UC知道简单的英文文献翻译（英译汉）
来源：百度知道 编辑：UC知道 时间：2024/06/30 21:17:55
哪位英语高手可以帮我翻译一下这篇人工神经网络方面的英文文献？不要直接用软件翻译，要准确通顺的翻译，谢谢。
We propose a method to evolve adaptive behavior
of learning in an artificial neural network (ANN). The
adaptive behavior of learning emerges from the coordination
of learning rules. Each learning rule is defined as a
function of local information of a corresponding neuron
only and modifies the connective strength between the neuron
and its neighbors. It is exposed to selective pressure
based on the fitness value, which represents the importance
in producing the correct output signals of the ANN. The
learning rules with lower fitness values are replaced by new
ones generated by genetic programming techniques. Experimental
results demonstrate that the proposed method
produces adaptive behavior of learning in single-layered
and two-layered ANNs. This means that efficient learning
rules evolve 9 Further, the learning rules in the two-layered
ANN coordinate w
We propose a method to evolve adaptive behavior
of learning in an artificial neural network (ANN). The
adaptive behavior of learning emerges from the coordination
of learning rules. Each learning rule is defined as a
function of local information of a corresponding neuron
only and modifies the connective strength between the neuron
and its neighbors. It is exposed to selective pressure
based on the fitness value, which represents the importance
in producing the correct output signals of the ANN. The
learning rules with lower fitness values are replaced by new
ones generated by genetic programming techniques. Experimental
results demonstrate that the proposed method
produces adaptive behavior of learning in single-layered
and two-layered ANNs. This means that efficient learning
rules evolve 9 Further, the learning rules in the two-layered
ANN coordinate w
我们提出一个演变适应性行为的方法学会在一个人工神经网络(ANN)。
这种适应性行为表现为学会从学会规则的协调涌现。 每个学习的规则被定义作为仅一个对应的神经元的地方信息功能并且修改在神经元和它的邻居之间的连通性力量。 它被暴露在根据健身价值的有选择性的压力，代表在导致ANN的正确输出信号的重要性。 与更加低值的健身的学习的规则被基因编程技术引起的新的替换。 实验性结果显示出，提出的方法引起适应性行为学会在唯一层状和两层的ANN。 这意味着那高效率的学习的规则演变成9类引深，在两层的ANN座标的学习的规则互相，并且宏观适应性行为学会涌现。