The research results show that using iterative learning control algorithm can improve the tracing accurate of the force system.
研究结果表明，采用迭代学习控制算法可以有效地提高力系统的跟随精度。
Ensemble learning is a research hotspot in machine learning, which can improve generalization performance of classification algorithm.
集成学习是当前机器学习的一个研究热点，它可以提高分类算法的泛化性能。
Compared with RBF Network, it is concluded that learning algorithm is master key to improve properties of Artificial Neural Network.
与工具箱的RBF网络相比较，说明网络的学习算法是改善网络性能的关键。
For accelerating the algorithm convergence and avoiding the local optimization, an individual learning mechanism is often applied to generic algorithm to improve algorithm performance.
在遗传算法中引入个体学习机制能够提高算法的性能，避免算法收敛过慢或陷入局部最优。
Locally linear embedding (LLE) is a widely-used manifold learning algorithm, in this paper we improve on the algorithm and put it to use in spatial data index.
局部线性嵌入方法是一种应用广泛的流形学习方法，本文提出算法的一种改进，并将其应用于空间数据索引。
The algorithm selects training samples by local sample density, to reduce the training samples and thus to improve the speed of learning.
该算法根据样本的局部密度选择训练样本，减少参加训练的样本数量，提高学习速度。
We integrate the Sparse Bayesian Learning algorithm into the SMC blind receiver to improve the performance under sparse channels.
我们将稀疏贝叶斯学习与序列蒙特卡罗盲均衡算法结合，提高了原算法的性能。
Meanwhile, parameter learning algorithm of the membership function is developed. Both of them improve diagnostic rules as well as learning properties.
提出了部分层学习算法，并推导出隶属度函数的参数学习算法，改善了诊断规则和学习性能。
By adopting the value iterative strategies of reinforcement learning, the algorithm can absorb the corresponding knowledge from its environment during its running and improve its search ability.
该算法采用强化学习中值迭代策略，在运行中能够从环境中获取相应知识，提高其搜索能力。
A parameter self-learning algorithm is presented after defining data structure and variable array to improve the prototype's adaptability to different size of workpieces.
在定义了数据结构和变量数组的基础上，给出了参数自学习过程算法，改善了模型样机对不同规格样本工件的适应性。
The simulation results show the presented quick training algorithm can speed up the learning process of MLP, and improve the learning properties on convergence and robust performance.
仿真结果表明，改进的BP算法可显著加速网络训练速度，学习过程具有较好的收敛性和较强的鲁棒性。
The simulation results show the presented quick training algorithm can speed up the learning process of MLP, and improve the learning properties on convergence and robust performance.
仿真结果表明，改进的BP算法可显著加速网络训练速度，学习过程具有较好的收敛性和较强的鲁棒性。
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