Skilled individual agents are firm basis of a strong soccer team. The skills available to Everest 2002 (agents) include kicking, dribbling, forwarding, ball interception and tackling. These intermediate sub goals are ...Skilled individual agents are firm basis of a strong soccer team. The skills available to Everest 2002 (agents) include kicking, dribbling, forwarding, ball interception and tackling. These intermediate sub goals are implemented by a combination of local optimization which hopes to determine the optimal primitive action from a local perspective and adversarial consideration which takes into account opponents and limitations imposed by simulation environment. Everest 2002 RoboCup simulation teams, building on 11 skilled agents and an on-line coach, won the 2nd place in RoboCup 2002 simulation league.展开更多
In order to study the triangulation for the point cloud data collected by three-dimensional laser radar,in accordance with the line-by-line characteristics of laser radar scanning,an improved Delaunay triangulation me...In order to study the triangulation for the point cloud data collected by three-dimensional laser radar,in accordance with the line-by-line characteristics of laser radar scanning,an improved Delaunay triangulation method is proposed to mesh the point cloud data as a triangulation irregular network.Based on the geometric topology location information among radar point cloud data,focusing on the position relationship between adjacent scanning line of the point data,a preliminary match network is obtained according to their geometric relationship.A reasonable triangulation network for the object surface is acquired after the use of local optimization on initial mesh by Delaunay rule.Meanwhile,a new judging rule is proposed to contrast the triangulation before and after the optimization on the network.The result shows that triangulation for point cloud with full use of its own characteristics can improve the speed of the algorithm obviously,and the rule for judging the triangulation can evaluate the quality of network.展开更多
Wireless Sensor Network(WSNs)consists of a group of nodes that analyze the information from surrounding regions.The sensor nodes are responsible for accumulating and exchanging information.Generally,node local-ization...Wireless Sensor Network(WSNs)consists of a group of nodes that analyze the information from surrounding regions.The sensor nodes are responsible for accumulating and exchanging information.Generally,node local-ization is the process of identifying the target node’s location.In this research work,a Received Signal Strength Indicator(RSSI)-based optimal node localization approach is proposed to solve the complexities in the conventional node localization models.Initially,the RSSI value is identified using the Deep Neural Network(DNN).The RSSI is conceded as the range-based method and it does not require special hardware for the node localization process,also it consumes a very minimal amount of cost for localizing the nodes in 3D WSN.The position of the anchor nodes is fixed for detecting the location of the target.Further,the optimal position of the target node is identified using Hybrid T cell Immune with Lotus Effect Optimization algorithm(HTCI-LEO).During the node localization process,the average localization error is minimized,which is the objective of the optimal node localization.In the regular and irregular surfaces,this hybrid algorithm effectively performs the localization process.The suggested hybrid algorithm converges very fast in the three-dimensional(3D)environment.The accuracy of the proposed node localization process is 94.25%.展开更多
Electrochemical carbon dioxide reduction reaction(CO_(2)RR)produces valuable chemicals by consuming gaseous CO_(2)as well as protons from the electrolyte.Protons,produced by water dissociation in alkaline electrolyte,...Electrochemical carbon dioxide reduction reaction(CO_(2)RR)produces valuable chemicals by consuming gaseous CO_(2)as well as protons from the electrolyte.Protons,produced by water dissociation in alkaline electrolyte,are critical for the reaction kinetics which involves multiple proton coupled electron transfer steps.Herein,we demonstrate that the two key steps(CO_(2)-^(*)COOH and^(*)CO-^(*)COH)efficiency can be precisely tuned by introducing proper amount of water dissociation center,i.e.,Fe single atoms,locally surrounding the Cu catalysts.In alkaline electrolyte,the Faradaic efficiency(FE)of multi-carbon(C^(2+))products exhibited a volcano type plot depending on the density of water dissociation center.A maximum FE for C^(2+)products of 73.2%could be reached on Cu nanoparticles supported on N-doped Carbon nanofibers with moderate Fe single atom sites,at a current density of 300 mA cm^(–2).Experimental and theoretical calculation results reveal that the Fe sites facilitate water dissociation kinetics,and the locally generated protons contribute significantly to the CO_(2)activation and^(*)CO protonation process.On the one hand,in-situ attenuated total reflection surface-enhanced infrared absorption spectroscopy(in-situ ATR-SEIRAS)clearly shows that the^(*)COOH intermediate can be observed at a lower potential.This phenomenon fully demonstrates that the optimized local water dissociation kinetics has a unique advantage in guiding the hydrogenation reaction pathway of CO₂molecules and can effectively reduce the reaction energy barrier.On the other hand,abundant^(*)CO and^(*)COH intermediates create favorable conditions for the asymmetric^(*)CO-^(*)COH coupling,significantly increasing the selectivity of the reaction for C^(2+)products and providing strong support for the efficient conversion of related reactions to the target products.This work provides a promising strategy for the design of a dual sites catalyst to achieve high FE of C^(2+)products through the optimized local water dissociation kinetics.展开更多
