针对不规则区域面积测算中定位精度和面积计算精度两方面不足,提出一种定位精度高、面积误差小的面积测算新方法。其采用一种组合定位方法精确定位,即将差分GPS测量系统(DGPS)与马尔可夫链蒙特卡罗(Markov chain Monte Carol,MCMC)粒子...针对不规则区域面积测算中定位精度和面积计算精度两方面不足,提出一种定位精度高、面积误差小的面积测算新方法。其采用一种组合定位方法精确定位,即将差分GPS测量系统(DGPS)与马尔可夫链蒙特卡罗(Markov chain Monte Carol,MCMC)粒子滤波相结合,再配合复化Newton-cotes算法,拟合边界曲线并准确求得区域面积。将MCMC粒子滤波应用于DGPS定位数据处理,其既可处理非高斯分布噪声,又解决粒子滤波(PF)的粒子退化问题,提高定位精度。将复化Newton-cotes算法应用于面积计算,其既避免高次插值的舍入误差,又将面积区间进一步细分,提高面积计算精度。实验结果表明,该新方法定位精度更高,面积误差更小。展开更多
Being as unique nonlinear components of block ciphers,substitution boxes（S-boxes） directly affect the security of the cryptographic systems.It is important and difficult to design cryptographically strong S-boxes th...Being as unique nonlinear components of block ciphers,substitution boxes（S-boxes） directly affect the security of the cryptographic systems.It is important and difficult to design cryptographically strong S-boxes that simultaneously meet with multiple cryptographic criteria such as bijection,non-linearity,strict avalanche criterion（SAC）,bits independence criterion（BIC）,differential probability（DP） and linear probability（LP）.To deal with this problem,a chaotic S-box based on the artificial bee colony algorithm（CSABC） is designed.It uses the S-boxes generated by the six-dimensional compound hyperchaotic map as the initial individuals and employs ABC to improve their performance.In addition,it considers the nonlinearity and differential uniformity as the fitness functions.A series of experiments have been conducted to compare multiple cryptographic criteria of this algorithm with other algorithms.Simulation results show that the new algorithm has cryptographically strong S-box while meeting multiple cryptographic criteria.展开更多
In this paper, a compound biped locomotion algorithm for a humanoid robot under development is presented. This paper is organized in two main parts. In the first part, it mainly focuses on the structural design for th...In this paper, a compound biped locomotion algorithm for a humanoid robot under development is presented. This paper is organized in two main parts. In the first part, it mainly focuses on the structural design for the humanoid. In the second part, the compound biped locomotion algorithm is presented based on the reference motion and reference Zero Moment Point （ZMP）. This novel algorithm includes calculation of the upper body motion and trajectory of the Center of Gravity （COG） of the robot. First, disturbances from the environment are eliminated by the compensational movement of the upper body; then based on the error between a reference ZMP and the real ZMP as well as the relation between ZMP and CoG, the CoG error is calculated, thus leading to the CoG trajectory. Then, the motion of the robot converges to its reference motion, generating stable biped walking. Because the calculation of upper body motion and trajectory of CoG both depend on the reference motion, they can work in parallel, thus providing double insurances against the robot＇s collapse. Finally, the algorithm is validated by different kinds of simulation experiments.展开更多
In the present work,we have employed machine learning(ML)techniques to evaluate ductile-brittle(DB)behaviors in intermetallic compounds(IMCs)which can form magnesium(Mg)alloys.This procedure was mainly conducted by a ...In the present work,we have employed machine learning(ML)techniques to evaluate ductile-brittle(DB)behaviors in intermetallic compounds(IMCs)which can form magnesium(Mg)alloys.This procedure was mainly conducted by a proxy-based method,where the ratio of shear(G)/bulk(B)moduli was used as a proxy to identify whether the compound is ductile or brittle.Starting from compounds information(composition and crystal structure)and their moduli,as found in open databases(AFLOW),ML-based models were built,and those models were used to predict the moduli in other compounds,and accordingly,to foresee the ductile-brittle