With an aim to the fact that the K-means clustering algorithm usually ends in local optimization and is hard to harvest global optimization, a new web clustering method is presented based on the chaotic social evoluti...With an aim to the fact that the K-means clustering algorithm usually ends in local optimization and is hard to harvest global optimization, a new web clustering method is presented based on the chaotic social evolutionary programming （CSEP） algorithm. This method brings up the manner of that a cognitive agent inherits a paradigm in clustering to enable the cognitive agent to acquire a chaotic mutation operator in the betrayal. As proven in the experiment, this method can not only effectively increase web clustering efficiency, but it can also practically improve the precision of web clustering.展开更多
Co-ordination of directional over current relays(DOCR) requires the selection and setting of relays so as to sequentially isolate only that portion of the power system where an abnormality has occurred.The problem of ...Co-ordination of directional over current relays(DOCR) requires the selection and setting of relays so as to sequentially isolate only that portion of the power system where an abnormality has occurred.The problem of coordinating protective relays in electrical power systems consists of selecting suitable settings such that their fundamental protective function is met,given operational requirements of sensitivity,selectivity,reliability and speed.Directional over current relays are best suited for protection of an interconnected sub-station transmission system.One of the major problems associated with this type of protection is the difficulty in coordinating relays.To insure proper coordination,all the main/back up relay pairs must be determined.This paper presents an effective algorithm to determine the minimum number of break points and main/back up relay pairs using relative sequence matrix(RSM).A novel optimization technique based on evolutionary programming was developed using these main/back up relay pairs for directional over current relay coordination in multi-loop networks.Since the problem has multi-optimum points,conventional mathematics based optimization techniques may sometimes fail.Hence evolutionary programming(EP) was used,as it is a stochastic multi-point search optimization algorithm capable of escaping from the local optimum problem,giving a better chance of reaching a global optimum.The method developed was tested on an existing 6 bus,7 line system and better results were obtained than with conventional methods.展开更多
交替方向乘子法(Alternating Direction Method of Multiplier,ADMM)因具有线性规划(Linear Programming,LP)译码条件约束的几何结构,同时利用了消息传递机制,被认为是一种第5代移动通信技术(5th Generation Mobile Communication Techn...交替方向乘子法(Alternating Direction Method of Multiplier,ADMM)因具有线性规划(Linear Programming,LP)译码条件约束的几何结构,同时利用了消息传递机制,被认为是一种第5代移动通信技术(5th Generation Mobile Communication Technology,5G)低密度校验(Low Density Parity Check,LDPC)码新型优化译码算法。通过在LP译码模型的目标函数中引入惩罚项,基于ADMM的变量节点惩罚译码有效地减轻了非积分解,从而提高了误帧率(Frame Error Rate,FER)性能。尽管ADMM在许多实际应用中表现出色,其收敛速度较慢以及对初始条件和参数设置敏感的问题仍然限制了其在高维、实时性要求高的场景中的进一步应用。特别是在LDPC线性规划译码过程中,ADMM的交替更新机制容易导致优化路径振荡,且在处理非精确约束时表现不佳。针对ADMM算法收敛速度慢的问题,我们提出了一种新的优化算法,该算法将Nesterov动量加速方法与ADMM相结合,以解决ADMM对LDPC译码器错误修正能力和收敛效率的影响。算法通过动量项减少迭代次数将一个Nesterov加速格式从无约束复合优化问题推广到ADMM惩罚函数模型,利用ADMM算法将原问题的约束条件有效转化为目标函数的一部分,从而构造出无约束优化子问题;在此基础上,进一步采用Nesterov加速技术对梯度下降迭代过程进行改进,以提高收敛速度和求解精度。仿真实验使用了三种不同码率的5G LDPC短码。结果表明,相对于现有ADMM惩罚译码算法,所提出的基于动量加速的ADMM译码算法不仅有大约0.2 dB的信噪比增益,而且平均迭代次数也降低了20%左右,加快了收敛速度。展开更多
In the field of calculating the attack area of air-to-air missiles in modern air combat scenarios,the limitations of existing research,including real-time calculation,accuracy efficiency trade-off,and the absence of t...In the field of calculating the attack area of air-to-air missiles in modern air combat scenarios,the limitations of existing research,including real-time calculation,accuracy efficiency trade-off,and the absence of the three-dimensional attack area model,restrict their practical applications.To address these issues,an improved backtracking algorithm is proposed to improve calculation efficiency.A significant reduction in solution time and maintenance of accuracy in the three-dimensional attack area are achieved by using the proposed algorithm.Furthermore,the age-layered population structure genetic programming(ALPS-GP)algorithm is introduced to determine an analytical polynomial model of the three-dimensional attack area,considering real-time requirements.The accuracy of the polynomial model is enhanced through the coefficient correction using an improved gradient descent algorithm.The study reveals a remarkable combination of high accuracy and efficient real-time computation,with a mean error of 91.89 m using the analytical polynomial model of the three-dimensional attack area solved in just 10^(-4)s,thus meeting the requirements of real-time combat scenarios.展开更多
针对遗传规划算法容易陷入局部最优解与局部搜索过慢的问题,提出一种基于语义聚类的遗传规划算法(genetic programming algorithm based on semantic clustering,SCGP),比较不同聚类算法对SCGP表现的影响。同时提出一种基于子种群规模...针对遗传规划算法容易陷入局部最优解与局部搜索过慢的问题,提出一种基于语义聚类的遗传规划算法(genetic programming algorithm based on semantic clustering,SCGP),比较不同聚类算法对SCGP表现的影响。同时提出一种基于子种群规模的自适应适应度函数,提高局部搜索能力。在多个基准问题上对比标准遗传规划、几何语义遗传规划、K均值聚类遗传规划与SCGP,实验结果表明,SCGP算法在拟合能力和泛化能力上都有较大改善。在诸多聚类方法中,层次聚类嵌入的SCGP算法在基准问题上的泛化能力最优,与标准遗传规划、几何语义遗传规划、K均值聚类遗传规划相比,分别提高了32.36%、61.29%、20.53%。展开更多
文摘With an aim to the fact that the K-means clustering algorithm usually ends in local optimization and is hard to harvest global optimization, a new web clustering method is presented based on the chaotic social evolutionary programming （CSEP） algorithm. This method brings up the manner of that a cognitive agent inherits a paradigm in clustering to enable the cognitive agent to acquire a chaotic mutation operator in the betrayal. As proven in the experiment, this method can not only effectively increase web clustering efficiency, but it can also practically improve the precision of web clustering.