Aiming at the problem that the mesh simplification algorithm loses the geometric features of the model in large-scale simplification,an improved half-edge collapse mesh simplification algorithm is proposed.The concept...Aiming at the problem that the mesh simplification algorithm loses the geometric features of the model in large-scale simplification,an improved half-edge collapse mesh simplification algorithm is proposed.The concept of approximate measurement of edge curvature is introduced,and the edge curvature is added to the error measure,so that the order of half-edge collapse of the mesh is changed,and the simplified details of the mesh model can be preserved accurately.At the same time,by analyzing the quality of simplified triangular mesh,optimizing triangular mesh locally,reducing the amount of narrow triangles,the quality of the simplified model is improved.The proposed algorithm was tested on Cow model,Car model and Bunny model,and compared with another three algorithms,one of them is a classical mesh simplification algorithm based on edge collapse,the other is an improved algorithm of the classical one.The experimental results show that the improved algorithm can better retain the detail features of the original model at the same reduction ratio,and has reasonable mesh allocation,fast execution speed and small error.展开更多
Landing gear lower drag stay is a key component which connects fuselage and landing gear and directly effects the safety and performance of aircraft takeoff and landing. To effectively design the lower drag stay and r...Landing gear lower drag stay is a key component which connects fuselage and landing gear and directly effects the safety and performance of aircraft takeoff and landing. To effectively design the lower drag stay and reduce the weight of landing gear, Global/local Linked Driven Optimization Strategy(GLDOS) was developed to conduct the overall process design of lower drag stay in respect of optimization thought. The whole-process optimization involves two stages of structural conceptual design and detailed design. In the structural conceptual design, the landing gear lower drag stay was globally topologically optimized by adopting multiple starting points algorithm. In the detailed design, the local size and shape of landing gear lower drag stay were globally optimized by the gradient optimization strategy. The GLDOS method adopts different optimization strategies for different optimization stages to acquire the optimum design effect. Through the experimental validation, the weight of the optimized lower dray stay with the developed GLDOS is reduced by 16.79% while keeping enough strength and stiffness, which satisfies the requirements of engineering design under the typical loading conditions. The proposed GLDOS is validated to be accurate and efficient in optimization scheme and design cycles. The efforts of this paper provide a whole-process optimization approach regarding different optimization technologies in different design phases, which is significant in reducing structural weight and enhance design tp wid 1 precision for complex structures in aircrafts.展开更多
Abstract This paper describes a longitudinal parameter identification procedure for a small unmanned aerial vehicle （UAV） through modified particle swam optimization （PSO）. The proce- dure is demonstrated using a ...Abstract This paper describes a longitudinal parameter identification procedure for a small unmanned aerial vehicle （UAV） through modified particle swam optimization （PSO）. The proce- dure is demonstrated using a small UAV equipped with only an micro-electro-mechanical systems （MEMS） inertial mea,mring element and a global positioning system （GPS） receiver to provide test information. A small UAV longitudinal parameter mathematical model is derived and the modified method is proposed based on PSO with selective particle regeneration （SRPSO）. Once modified PSO is applied to the mathematical model, the simulation results show that the mathematical model is correct, and aerodynamic parameters and coefficients of the propeller can be identified accurately. Results are compared with those of PSO and SRPSO and the comparison shows that the proposed method is more robust and faster than the other methods for the longitudinal parameter identification of the small UAV. Some parameter identification results are affected slightly by noise, but the identification results are very good overall. Eventually, experimental validation is employed to test the proposed method, which demonstrates the usefulness of this method.展开更多
Cooperative path planning is an important area in fixed-wing UAV swarm.However,avoiding multiple timevarying obstacles and avoiding local optimum are two challenges for existing approaches in a dynamic environment.Fir...Cooperative path planning is an important area in fixed-wing UAV swarm.However,avoiding multiple timevarying obstacles and avoiding local optimum are two challenges for existing approaches in a dynamic environment.Firstly,a normalized artificial potential field optimization is proposed by reconstructing a novel function with anisotropy in each dimension,which can make the flight speed of a fixed UAV swarm independent of the repulsive/attractive gain coefficient and avoid trapping into local optimization and local oscillation.Then,taking into account minimum velocity and turning angular velocity of fixed-wing UAV swarm,a strategy of decomposing target vector to avoid moving obstacles and pop-up threats is proposed.Finally,several simulations are carried out to illustrate superiority and effectiveness.展开更多
This paper presents a two-phase genetic algorithm (TPGA) based on the multi- parent genetic algorithm (MPGA). Through analysis we find MPGA will lead the population' s evol vement to diversity or convergence accor...This paper presents a two-phase genetic algorithm (TPGA) based on the multi- parent genetic algorithm (MPGA). Through analysis we find MPGA will lead the population' s evol vement to diversity or convergence according to the population size and the crossover size, so we make it run in different forms during the global and local optimization phases and then forms TPGA. The experiment results show that TPGA is very efficient for the optimization of low-dimension multi-modal functions, usually we can obtain all the global optimal solutions.展开更多
In the study of information technology,one of the important efforts is made on dealing with nonsubmodular optimizations since there are many such problems raised in various areas of computer and information science.Us...In the study of information technology,one of the important efforts is made on dealing with nonsubmodular optimizations since there are many such problems raised in various areas of computer and information science.Usually,nonsubmodular optimization problems are NP-hard.Therefore,design and analysis of approximation algorithms are important tasks in the study of nonsubmodular optimizations.However,the traditional methods do not work well.Therefore,a new method,the global approximation of local optimality,is proposed recently.In this paper,we give an extensive study for this new methodology.展开更多
