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Classification Problem of ANN in Assessment of Environmental Quality

机译:环境质量评价中的人工神经网络分类问题

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The advantage of artificial neural network is that there is no need to devise a mathematical model in order to perform a specific task. It processes information through interconnected processing elements (neurons). In assessment of environmental quality, ANN is an efficient and objective classification method. However according to our experience, ANN produces are not always comply with real situation, and sometimes, it can cause large errors with testing samples. These problems are caused by the nature of ANN itself. Studying of these problems increases our understanding of ANN classification.
机译:人工神经网络的优势在于,无需设计数学模型即可执行特定任务。它通过互连的处理元件(神经元)处理信息。在环境质量评估中,人工神经网络是一种高效,客观的分类方法。但是,根据我们的经验,人工神经网络产生的结果并不总是符合实际情况,有时可能会导致测试样本出现较大误差。这些问题是由人工神经网络本身的性质引起的。对这些问题的研究提高了我们对ANN分类的理解。

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