文摘Co-ordination of directional over current relays(DOCR) requires the selection and setting of relays so as to sequentially isolate only that portion of the power system where an abnormality has occurred.The problem of coordinating protective relays in electrical power systems consists of selecting suitable settings such that their fundamental protective function is met,given operational requirements of sensitivity,selectivity,reliability and speed.Directional over current relays are best suited for protection of an interconnected sub-station transmission system.One of the major problems associated with this type of protection is the difficulty in coordinating relays.To insure proper coordination,all the main/back up relay pairs must be determined.This paper presents an effective algorithm to determine the minimum number of break points and main/back up relay pairs using relative sequence matrix(RSM).A novel optimization technique based on evolutionary programming was developed using these main/back up relay pairs for directional over current relay coordination in multi-loop networks.Since the problem has multi-optimum points,conventional mathematics based optimization techniques may sometimes fail.Hence evolutionary programming(EP) was used,as it is a stochastic multi-point search optimization algorithm capable of escaping from the local optimum problem,giving a better chance of reaching a global optimum.The method developed was tested on an existing 6 bus,7 line system and better results were obtained than with conventional methods.
文摘交替方向乘子法(Alternating Direction Method of Multiplier,ADMM)因具有线性规划(Linear Programming,LP)译码条件约束的几何结构,同时利用了消息传递机制,被认为是一种第5代移动通信技术(5th Generation Mobile Communication Technology,5G)低密度校验(Low Density Parity Check,LDPC)码新型优化译码算法。通过在LP译码模型的目标函数中引入惩罚项,基于ADMM的变量节点惩罚译码有效地减轻了非积分解,从而提高了误帧率(Frame Error Rate,FER)性能。尽管ADMM在许多实际应用中表现出色,其收敛速度较慢以及对初始条件和参数设置敏感的问题仍然限制了其在高维、实时性要求高的场景中的进一步应用。特别是在LDPC线性规划译码过程中,ADMM的交替更新机制容易导致优化路径振荡,且在处理非精确约束时表现不佳。针对ADMM算法收敛速度慢的问题,我们提出了一种新的优化算法,该算法将Nesterov动量加速方法与ADMM相结合,以解决ADMM对LDPC译码器错误修正能力和收敛效率的影响。算法通过动量项减少迭代次数将一个Nesterov加速格式从无约束复合优化问题推广到ADMM惩罚函数模型,利用ADMM算法将原问题的约束条件有效转化为目标函数的一部分,从而构造出无约束优化子问题;在此基础上,进一步采用Nesterov加速技术对梯度下降迭代过程进行改进,以提高收敛速度和求解精度。仿真实验使用了三种不同码率的5G LDPC短码。结果表明,相对于现有ADMM惩罚译码算法,所提出的基于动量加速的ADMM译码算法不仅有大约0.2 dB的信噪比增益,而且平均迭代次数也降低了20%左右,加快了收敛速度。
基金National Natural Science Foundation of China(62373187)Forward-looking Layout Special Projects(ILA220591A22)。
文摘In the field of calculating the attack area of air-to-air missiles in modern air combat scenarios,the limitations of existing research,including real-time calculation,accuracy efficiency trade-off,and the absence of the three-dimensional attack area model,restrict their practical applications.To address these issues,an improved backtracking algorithm is proposed to improve calculation efficiency.A significant reduction in solution time and maintenance of accuracy in the three-dimensional attack area are achieved by using the proposed algorithm.Furthermore,the age-layered population structure genetic programming(ALPS-GP)algorithm is introduced to determine an analytical polynomial model of the three-dimensional attack area,considering real-time requirements.The accuracy of the polynomial model is enhanced through the coefficient correction using an improved gradient descent algorithm.The study reveals a remarkable combination of high accuracy and efficient real-time computation,with a mean error of 91.89 m using the analytical polynomial model of the three-dimensional attack area solved in just 10^(-4)s,thus meeting the requirements of real-time combat scenarios.
文摘针对遗传规划算法容易陷入局部最优解与局部搜索过慢的问题,提出一种基于语义聚类的遗传规划算法(genetic programming algorithm based on semantic clustering,SCGP),比较不同聚类算法对SCGP表现的影响。同时提出一种基于子种群规模的自适应适应度函数,提高局部搜索能力。在多个基准问题上对比标准遗传规划、几何语义遗传规划、K均值聚类遗传规划与SCGP,实验结果表明,SCGP算法在拟合能力和泛化能力上都有较大改善。在诸多聚类方法中,层次聚类嵌入的SCGP算法在基准问题上的泛化能力最优,与标准遗传规划、几何语义遗传规划、K均值聚类遗传规划相比,分别提高了32.36%、61.29%、20.53%。