This paper presents a method to reconstruct 3-D models of trees from terrestrial laser scan(TLS)point clouds.This method uses the weighted locally optimal projection(WLOP)and the AdTree method to reconstruct detailed ...This paper presents a method to reconstruct 3-D models of trees from terrestrial laser scan(TLS)point clouds.This method uses the weighted locally optimal projection(WLOP)and the AdTree method to reconstruct detailed 3-D tree models.To improve its representation accuracy,the WLOP algorithm is introduced to consolidate the point cloud.Its reconstruction accuracy is tested using a dataset of ten trees,and the one-sided Hausdorff distances between the input point clouds and the resulting 3-D models are measured.The experimental results show that the optimal projection modeling method has an average one-sided Hausdorff distance(mean)lower by 30.74%and 6.43%compared with AdTree and AdQSM methods,respectively.Furthermore,it has an average one-sided Hausdorff distance(RMS)lower by 29.95%and 12.28%compared with AdTree and AdQSM methods.Results show that the 3-D model generated fits closely to the input point cloud data and ensures a high geometrical accuracy.展开更多
A distibuted optimal local double loop(DOLDL) network is presented. Emphasis is laid on the topology and distributed routing algorithms for the DOLDL. On the basis of building an abstract model, a set of definitions a...A distibuted optimal local double loop(DOLDL) network is presented. Emphasis is laid on the topology and distributed routing algorithms for the DOLDL. On the basis of building an abstract model, a set of definitions and theorems are described and proved. An algorithm which can optimize the double loop networks is presented. The optimal values of the topologic parameters for the DOLDL have been obtained by the algorithm, and these numerical results are analyzed. The study shows that the bounds of the optimal diameter (d) and average hop distance (a) for this class of networks are [square-root 3N -2] less-than-or-equal-to d less-than-or-equal-to [square-root 3N+1] and (5N/9(N-1)) (square-root 3N-1.8) < a < (5N/9 (N-1)). (square-root 3N - 0.23), respectively (N is the number of nodes in the network. (3 less-than-or-equal-to N less-than-or-equal-to 10(4)). A class of the distributed routing algorithms for the DOLDL and the implementation procedure of an adaptive fault-tolerant algorithm are proposed. The correctness of the algorithm has been also verified by simulating.展开更多
The clustered regularly interspaced short palindromic repeats(CRISPR)–CRISPR-associated protein(Cas) system has been widely used for genome editing. In this system, the cytosine base editor(CBE) and adenine base edit...The clustered regularly interspaced short palindromic repeats(CRISPR)–CRISPR-associated protein(Cas) system has been widely used for genome editing. In this system, the cytosine base editor(CBE) and adenine base editor(ABE) allow generating precise and irreversible base mutations in a programmable manner and have been used in many different types of cells and organisms. However, their applications are limited by low editing efficiency at certain genomic target sites or at specific target cytosine(C) or adenine(A) residues. Using a strategy of combining optimized synergistic core components, we developed a new multiplex super-assembled ABE(sABE) in rice that showed higher base-editing efficiency than previously developed ABEs. We also designed a new type of nuclear localization signal(NLS) comprising a FLAG epitope tag with four copies of a codon-optimized NLS(F4NLS^(r2)) to generate another ABE named F4NLS-sABE. This new NLS increased editing efficiency or edited additional A at several target sites. A new multiplex super-assembled CBE(sCBE) and F4NLS^(r2) involved F4NLS-sCBE were also created using the same strategy. F4NLS-sCBE was proven to be much more efficient than sCBE in rice. These optimized base editors will serve as powerful genome-editing tools for basic research or molecular breeding in rice and will provide a reference for the development of superior editing tools for other plants or animals.展开更多
Considering comprehensive benefit of micro-grid system and consumers,we establish a mathematical model with the goal of the maximum consumer satisfaction and the maximum benefit of power generation side in the view of...Considering comprehensive benefit of micro-grid system and consumers,we establish a mathematical model with the goal of the maximum consumer satisfaction and the maximum benefit of power generation side in the view of energy management.An improved multi-objective local mutation adaptive quantum particle swarm optimization(MO-LM-AQPSO)algorithm is adopted to obtain the Pareto frontier of consumer satisfaction and the benefit of power generation side.The optimal solution of the non-dominant solution is selected with introducing the power shortage and power loss to maximize the benefit of power generation side,and its reasonableness is verified by numerical simulation.Then,translational load and time-of-use electricity price incentive mechanism are considered and reasonable peak-valley price ratio is adopted to guide users to actively participate in demand response.The simulation results show that the reasonable incentive mechanism increases the benefit of power generation side and improves the consumer satisfaction.Also the mechanism maximizes the utilization of renewable energy and effectively reduces the operation cost of the battery.展开更多
Among steganalysis techniques,detection against MV(motion vector)domain-based video steganography in the HEVC(High Efficiency Video Coding)standard remains a challenging issue.For the purpose of improving the detectio...Among steganalysis techniques,detection against MV(motion vector)domain-based video steganography in the HEVC(High Efficiency Video Coding)standard remains a challenging issue.For the purpose of improving the detection performance,this paper proposes a steganalysis method that can perfectly detectMV-based steganography in HEVC.Firstly,we define the local optimality of MVP(Motion Vector Prediction)based on the technology of AMVP(Advanced Motion Vector Prediction).Secondly,we analyze that in HEVC video,message embedding either usingMVP index orMVD(Motion Vector Difference)may destroy the above optimality of MVP.And then,we define the optimal rate of MVP as a steganalysis feature.Finally,we conduct steganalysis detection experiments on two general datasets for three popular steganographymethods and compare the performance with four state-ofthe-art steganalysis methods.The experimental results demonstrate the effectiveness of the proposed feature set.Furthermore,our method stands out for its practical applicability,requiring no model training and exhibiting low computational complexity,making it a viable solution for real-world scenarios.展开更多
