水质预测

  • 网络water quality prediction
水质预测水质预测
  1. MATLAB神经网络工具箱在河流水质预测中的应用

    Application of MATLAB Neural Network ' Tool-box in River Water Quality Prediction

  2. 本文最后介绍了BP人工神经网络水质预测算法,给出了算法的Matlab程序实现;

    Lastly , this paper introduced the water quality prediction algorithm by the BP artificial neural network together with the realization of the algorithm using Matlab .

  3. 基于改进BP网络模型的水质预测模型的研究

    Study of Forecasting Model on Water Quality Based on Improved BP Model

  4. 基于BP人工神经网络的生化处理水水质预测

    Prediction of water quality in biological wastewater treatment plant using BP artificial neural network

  5. GMDH方法在长良川水质预测中的应用

    Application of GMDH Method to Water Quality Prediction in Nagara River

  6. 在常规污染预测研究中,引用人工神经网络技术,应用MATLAB软件建立常规水质预测模型。

    It introduces the artificial neural network technology and applies the MATLAB software to set up the conventional water quality prediction model in the study of the conventional water quality prediction .

  7. 文章通过引入神经网络技术来建立水质预测模型,分别采用LM算法和RBF算法来提高预测的精度。

    In this paper , one water quality model was developed using neutral network technology . LM algorithm and RBF algorithm were used to increase predictive precision .

  8. 该评价模型经过对比分析经过详细验证,评价结果的表达更加准确、严密。(4)本文使用BP人工神经网络进行水质预测,从预测值的预测趋势来看,都能反映水质随时间的变化趋势。

    Comparative analysis of the evaluation model through extensive examination , evaluation results are more accurate and rigorous . ( 4 ) The paper uses BP artificial neural network to predict water quality , and the forecast from the forecast trend can reflect changes in water quality trends over time .

  9. 介绍了GM(1,1)的原息模型、新息模型和等维新息模型及残差修正模型的建模方法,分别建立了长江水质预测的等维新息模型和残差修正模型。

    The modelling methods of old information model , new information model , equal dimension new information model and modified model of residual based on GM ( 1,1 ) are introduced ; the equal dimension new information model and the modified model of residual are set up separately .

  10. 实验表明,该方法的时间序列预测精度高于任意个体RBF的预测精度,将该方法应用于水环境水质预测,获得了较好的实际应用效果。

    Through the experiment , the result shows that the forecast accuracy of the RBF neural network integration method is higher than any individual in the forecast accuracy of RBF and the method get better application effect when using the method in the water quality forecast of water environment .

  11. 在分析了水质预测与水质预警之间的区别和联系之后,将SVR预测模型引入到水质预警中,初步讨论了基于SVR预测模型的水质指标预警技术的实现。

    After analyzing the difference and relation between water quality prediction and early warning , we introduce SVR predictive model into early warning of water quality and preliminary discuss the implement of water quality warning technology based on SVR predictive model .

  12. 地下水水质预测的多元线性回归分析模型研究

    Study of multivariate linear regression analysis model for groundwater quality prediction

  13. 水环境容量分析及水质预测分析表明:当前“三河”水质情况不容乐观。

    The analyses show that their water environmental capacities are limited .

  14. 长江水质预测的建模

    Modeling of the Prediction of the Quality of the Yangtze River

  15. 水质预测理论模式研究进展与趋势分析

    Advance and trend analysis of theoretical methodology for water quality forecast

  16. 改进型灰色神经网络模型在水质预测中的应用

    Application of improved grey neural network model to water quality prediction

  17. 最优化技术在地下水水质预测中的应用

    Application of Optimization Technique in search for Prediction of Groundwater Quality

  18. 受闸坝控制的河道水质预测方法研究

    Water Quality Prediction for Channals Controlled by Sluices and Dams

  19. 河流水质预测的模糊线性回归模型研究

    On fuzzy linear regression model for river water quality forecast

  20. 多重网格有限元法在水质预测问题中的应用

    The application of multiple grid finite element method to water quality prediction

  21. 指数平滑法在地下水水质预测中的尝试

    An attempt at groundwater quality forecasting by exponential smoothing method

  22. 三峡水库重庆库区水质预测

    Water quality prediction for Chong-qing region of Three Gorges Reservoir

  23. 湖泊水质预测模型的建立及其应用

    Establishment and Application of Water Quality Forecasting Model of Lake

  24. 基于决策树技术及在线监测的水质预测

    Forecast Water Quality Based on Decision-making Tree and Online Monitoring

  25. 水质预测结果具有一定的精度,表明该方法具有一定的有效性和可行性。

    The prediction results show that this method is effective and applicable .

  26. 河流水质预测中的模型选择和源强估算

    Model Selection and Loading Evaluation in River Water Quality Prediction

  27. 神经网络用于近海水质预测的研究

    Application of neural network to prediction of coastal water quality

  28. 油田开采对水资源的影响及水质预测

    The Oil Field Exploiting Impacts on Water Resources and Water Quality Prediction

  29. 基于多传感器技术的城市供水水质预测

    Prediction of urban water supply quality based on multi-sensor technology

  30. 海水碳酸盐体系缓冲模型在水质预测中的应用

    Application of the seawater carbonate buffer model in the prediction of water quality