1)  Alopex
Alopex
1.
An Dynamical Evolutionary Algorithm Improved by Alopex;
利用Alopex改进的动力学演化算法
2.
Improved Particle Swarm Optimization Algorithms by Alopex and Its Application in Soft Sensor Modeling;
利用Alopex改进的粒子群优化算法及其在软测量建模中的应用
3.
Aimed at the disadvantages of basic differential evolution algorithm,presents an improved differential algorithm(IDE) based on Alopex(algorithms of pattern extraction)and BP algorithm with self-adapting learning-rate,first of all IDE would be used to optimize the weights of neural network and then in order to obtain better performance,the LM algorithm is applied to optimize the pa- rameters.
针对基本差分进化法搜索精度不高,容易陷入局部最优的缺点,提出基于Alopex改进的差分进化法和自适应学习速率的BP神经网络相结合的学习法,首先运用改进的差分进化法来寻找满意的神经网络参数;然后调用自适应学习速率的LM法精调网络参数。
2)  Alopex algorithm
Alopex算法
1.
Alopex algorithm is an effective random optimization algorithm that can search the most optimum answer quickly .
Alopex算法是一种有效的随机优化算法 ,能尽快向最优解方向搜索 。
2.
A hybrid algorithm, APSO, was proposed by combining particle swarm optimization (PSO) with Alopex algorithm that is a stochastic optimization method, for solving constrained optimization problems.
将微粒群算法(Particle Swarm Optimization,PSO)与随机优化方法-Alopex算法相结合,提出一种随机微粒群混合算法(APSO)求解约束优化问题。
3.
A stochastic optimization algorithm,AACO,is proposed by combining ant colony optimization(ACO) algorithm with Alopex algorithm that is a stochastic optimization method for solving continuous space optimization problems.
通过将蚁群优化算法(ant colony optimization,ACO)与一种随机优化方法———Alopex算法相结合,提出一种随机蚁群混合算法(AACO)求解连续空间优化问题。
3)  Alopex algorithm
Alopex方法
1.
For the power system equipped with on-load tap changers and shunt capacitors in electricity marke, this paper proposes a sectionalized reactive power optimization method, which combines genetic and Alopex algorithm.
该方法采用了遗传算法和Alopex方法相结合,能够在满足当日内变压器分接头和补偿电容动作次数约束和电压合格率的条件下,有效地降低网损。
4)  Alopex-B
Alopex-B算法
1.
Particle swarm optimization algorithm and Alopex-B algorithm are introduced.
介绍了粒子群优化算法和Alopex-B算法的基本原理,提出了一种用Alopex-B算法改进的粒子群优化算法,并将其应用于函数优化和有机物毒性的QSAR研究。
5)  aluminum
Al
1.
Effects of ferric oxide removal on adsorption and desorption of aluminum in soils;
去除氧化铁对Al在土壤中吸附-解吸的影响
2.
Studies on marine biogeochemistry of aluminum;
Al的海洋生物地球化学研究
3.
The Impacts of Aluminum on the Abnormal Aggregation of R3 Peptide of Tau Protein and Its Mechanism;
Al离子对tau蛋白R3多肽异常聚集的影响及其机理
6)  Al
Al
1.
EAM CALCULATION OF FORMATION ENTHALPIES OF Al,Li AND Mg(Ti) INTERMETALLIC COMPOUNDS;
Al-Li-Mg(Ti)合金形成焓的EAM研究
2.
ICP-AES Determination of Mn,Si,Al,Ti,Nb,La in Ultrahigh Strength Steel;
ICP-AES法测定超高强度钢中Mn,Si,Al,Ti,Nb,La杂质元素
3.
Effects of Al and Ca Additions on Microstructure and Creep Properties of Magnesium Alloys;
Al,Ca元素对镁合金显微组织及蠕变性能的影响
参考词条
补充资料：BP算法
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性质：又称逆推学习算法，简称BP算法，是1986年鲁梅哈特(D. E. Rumelhart)和麦克莱朗德(J. L. McClelland)提出来的。用样本数据训练人工神经网络(一种模仿人脑的信息处理系统)，它自动地将实际输出值和期望值进行比较，得到误差信号，再根据误差信号从后(输出层)向前(输入层)逐层反传，调节各神经层神经元之间的连接权重，直至误差减至满足要求为止。反向传播算法的主要特征是中间层能对输出层反传过来的误差进行学习。这种算法不能保证训练期间实现全局误差最小，但可以实现局部误差最小。BP算法在图像处理、语音处理、优化等领域得到应用。

说明：补充资料仅用于学习参考，请勿用于其它任何用途。