Finding out reasonable structures from bulky data is one of the difficulties in modeling of Bayesian network （BN）, which is also necessary in promoting the application of BN. This pa- per proposes an immune algorith...Finding out reasonable structures from bulky data is one of the difficulties in modeling of Bayesian network （BN）, which is also necessary in promoting the application of BN. This pa- per proposes an immune algorithm based method （BN-IA） for the learning of the BN structure with the idea of vaccination. Further- more, the methods on how to extract the effective vaccines from local optimal structure and root nodes are also described in details. Finally, the simulation studies are implemented with the helicopter convertor BN model and the car start BN model. The comparison results show that the proposed vaccines and the BN-IA can learn the BN structure effectively and efficiently.展开更多
DRAM row buffer conflicts can increase memory access latency significantly. This paper presents a new pageallocation-based optimization that works seamlessly together with some existing hardware and software optimizat...DRAM row buffer conflicts can increase memory access latency significantly. This paper presents a new pageallocation-based optimization that works seamlessly together with some existing hardware and software optimizations to eliminate significantly more row buffer conflicts. Validation in simulation using a set of selected scientific and engineering benchmarks against a few representative memory controller optimizations shows that our method can reduce row buffer miss rates by up to 76% （with an average of 37.4%）. This reduction in row buffer miss rates will be translated into performance speedups by up to 15% （with an average of 5%）.展开更多
In this paper,we consider a class of mixed integer weakly concave programming problems(MIWCPP)consisting of minimizing a difference of a quadratic function and a convex function.A new necessary global optimality condi...In this paper,we consider a class of mixed integer weakly concave programming problems(MIWCPP)consisting of minimizing a difference of a quadratic function and a convex function.A new necessary global optimality conditions for MIWCPP is presented in this paper.A new local optimization method for MIWCPP is designed based on the necessary global optimality conditions,which is different from the traditional local optimization method.A global optimization method is proposed by combining some auxiliary functions and the new local optimization method.Furthermore,numerical examples are also presented to show that the proposed global optimization method for MIWCPP is efficient.展开更多
Recently proposed steganalysis methods based on the local optimality of motion vector prediction(MVP)indicate that the existing HEVC(high efficiency video coding)motion vector(MV)domain video steganography algorithms ...Recently proposed steganalysis methods based on the local optimality of motion vector prediction(MVP)indicate that the existing HEVC(high efficiency video coding)motion vector(MV)domain video steganography algorithms can disturb the optimality of MVP in advanced motion vector prediction(AMVP)technology.In order to improve the security of steganography algorithm,this paper proposes an MV domain steganography method in HEVC based on MVP’s index and motion vector difference(MVD).First,we analyze the conditions that need to be met for steganography to resist attacks from MVP’s optimality features and other traditional steganalysis features.Then,a distortion function for minimizing embedding distortion is designed,and an algorithm for secret message embedding and extraction in units of inter-frame is proposed.Experimental results show that the proposed algorithm can resist attacks based on the optimality of MVP and also has high security against other traditional steganalysis methods.In addition,the proposed algorithm has excellent performance in visual quality and coding efficiency,and can be applied to practical scenarios of video covert communication.展开更多
As distributed energy storage equipments, electric vehicles (EVs) have great potential for applications in power systems. Meanwhile, reasonable optimization of the charging time of EVs can reduce the users’ expense. ...As distributed energy storage equipments, electric vehicles (EVs) have great potential for applications in power systems. Meanwhile, reasonable optimization of the charging time of EVs can reduce the users’ expense. Thus, the schedule of the EV load requires multi-objective optimization. A diversity-maximization non-dominated sorting genetic algorithm (DM-NSGA)-II is developed to perform multi-objective optimization by considering the power load profile, the users’charging cost, and battery degradation. Furthermore, a real-time locally optimal schedule is adopted by utilizing a flexible time scale. The case study illustrates that the proposed DM-NSGA-II can prevent being trapped in a relatively limited region so as to diversify the optimal results and provide trade-off solutions to decision makers. The simulation analysis shows that the variable time scale can continuously involve the present EVs in the real-time optimization rather than rely on the forecasting data. The schedule of the EV load is more practical without the loss of accuracy.展开更多
文摘Skilled individual agents are firm basis of a strong soccer team. The skills available to Everest 2002 (agents) include kicking, dribbling, forwarding, ball interception and tackling. These intermediate sub goals are implemented by a combination of local optimization which hopes to determine the optimal primitive action from a local perspective and adversarial consideration which takes into account opponents and limitations imposed by simulation environment. Everest 2002 RoboCup simulation teams, building on 11 skilled agents and an on-line coach, won the 2nd place in RoboCup 2002 simulation league.
