本文關(guān)鍵詞： 風(fēng)暴潮 損失預(yù)評估 支持向量機(jī) BP神經(jīng)網(wǎng)絡(luò) 組合預(yù)測　出處：《海洋環(huán)境科學(xué)》2017年04期 　論文類型：期刊論文

【摘要】：風(fēng)暴潮災(zāi)害是影響我國最嚴(yán)重的海洋災(zāi)害,風(fēng)暴潮災(zāi)害損失的預(yù)評估對防災(zāi)減災(zāi)有重要作用。本文選用2002~2014年的40組風(fēng)暴潮歷史災(zāi)情資料進(jìn)行試驗(yàn),首先建立風(fēng)暴潮災(zāi)害損失評估指標(biāo)體系并用灰色關(guān)聯(lián)分析法對指標(biāo)進(jìn)行篩選,然后采用最優(yōu)權(quán)重組合將支持向量機(jī)和BP神經(jīng)網(wǎng)絡(luò)進(jìn)行組合預(yù)測分別對風(fēng)暴潮直接經(jīng)濟(jì)損失和受災(zāi)人口數(shù)進(jìn)行預(yù)測,并與單一預(yù)測方法進(jìn)行對比,發(fā)現(xiàn)組合預(yù)測方法可以降低誤差,提高損失預(yù)測的準(zhǔn)確性,建立風(fēng)暴潮災(zāi)害損失預(yù)評估模型,為決策者進(jìn)行預(yù)警信息的發(fā)布提供有效依據(jù)。
[Abstract]:Storm surge disaster is the most serious marine disaster in China, and the pre-assessment of storm surge disaster loss plays an important role in disaster prevention and mitigation. 40 groups of historical disaster data of storm surge from 2002 to 2014 are selected in this paper. First of all, the index system of storm surge disaster loss assessment is established, and the grey relational analysis method is used to screen the index. Then the combination of support vector machine and BP neural network is used to forecast the direct economic loss of storm surge and the number of affected population respectively and compared with the single forecasting method. It is found that the combined forecasting method can reduce the error, improve the accuracy of the loss prediction, establish the pre-assessment model of storm surge disaster loss, and provide an effective basis for the decision makers to release the early warning information.
【作者單位】： 中國海洋大學(xué)工程學(xué)院土木工程系;
【基金】：國家自然科學(xué)基金(41072176,41371496) 國家科技支撐計(jì)劃項(xiàng)目(2013BAK05B04)
【分類號】：P731.23

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本文編號：1514607