behaviors of these new compounds.The results reached in the present work showed that the built models can effectively catch the elastic moduli of new compounds.This was confirmed through moduli calculations done by density functional theory(DFT)on some compounds,where the DFT calculations were consistent with the ML prediction.A further confirmation on the reliability of the built ML models was considered through relating between the DB behavior in MgBe_(13) and MgPd_(2),as evaluated by the ML-predicted moduli,and the nature of chemical bonding in these two compounds,which in turn,was investigated by the charge density distribution(CDD)and electron localization function(ELF)obtained by DFT methodology.The ML-evaluated DB behaviors of the two compounds was also consistent with the DFT calculations of CDD and ELF.These findings and confirmations gave legitimacy to the built model to be employed in further prediction processes.Indeed,as examples,the DB characteristics were investigated in IMCs that might from in three Mg alloy series,involving AZ,ZX and WE.展开更多
TheHoney Badger Algorithm(HBA)is a novelmeta-heuristic algorithm proposed recently inspired by the foraging behavior of honey badgers.The dynamic search behavior of honey badgers with sniffing and wandering is divided...TheHoney Badger Algorithm(HBA)is a novelmeta-heuristic algorithm proposed recently inspired by the foraging behavior of honey badgers.The dynamic search behavior of honey badgers with sniffing and wandering is divided into exploration and exploitation in HBA,which has been applied in photovoltaic systems and optimization problems effectively.However,HBA tends to suffer from the local optimum and low convergence.To alleviate these challenges,an improved HBA(IHBA)through fusing multi-strategies is presented in the paper.It introduces Tent chaotic mapping and composite mutation factors to HBA,meanwhile,the random control parameter is improved,moreover,a diversified updating strategy of position is put forward to enhance the advantage between exploration and exploitation.IHBA is compared with 7 meta-heuristic algorithms in 10 benchmark functions and 5 engineering problems.The Wilcoxon Rank-sum Test,Friedman Test and Mann-WhitneyU Test are conducted after emulation.The results indicate the competitiveness and merits of the IHBA,which has better solution quality and convergence traits.The source code is currently available from:https://github.com/zhaotao789/IHBA.展开更多
文摘针对不规则区域面积测算中定位精度和面积计算精度两方面不足,提出一种定位精度高、面积误差小的面积测算新方法。其采用一种组合定位方法精确定位,即将差分GPS测量系统(DGPS)与马尔可夫链蒙特卡罗(Markov chain Monte Carol,MCMC)粒子滤波相结合,再配合复化Newton-cotes算法,拟合边界曲线并准确求得区域面积。将MCMC粒子滤波应用于DGPS定位数据处理,其既可处理非高斯分布噪声,又解决粒子滤波(PF)的粒子退化问题,提高定位精度。将复化Newton-cotes算法应用于面积计算,其既避免高次插值的舍入误差,又将面积区间进一步细分,提高面积计算精度。实验结果表明,该新方法定位精度更高,面积误差更小。
基金supported by the National Natural Science Foundation of China(6060309260975042)
文摘Being as unique nonlinear components of block ciphers,substitution boxes（S-boxes） directly affect the security of the cryptographic systems.It is important and difficult to design cryptographically strong S-boxes that simultaneously meet with multiple cryptographic criteria such as bijection,non-linearity,strict avalanche criterion（SAC）,bits independence criterion（BIC）,differential probability（DP） and linear probability（LP）.To deal with this problem,a chaotic S-box based on the artificial bee colony algorithm（CSABC） is designed.It uses the S-boxes generated by the six-dimensional compound hyperchaotic map as the initial individuals and employs ABC to improve their performance.In addition,it considers the nonlinearity and differential uniformity as the fitness functions.A series of experiments have been conducted to compare multiple cryptographic criteria of this algorithm with other algorithms.Simulation results show that the new algorithm has cryptographically strong S-box while meeting multiple cryptographic criteria.