基金the National Natural Science Foundation of China (No. 50805094)the National Basic Research Program (973) of China (No. 2006CB705400)
文摘In order to study the triangulation for the point cloud data collected by three-dimensional laser radar,in accordance with the line-by-line characteristics of laser radar scanning,an improved Delaunay triangulation method is proposed to mesh the point cloud data as a triangulation irregular network.Based on the geometric topology location information among radar point cloud data,focusing on the position relationship between adjacent scanning line of the point data,a preliminary match network is obtained according to their geometric relationship.A reasonable triangulation network for the object surface is acquired after the use of local optimization on initial mesh by Delaunay rule.Meanwhile,a new judging rule is proposed to contrast the triangulation before and after the optimization on the network.The result shows that triangulation for point cloud with full use of its own characteristics can improve the speed of the algorithm obviously,and the rule for judging the triangulation can evaluate the quality of network.
基金appreciation to King Saud University for funding this research through the Researchers Supporting Program number(RSPD2024R918),King Saud University,Riyadh,Saudi Arabia.
文摘Wireless Sensor Network(WSNs)consists of a group of nodes that analyze the information from surrounding regions.The sensor nodes are responsible for accumulating and exchanging information.Generally,node local-ization is the process of identifying the target node’s location.In this research work,a Received Signal Strength Indicator(RSSI)-based optimal node localization approach is proposed to solve the complexities in the conventional node localization models.Initially,the RSSI value is identified using the Deep Neural Network(DNN).The RSSI is conceded as the range-based method and it does not require special hardware for the node localization process,also it consumes a very minimal amount of cost for localizing the nodes in 3D WSN.The position of the anchor nodes is fixed for detecting the location of the target.Further,the optimal position of the target node is identified using Hybrid T cell Immune with Lotus Effect Optimization algorithm(HTCI-LEO).During the node localization process,the average localization error is minimized,which is the objective of the optimal node localization.In the regular and irregular surfaces,this hybrid algorithm effectively performs the localization process.The suggested hybrid algorithm converges very fast in the three-dimensional(3D)environment.The accuracy of the proposed node localization process is 94.25%.
文摘Electrochemical carbon dioxide reduction reaction(CO_(2)RR)produces valuable chemicals by consuming gaseous CO_(2)as well as protons from the electrolyte.Protons,produced by water dissociation in alkaline electrolyte,are critical for the reaction kinetics which involves multiple proton coupled electron transfer steps.Herein,we demonstrate that the two key steps(CO_(2)-^(*)COOH and^(*)CO-^(*)COH)efficiency can be precisely tuned by introducing proper amount of water dissociation center,i.e.,Fe single atoms,locally surrounding the Cu catalysts.In alkaline electrolyte,the Faradaic efficiency(FE)of multi-carbon(C^(2+))products exhibited a volcano type plot depending on the density of water dissociation center.A maximum FE for C^(2+)products of 73.2%could be reached on Cu nanoparticles supported on N-doped Carbon nanofibers with moderate Fe single atom sites,at a current density of 300 mA cm^(–2).Experimental and theoretical calculation results reveal that the Fe sites facilitate water dissociation kinetics,and the locally generated protons contribute significantly to the CO_(2)activation and^(*)CO protonation process.On the one hand,in-situ attenuated total reflection surface-enhanced infrared absorption spectroscopy(in-situ ATR-SEIRAS)clearly shows that the^(*)COOH intermediate can be observed at a lower potential.This phenomenon fully demonstrates that the optimized local water dissociation kinetics has a unique advantage in guiding the hydrogenation reaction pathway of CO₂molecules and can effectively reduce the reaction energy barrier.On the other hand,abundant^(*)CO and^(*)COH intermediates create favorable conditions for the asymmetric^(*)CO-^(*)COH coupling,significantly increasing the selectivity of the reaction for C^(2+)products and providing strong support for the efficient conversion of related reactions to the target products.This work provides a promising strategy for the design of a dual sites catalyst to achieve high FE of C^(2+)products through the optimized local water dissociation kinetics.
