Examples of using Artificial neural network in English and their translations into Chinese
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Currently, the research team plans to design an artificial neural network that can learn to form“memory” from instances added to the test tube.
目前，研究小组计划设计一个人工神经网络，它能够学习、从添加到试管的实例中形成“记忆”。Now[this] is possible the use of millions of data to train an artificial neural network toward the identification of unknown drug-target interactions.
现在有可能利用数以百万计的数据来训练一个人工神经网络，以识别未知的药物靶相互作用。Geostatistical models and artificial neural network techniques were used in the temporal and spatial evaluation of evapotranspiration in Cuba.
使用地质统计模型和仿真神经网络技术对古巴蒸散情况进行了时空评价。However, before going any further, we first have to understand what an Artificial Neural Network or ANN is.
ANN Visualizer is a python library that enables us to visualize an Artificial Neural Network using just a single line of code.
ANNVisualizer同样是一个Python库，它让我们仅用一行代码即可实现人工智能神经网络。At the heart of the program is a group of software“neurons” that are connected together to form an artificial neural network.
系统的核心是一组软件上的「神经元」，这些「神经元」连接在一起，形成一个人工的神经网络。In both cases the result is an Artificial Neural Network(ANN) that contains all the information necessary to carry out the task.
这两种情况最后都产生一个包含执行任务所需的全部信息的人工神经网络（ANN）。Now Shelley's artificial neural network is generating its own stories, posting opening lines on Twitter, then taking turns with humans in collaborative storytelling.
现在，Shelley的人工神经网络正在创作它自己的故事，并在Twitter上发布了开头部分，然后与人类合作，轮流讲述这个故事。An artificial neural network consists of"nodes" that, like individual neurons, have limited information-processing power but are densely interconnected.
一个人工神经网络包含一系列结点（nodes），这些节点就如一个个神经元，单个结点的信息处理能力有限，但结点之间的相互联系非常稠密。Posted to arXiv earlier this month, the paper describes an artificial neural network called Creatism that is a"system for artistic content creation.".
本月初发表在arXiv上的这篇论文称，研究院已经发明了一种名为Creatism的人工神经网络，是一种“艺术创造系统”。SOLUTIONS MANUAL: Artificial Neural Networks by B.
Ann:人工神经网络（ArtificialNeuralNetworks）b….Researchers are trying to build artificial neural networks that can appropriately adjust to new information without abruptly forgetting what they learned before.
研究人员正试图建立人工神经网络，可以适当地适应新的信息，而不会突然忘记他们以前学过的东西。With its extensive range of libraries, you can build various applications in artificial neural networks, statistical data processing, image processing, and many others.
凭借其广泛的库，你可以在人工神经网络，统计数据处理，图像处理等中构建各种应用。For example, biologically plausible deep/recurrent artificial neural networks are learning to solve pattern recognition tasks that seemed infeasible only 10 years ago.
例如，生物合理深/复发人工神经网络的学习来解决，只有10年前似乎是不可行的模式识别任务。McCulloch and Pitts developed the first variants of what are now known as artificial neural networks, models of computation inspired by the structure of biological neural networks. .
麦卡洛特和皮茨发展了我们今天称为人工神经网络的最早版本，来源于生物神经网络结构的计算模型。Despite their massive size, successful deep artificial neural networks can exhibit a remarkably small difference between training and test performance.
尽管体积巨大，成功的深度人工神经网络在训练和测试性能之间可以展现出非常小的差异。Artificial neural networks, which are computer systems modeled on the human brain and nervous system, and deep learning are also responsible for advances in AI.
人工神经网络是模仿人类大脑和神经系统的计算机系统，而深度学习也是AI进步的原因。Modern artificial neural networks are composed of an array of software components, divided into inputs, hidden layers and outputs.
现代人工神经网络由一系列软件组成，分为输入、隐藏层和输出几个部分。Researchers are trying to build artificial neural networks that can appropriately adjust to new information without abruptly forgetting what they learned before.
研究人员正试图建立人工神经网络，以便在突然忘记之前学过的东西的情况下，适当地调整新信息。Most artificial neural networks have two things in common: a huge number of weights, which are essentially the tunable parameters that networks learn during training;
大多数人工神经网络有两个共同点:大量的权值，本质上是网络在训练中学习的可调参数;
