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首页> 外文期刊>Irrigazione e Drenaggio >Neural networks in agricultural and environmental monitoring
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Neural networks in agricultural and environmental monitoring

机译：农业和环境监测中的神经网络

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摘要

Recently, some new computing technologies have been used in modelling applications (artificial neural networks, fuzzy systems, expert systems, genetic algorithms, etc.). The artificial neural networks are the most important among these technologies.In this work, we provide rudiments of neural networks and analyse properties, advantages and limitations of this technique. We also describe some of the more common applications of neural networks in agrometeorological and environmental modelling. Neural networks exhibit the capability to map the input/output relationship and to make an internal function of phenomena from the example data. Moreover, neural networks perform well in complex non-linear problems and when inputs are incomplete or affected by measurement errors. These characteristics are very useful in agrometeorological and environmental modelling. The review of neural network applications points out the advantages of this technique compared to traditional analytical approaches.
机译：最近，一些新的计算技术已用于建模应用程序（人工神经网络，模糊系统，专家系统，遗传算法等）。人工神经网络是这些技术中最重要的。在这项工作中，我们提供了神经网络的基础知识，并分析了该技术的性质，优点和局限性。我们还描述了神经网络在农业气象和环境建模中的一些更常见的应用。神经网络具有映射输入/输出关系并从示例数据中构造现象的内部功能的能力。此外，当输入不完整或受测量误差影响时，神经网络在复杂的非线性问题中表现良好。这些特征在农业气象和环境建模中非常有用。对神经网络应用的回顾指出了与传统分析方法相比该技术的优势。

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