文摘Aiming at the problem that the mesh simplification algorithm loses the geometric features of the model in large-scale simplification,an improved half-edge collapse mesh simplification algorithm is proposed.The concept of approximate measurement of edge curvature is introduced,and the edge curvature is added to the error measure,so that the order of half-edge collapse of the mesh is changed,and the simplified details of the mesh model can be preserved accurately.At the same time,by analyzing the quality of simplified triangular mesh,optimizing triangular mesh locally,reducing the amount of narrow triangles,the quality of the simplified model is improved.The proposed algorithm was tested on Cow model,Car model and Bunny model,and compared with another three algorithms,one of them is a classical mesh simplification algorithm based on edge collapse,the other is an improved algorithm of the classical one.The experimental results show that the improved algorithm can better retain the detail features of the original model at the same reduction ratio,and has reasonable mesh allocation,fast execution speed and small error.
基金co-supported by National Natural Science Foundation of China (Nos. 51975124 and 51675179)Aerospace Science and Technology Fund of China (No.AERO201937)Research Start-up Funding of Fudan University (No. FDU38341)。
文摘Landing gear lower drag stay is a key component which connects fuselage and landing gear and directly effects the safety and performance of aircraft takeoff and landing. To effectively design the lower drag stay and reduce the weight of landing gear, Global/local Linked Driven Optimization Strategy(GLDOS) was developed to conduct the overall process design of lower drag stay in respect of optimization thought. The whole-process optimization involves two stages of structural conceptual design and detailed design. In the structural conceptual design, the landing gear lower drag stay was globally topologically optimized by adopting multiple starting points algorithm. In the detailed design, the local size and shape of landing gear lower drag stay were globally optimized by the gradient optimization strategy. The GLDOS method adopts different optimization strategies for different optimization stages to acquire the optimum design effect. Through the experimental validation, the weight of the optimized lower dray stay with the developed GLDOS is reduced by 16.79% while keeping enough strength and stiffness, which satisfies the requirements of engineering design under the typical loading conditions. The proposed GLDOS is validated to be accurate and efficient in optimization scheme and design cycles. The efforts of this paper provide a whole-process optimization approach regarding different optimization technologies in different design phases, which is significant in reducing structural weight and enhance design tp wid 1 precision for complex structures in aircrafts.
基金supported by the National Defense Basic Research Program of China(No.B22201320xx)
文摘Abstract This paper describes a longitudinal parameter identification procedure for a small unmanned aerial vehicle （UAV） through modified particle swam optimization （PSO）. The proce- dure is demonstrated using a small UAV equipped with only an micro-electro-mechanical systems （MEMS） inertial mea,mring element and a global positioning system （GPS） receiver to provide test information. A small UAV longitudinal parameter mathematical model is derived and the modified method is proposed based on PSO with selective particle regeneration （SRPSO）. Once modified PSO is applied to the mathematical model, the simulation results show that the mathematical model is correct, and aerodynamic parameters and coefficients of the propeller can be identified accurately. Results are compared with those of PSO and SRPSO and the comparison shows that the proposed method is more robust and faster than the other methods for the longitudinal parameter identification of the small UAV. Some parameter identification results are affected slightly by noise, but the identification results are very good overall. Eventually, experimental validation is employed to test the proposed method, which demonstrates the usefulness of this method.
文摘Cooperative path planning is an important area in fixed-wing UAV swarm.However,avoiding multiple timevarying obstacles and avoiding local optimum are two challenges for existing approaches in a dynamic environment.Firstly,a normalized artificial potential field optimization is proposed by reconstructing a novel function with anisotropy in each dimension,which can make the flight speed of a fixed UAV swarm independent of the repulsive/attractive gain coefficient and avoid trapping into local optimization and local oscillation.Then,taking into account minimum velocity and turning angular velocity of fixed-wing UAV swarm,a strategy of decomposing target vector to avoid moving obstacles and pop-up threats is proposed.Finally,several simulations are carried out to illustrate superiority and effectiveness.
基金Supported by the National Natural Science Foundation of China (70071042,60073043,60133010)
文摘This paper presents a two-phase genetic algorithm (TPGA) based on the multi- parent genetic algorithm (MPGA). Through analysis we find MPGA will lead the population' s evol vement to diversity or convergence according to the population size and the crossover size, so we make it run in different forms during the global and local optimization phases and then forms TPGA. The experiment results show that TPGA is very efficient for the optimization of low-dimension multi-modal functions, usually we can obtain all the global optimal solutions.
