摘要
首次利用支持向量机 ( SVM)理论对海水水质富营养化的程度进行评价 ,并与 BP人工神经网络方法所得结果进行比较 ,通过实例验证 ,说明 SVM理论能较好地解决小样本的分类评价问题 ,评价效果良好 ,在水质评价领域有较好的应用前景。
In this paper,Support Vector Machine (SVM) theory is first applied to evaluation of eutrophication degree of sea water quality. An applied example is evaluated with a satisfactory result, Compared with BP artificial neural network. Support Vector Machine can resolve problems of classification with small sample more effectively and accurately. Thus, a simple and effective evaluation method is provided for evaluation of eutrophication of seawater quality.
出处
《海洋技术》
2005年第1期48-51,共4页
Ocean Technology
基金
国家自然科学基金资助项目 ( 1 0 472 0 77)