基金supported by the National Natural Science Foundation of China (No.60375031)General Administration of Civil Aviation of China(No.60776816)the Natural Science Foundation of Guangdong Province (No.8251064101000005)
文摘In this paper, a compound biped locomotion algorithm for a humanoid robot under development is presented. This paper is organized in two main parts. In the first part, it mainly focuses on the structural design for the humanoid. In the second part, the compound biped locomotion algorithm is presented based on the reference motion and reference Zero Moment Point （ZMP）. This novel algorithm includes calculation of the upper body motion and trajectory of the Center of Gravity （COG） of the robot. First, disturbances from the environment are eliminated by the compensational movement of the upper body; then based on the error between a reference ZMP and the real ZMP as well as the relation between ZMP and CoG, the CoG error is calculated, thus leading to the CoG trajectory. Then, the motion of the robot converges to its reference motion, generating stable biped walking. Because the calculation of upper body motion and trajectory of CoG both depend on the reference motion, they can work in parallel, thus providing double insurances against the robot＇s collapse. Finally, the algorithm is validated by different kinds of simulation experiments.
基金supported by National Research Foundation(NRF)of South Korea(2020R1A2C1004720)。
文摘In the present work,we have employed machine learning(ML)techniques to evaluate ductile-brittle(DB)behaviors in intermetallic compounds(IMCs)which can form magnesium(Mg)alloys.This procedure was mainly conducted by a proxy-based method,where the ratio of shear(G)/bulk(B)moduli was used as a proxy to identify whether the compound is ductile or brittle.Starting from compounds information(composition and crystal structure)and their moduli,as found in open databases(AFLOW),ML-based models were built,and those models were used to predict the moduli in other compounds,and accordingly,to foresee the ductile-brittle behaviors of these new compounds.The results reached in the present work showed that the built models can effectively catch the elastic moduli of new compounds.This was confirmed through moduli calculations done by density functional theory(DFT)on some compounds,where the DFT calculations were consistent with the ML prediction.A further confirmation on the reliability of the built ML models was considered through relating between the DB behavior in MgBe_(13) and MgPd_(2),as evaluated by the ML-predicted moduli,and the nature of chemical bonding in these two compounds,which in turn,was investigated by the charge density distribution(CDD)and electron localization function(ELF)obtained by DFT methodology.The ML-evaluated DB behaviors of the two compounds was also consistent with the DFT calculations of CDD and ELF.These findings and confirmations gave legitimacy to the built model to be employed in further prediction processes.Indeed,as examples,the DB characteristics were investigated in IMCs that might from in three Mg alloy series,involving AZ,ZX and WE.
基金supported by National Science Foundation of China(Grant No.52075152)Xining Big Data Service Administration.
文摘TheHoney Badger Algorithm(HBA)is a novelmeta-heuristic algorithm proposed recently inspired by the foraging behavior of honey badgers.The dynamic search behavior of honey badgers with sniffing and wandering is divided into exploration and exploitation in HBA,which has been applied in photovoltaic systems and optimization problems effectively.However,HBA tends to suffer from the local optimum and low convergence.To alleviate these challenges,an improved HBA(IHBA)through fusing multi-strategies is presented in the paper.It introduces Tent chaotic mapping and composite mutation factors to HBA,meanwhile,the random control parameter is improved,moreover,a diversified updating strategy of position is put forward to enhance the advantage between exploration and exploitation.IHBA is compared with 7 meta-heuristic algorithms in 10 benchmark functions and 5 engineering problems.The Wilcoxon Rank-sum Test,Friedman Test and Mann-WhitneyU Test are conducted after emulation.The results indicate the competitiveness and merits of the IHBA,which has better solution quality and convergence traits.The source code is currently available from:https://github.com/zhaotao789/IHBA.