基金supported in part by the National Natural Science Foundation of China(No.U20A2068)Zhejiang Provincial Natural Science Foundation of China(No.LD19A010001)Natural Science Foundation of USA(No.1907472)。
文摘In the study of information technology,one of the important efforts is made on dealing with nonsubmodular optimizations since there are many such problems raised in various areas of computer and information science.Usually,nonsubmodular optimization problems are NP-hard.Therefore,design and analysis of approximation algorithms are important tasks in the study of nonsubmodular optimizations.However,the traditional methods do not work well.Therefore,a new method,the global approximation of local optimality,is proposed recently.In this paper,we give an extensive study for this new methodology.
基金supported in part by the National Natural Science Foundation of China(Nos.42271343,42177387)the Fund of State Key Laboratory of Remote Sensing Information and Image Analysis Technology of Beijing Research Institute of Uranium Geology under(No.6142A010403)
文摘This paper presents a method to reconstruct 3-D models of trees from terrestrial laser scan(TLS)point clouds.This method uses the weighted locally optimal projection(WLOP)and the AdTree method to reconstruct detailed 3-D tree models.To improve its representation accuracy,the WLOP algorithm is introduced to consolidate the point cloud.Its reconstruction accuracy is tested using a dataset of ten trees,and the one-sided Hausdorff distances between the input point clouds and the resulting 3-D models are measured.The experimental results show that the optimal projection modeling method has an average one-sided Hausdorff distance(mean)lower by 30.74%and 6.43%compared with AdTree and AdQSM methods,respectively.Furthermore,it has an average one-sided Hausdorff distance(RMS)lower by 29.95%and 12.28%compared with AdTree and AdQSM methods.Results show that the 3-D model generated fits closely to the input point cloud data and ensures a high geometrical accuracy.
文摘A distibuted optimal local double loop(DOLDL) network is presented. Emphasis is laid on the topology and distributed routing algorithms for the DOLDL. On the basis of building an abstract model, a set of definitions and theorems are described and proved. An algorithm which can optimize the double loop networks is presented. The optimal values of the topologic parameters for the DOLDL have been obtained by the algorithm, and these numerical results are analyzed. The study shows that the bounds of the optimal diameter (d) and average hop distance (a) for this class of networks are [square-root 3N -2] less-than-or-equal-to d less-than-or-equal-to [square-root 3N+1] and (5N/9(N-1)) (square-root 3N-1.8) < a < (5N/9 (N-1)). (square-root 3N - 0.23), respectively (N is the number of nodes in the network. (3 less-than-or-equal-to N less-than-or-equal-to 10(4)). A class of the distributed routing algorithms for the DOLDL and the implementation procedure of an adaptive fault-tolerant algorithm are proposed. The correctness of the algorithm has been also verified by simulating.
基金supported by the Beijing Scholars Program[BSP041]。
文摘The clustered regularly interspaced short palindromic repeats(CRISPR)–CRISPR-associated protein(Cas) system has been widely used for genome editing. In this system, the cytosine base editor(CBE) and adenine base editor(ABE) allow generating precise and irreversible base mutations in a programmable manner and have been used in many different types of cells and organisms. However, their applications are limited by low editing efficiency at certain genomic target sites or at specific target cytosine(C) or adenine(A) residues. Using a strategy of combining optimized synergistic core components, we developed a new multiplex super-assembled ABE(sABE) in rice that showed higher base-editing efficiency than previously developed ABEs. We also designed a new type of nuclear localization signal(NLS) comprising a FLAG epitope tag with four copies of a codon-optimized NLS(F4NLS^(r2)) to generate another ABE named F4NLS-sABE. This new NLS increased editing efficiency or edited additional A at several target sites. A new multiplex super-assembled CBE(sCBE) and F4NLS^(r2) involved F4NLS-sCBE were also created using the same strategy. F4NLS-sCBE was proven to be much more efficient than sCBE in rice. These optimized base editors will serve as powerful genome-editing tools for basic research or molecular breeding in rice and will provide a reference for the development of superior editing tools for other plants or animals.
基金National Natural Science Foundation of China(No.519667013)Institution of Higher Learning Scientific Research Project of Gansu Province of China(No.2016B-032)。
文摘Considering comprehensive benefit of micro-grid system and consumers,we establish a mathematical model with the goal of the maximum consumer satisfaction and the maximum benefit of power generation side in the view of energy management.An improved multi-objective local mutation adaptive quantum particle swarm optimization(MO-LM-AQPSO)algorithm is adopted to obtain the Pareto frontier of consumer satisfaction and the benefit of power generation side.The optimal solution of the non-dominant solution is selected with introducing the power shortage and power loss to maximize the benefit of power generation side,and its reasonableness is verified by numerical simulation.Then,translational load and time-of-use electricity price incentive mechanism are considered and reasonable peak-valley price ratio is adopted to guide users to actively participate in demand response.The simulation results show that the reasonable incentive mechanism increases the benefit of power generation side and improves the consumer satisfaction.Also the mechanism maximizes the utilization of renewable energy and effectively reduces the operation cost of the battery.
