV) of not accurately reaching waypoints. This problem results at times in high overshoot and, in the presence of wind disturbances, it can cause a vehicle to miss the waypoint and swirl around it. To prevent this, the DWN creates “new waypoints” that are in the background, called turning points. Examples illustrate the improvement of the performance of WN achieved using the DWN algorithm in terms of the targeting of waypoints while reducing fuel and time. 展开更多
关键词 Dubins PATH WAYPOINT NAVIGATION Unmanned AERIAL VEHICLES AUTONOMY Shortest PATH Fuel Optimization
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Aerodynamic optimization design of general parameters for cycloidal propeller in hover based on surrogate model
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作者 ZENG Jianan ZHU Qinghua +2 位作者 WANG Kun ZHU Zhenhua SHEN Suiyuan 《航空动力学报》 EI CAS CSCD 北大核心 2019年第8期1741-1750,共10页
A surrogate-model-based aerodynamic optimization design method for cycloidal propeller in hover was proposed,in order to improve its aerodynamic efficiency,and analyze the basic criteria for its aerodynamic optimizati... A surrogate-model-based aerodynamic optimization design method for cycloidal propeller in hover was proposed,in order to improve its aerodynamic efficiency,and analyze the basic criteria for its aerodynamic optimization design.The reliability and applicability of overset mesh method were verified.An optimization method based on Kriging surrogate model was proposed to optimize the geometric parameters for cycloidal propeller in hover with the use of genetic algorithm.The optimization results showed that the thrust coefficient was increased by 3.56%,the torque coefficient reduced by 12.05%,and the figure of merit(FM)increased by 19.93%.The optimization results verified the feasibility of this design idea.Although the optimization was only carried out at a single rotation speed,the aerodynamic efficiency was also significantly improved over a wide range of rotation speeds.The optimal configuration characteristics for micro and small-sized cycloidal propeller were:solidity of 0.2-0.22,maximum pitch angle of 25°-35°,pitch axis locating at 35%-45% of the blade chord length. 展开更多
关键词 cycloidal PROPELLER aerodynamic shape OPTIMIZATION KEY design PARAMETERS surrogate-based OPTIMIZATION dynamic overset MESH
Optimization of Isolation and Culture of Protoplasts in Alfalfa (<i>Medicago sativa</i>) Cultivar Regen-SY 预览
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作者 Ankush Sangra Lubana Shahin Sarwan K. Dhir 《美国植物学期刊(英文)》 2019年第7期1206-1219,共14页
Alfalfa (Medicago sativa) is an important forage crop belonging to the Fabaceae family. It is cultivated across the world for fodder and originated in Asia. Alfalfa cultivar Regen-SY was used in this study which is a ... Alfalfa (Medicago sativa) is an important forage crop belonging to the Fabaceae family. It is cultivated across the world for fodder and originated in Asia. Alfalfa cultivar Regen-SY was used in this study which is a hybrid of first-generation self-parents from Regen-S (M. sativa) and Regen-Y (Medicago falcata) research cultivars. The main objective of the study was to optimize conditions for the isolation and liquid culture of alfalfa Regen-SY protoplasts. Several factors like enzyme combination, incubation time, plant age, centrifugation speed and shaker speed affecting protoplast isolation and culture were optimized in the study. The yield and viability of the protoplasts was determined by using hemocytometer and Fluorescein diacetate (FDA) staining respectively. Results showed that factors like enzyme combination, incubation time, plant age, centrifugation speed and Mannitol concentration significantly (p ≤ 0.05) affect protoplast yield and viability whereas shaker speed didn’t result in any significant difference in the yield and viability of protoplasts. Using optimum conditions protoplasts were cultured in the liquid medium and microcalli formation was achieved after five weeks of the culture. The protocol established in this study will assist researchers in the isolation and culture of protoplasts in alfalfa and will accelerate the research processes like protoplast fusion and genetic engineering. 展开更多
关键词 ALFALFA PROTOPLAST PROTOPLAST ISOLATION PROTOPLAST CULTURE OPTIMIZATION
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基于改进人工鱼群算法优化的 BP神经网络预测控制系统 预览
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作者 黄丽华 李俊丽 《化工自动化及仪表》 CAS 2019年第8期610-614,共5页
为了使传统的BP神经网络预测控制的收敛速度更快、准确率更高,提出一种改进的人工鱼群算法。分别用BP神经网络、PSO-BP神经网络和IAFSA-BP神经网络来优化预测控制系统的建模部分和滚动优化部分,并进行仿真试验,结果表明:IAFSA-BP神经网... 为了使传统的BP神经网络预测控制的收敛速度更快、准确率更高,提出一种改进的人工鱼群算法。分别用BP神经网络、PSO-BP神经网络和IAFSA-BP神经网络来优化预测控制系统的建模部分和滚动优化部分,并进行仿真试验,结果表明:IAFSA-BP神经网络优化后的预测模型精度更高,并且滚动优化部分的响应速度加快,控制系统更稳定。 展开更多
关键词 BP神经网络 预测控制 优化 改进人工鱼群算法 极值寻优
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Modeling and Optimization of Two Clays Acidic Activation for Phosphate Ions Removal in Aqueous Solution by Response Surface Methodology 预览
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作者 Yao Joseph Adjoumani Pierre Jean Marie Richard Dablé +3 位作者 Konan Edmond Kouassi Soumahoro Gueu Alain Stéphane Assémian Kouassi Benjamin Yao 《水资源与保护(英文)》 2019年第2期200-216,共17页
This work deals with phosphate ions removal in aqueous solution by adsorption carried out using two clays, both in activated form. One, non-swelling clay, rich in kaolinite, is associated with illite and quartz. The o... This work deals with phosphate ions removal in aqueous solution by adsorption carried out using two clays, both in activated form. One, non-swelling clay, rich in kaolinite, is associated with illite and quartz. The other, swelling, richer in montmorillonite, is associated with kaolinite, illite and quartz. Seven factors including these two clays were taken into account in a series of experimental designs in order to model and optimize the acidic activation process favoring a better phosphate removal. In addition to the choice of clay nature, the study was also interested in the identification of the mineral acid, between hydrochloric acid and sulfuric acid, which would promote this acidic activation. Response Surface Methodology (RSM) was used for this purpose by sequentially applying Plackett and Burman Design and Full Factorial Design (FD) for screening. Then, a central composite design (CCD) was used for modeling the activation process. A mathematical surface model has been successfully established. Thus, the best acidic activation conditions were obtained by activating the montmorillonite clay with a 2N sulfuric acid solution, in an acid/clay mass ratio of 7.5 at 100°C for 16H. The phosphate removal maximum rate obtained was estimated at 89.32% ± 0.86%. 展开更多
关键词 Clay ACIDIC ACTIVATION MODELING Optimization PHOSPHATE REMOVAL Response Surface Methodology
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