精养虾池水质主要因子变化规律及底质氮释放转化规律的初步研究

学位：理学硕士院系专业：海洋与环境学院海洋学系_海洋化学学号：19942700

Nitrate Measurement in the Ocean Based on Neural Network Model

Nitrate concentration is an important indicator for the marine ecosystem.Compared with laboratory chemical methods such as Cadmium-Reduction method,in-situ nitrate optical sensor is much faster and reagent-free in a long time and continuous monitoring.Partial Least Squares(PLS)method is often used in ultraviolet absorption spectrum modeling,which is difficult to optimize and has low generalization ability.The neural network can compel any no-linear function by any precision,which has high generalization ability in the modeling.A neural network model is established in the in-situ nitrate sensor to measure the nitrate concentration in seawater in which the nitrate concentration range is 30~750mug·L~(-1).Double-hidden layer neural network model is determined to adopt by contrasting performance of single-hidden layer and double-hidden layer to measure nitrate concentration,the input layer is absorption spectrum from 200to 275nm,the output layer is nitrate concentration,and sigmoid function is used as the activation function.Gradient descent method is used to update weighting parameters for the neural network of each layer,after 55 000times iteration,network training is conducted based on the learning rate of 0.26. After validation for the blind test of the model through 8-group randomized validation data,the nitrate concentration using double-hidden layer neural network model is higher in linear correlation to its actual concentration(R~2=0.997)in which the Root Mean Squared Error is 10.864,average absolute error is 8.442mug·L~(-1),average the relative error is 2.8%.Compared with single-hidden layer neural network model,the double-hidden layer neural network model has higher accuracy in which the average relative error is reduced by 4.92%,the Root Mean Squared Error of PLS is 4.58%using the same spectral data,while the mean relative error is 11.470.The result shows that the neural network model is much better than the Partial Least Squares model under certain conditions.It verifies the superiority of the neural network model applied to the nitrate concentration measurement by ultraviolet absorption spectrometry.The application test was carried out on theEnvironmental Monitoring 01 monitoring vessel of the Ministry of Natural Resources,the measurement results are basically identical with the laboratory method in 11stations,which is further proved from the reliability and practicality