基金the National Natural Science Foundation of China(Grant Nos.62272478,62202496,61872384).
文摘Among steganalysis techniques,detection against MV(motion vector)domain-based video steganography in the HEVC(High Efficiency Video Coding)standard remains a challenging issue.For the purpose of improving the detection performance,this paper proposes a steganalysis method that can perfectly detectMV-based steganography in HEVC.Firstly,we define the local optimality of MVP(Motion Vector Prediction)based on the technology of AMVP(Advanced Motion Vector Prediction).Secondly,we analyze that in HEVC video,message embedding either usingMVP index orMVD(Motion Vector Difference)may destroy the above optimality of MVP.And then,we define the optimal rate of MVP as a steganalysis feature.Finally,we conduct steganalysis detection experiments on two general datasets for three popular steganographymethods and compare the performance with four state-ofthe-art steganalysis methods.The experimental results demonstrate the effectiveness of the proposed feature set.Furthermore,our method stands out for its practical applicability,requiring no model training and exhibiting low computational complexity,making it a viable solution for real-world scenarios.
基金supported by the National Natural Science Foundation of China(7110111671271170)+1 种基金the Program for New Century Excellent Talents in University(NCET-13-0475)the Basic Research Foundation of NPU(JC20120228)
文摘Finding out reasonable structures from bulky data is one of the difficulties in modeling of Bayesian network （BN）, which is also necessary in promoting the application of BN. This pa- per proposes an immune algorithm based method （BN-IA） for the learning of the BN structure with the idea of vaccination. Further- more, the methods on how to extract the effective vaccines from local optimal structure and root nodes are also described in details. Finally, the simulation studies are implemented with the helicopter convertor BN model and the car start BN model. The comparison results show that the proposed vaccines and the BN-IA can learn the BN structure effectively and efficiently.
基金Supported by the National Basic Research 973 Program of China under Grant No. 2005CB321602the National Natural Science Foundation of China under Grant No. 60736012
文摘DRAM row buffer conflicts can increase memory access latency significantly. This paper presents a new pageallocation-based optimization that works seamlessly together with some existing hardware and software optimizations to eliminate significantly more row buffer conflicts. Validation in simulation using a set of selected scientific and engineering benchmarks against a few representative memory controller optimizations shows that our method can reduce row buffer miss rates by up to 76% （with an average of 37.4%）. This reduction in row buffer miss rates will be translated into performance speedups by up to 15% （with an average of 5%）.
基金supported by Natural Science Foundation of Chongqing(Nos.cstc2013jjB00001 and cstc2011jjA00010).
文摘In this paper,we consider a class of mixed integer weakly concave programming problems(MIWCPP)consisting of minimizing a difference of a quadratic function and a convex function.A new necessary global optimality conditions for MIWCPP is presented in this paper.A new local optimization method for MIWCPP is designed based on the necessary global optimality conditions,which is different from the traditional local optimization method.A global optimization method is proposed by combining some auxiliary functions and the new local optimization method.Furthermore,numerical examples are also presented to show that the proposed global optimization method for MIWCPP is efficient.
基金supported by the National Natural Science Foundation of China(Nos.62102450,62272478,and 62202496).
文摘Recently proposed steganalysis methods based on the local optimality of motion vector prediction(MVP)indicate that the existing HEVC(high efficiency video coding)motion vector(MV)domain video steganography algorithms can disturb the optimality of MVP in advanced motion vector prediction(AMVP)technology.In order to improve the security of steganography algorithm,this paper proposes an MV domain steganography method in HEVC based on MVP’s index and motion vector difference(MVD).First,we analyze the conditions that need to be met for steganography to resist attacks from MVP’s optimality features and other traditional steganalysis features.Then,a distortion function for minimizing embedding distortion is designed,and an algorithm for secret message embedding and extraction in units of inter-frame is proposed.Experimental results show that the proposed algorithm can resist attacks based on the optimality of MVP and also has high security against other traditional steganalysis methods.In addition,the proposed algorithm has excellent performance in visual quality and coding efficiency,and can be applied to practical scenarios of video covert communication.
文摘As distributed energy storage equipments, electric vehicles (EVs) have great potential for applications in power systems. Meanwhile, reasonable optimization of the charging time of EVs can reduce the users’ expense. Thus, the schedule of the EV load requires multi-objective optimization. A diversity-maximization non-dominated sorting genetic algorithm (DM-NSGA)-II is developed to perform multi-objective optimization by considering the power load profile, the users’charging cost, and battery degradation. Furthermore, a real-time locally optimal schedule is adopted by utilizing a flexible time scale. The case study illustrates that the proposed DM-NSGA-II can prevent being trapped in a relatively limited region so as to diversify the optimal results and provide trade-off solutions to decision makers. The simulation analysis shows that the variable time scale can continuously involve the present EVs in the real-time optimization rather than rely on the forecasting data. The schedule of the EV load is more practical without the loss of accuracy.
