应用人工神经网络识别闽南粤东沿海老红沙沉积

闽南、粤东沿海,断续分布着一种俗称"老红砂"的红色、棕红色半胶结的中细砂沉积物。近十多年来,对其成因和时代进行了较多研究。然而,关于它的成因,目前仍有争议,有的认为是属于一种近源的滨海相沉积,也有人认为是风成的。本文用经过华南沿海现代海岸风成沙和海滩沙样品训练的神经网络来识别闽南粤东沿海的老红砂。由这些海岸风沙和海滩沙的粒度参数、沉积物的各个粒级含量等作为输入,构成不同的神经网络的识别结果表明,大部分老红砂被神经网络判别为风沙沉积,同时也表明,粉沙/粘土的含量是判别沉积物是否为风沙搬运的有效指标。而单纯以沉积物各个粒级含量作为输入构成的网络无法用于沉积物的识别。

Identification of the "Old Red Sand" on Southern Fujian and Eastern Guangdong Coasts with Artificial Neural Networks

The so-called !old red sands" are semi-cemented fine and medium sands with colors in red or brown red, distributing along the coasts in the southern Fujian and eastern Guangdong provinces, China. In recent ten years, different opinions raised about the origin of the !old red sands". Some people considered that the !old red sands" were coastal deposits with their sources from nearby places, while others believed that they were products deriving from aeolian sands.Artificial neural networks (ANN) are a recently developed information processing technique, which is most likely to be superior to other methods in processing data of nonlinearity and ill-definition and corrupted by significant noise. Several B-P neural networks with three, four, five, six and seven inputs were constructed for identification of the origin of the !old red sand" and each network has one intermediary layer and one output. The inputs of the networks were the grain size parameters of the sediments, such as Mean, Sorting, Skewness and Kurtosis. The grain contents of different sizes from gavel to silt/clay are also used as the inputs for the networks. Modern coastal dune sand and beach sand collected from South China coasts were used to train the B-P networks. The fully trained B-P networks couled recognized most of the !old red sand" as aeolian sand, indicating a close relationship between the !old red sand" and aeolian sand. The result of the identification by the networks with gavel and silt/clay content as the inputs of the networks indicates that it is an effective parameter for identifying aeolian deposits. However, the network only with the gain contents of all sizes from gavel to silt/clay as the inputs fails in identifying of the !old red sand". The result also shows that the !old red sand" has poorer sorting and finer particle size than those of the modern coastal dunes.