基于BP神經(jīng)網(wǎng)絡模型的福建海域赤潮預報方法研究
發(fā)布時間：2018-10-17 16:45
【摘要】：赤潮往往給漁業(yè)生產(chǎn)和人類的生命安全造成極大的危害,但由于赤潮的成因十分復雜,對其進行預報非常困難。本研究收集了福建海區(qū)2000年至2016年發(fā)生的219個赤潮案例有效數(shù)據(jù),應用BP神經(jīng)網(wǎng)絡人工智能模型建立了其與氣溫、降水、風速、氣壓和日照5個氣象因子的非線性關(guān)系,并將這些赤潮案例數(shù)據(jù)與相應的氣象指標按閩東、閩中和閩南3個海區(qū),分別輸入模型進行學習、訓練與預測。結(jié)果顯示:1)閩東海區(qū)53個訓練樣本45個預測正確,正確率達84.91%,3個模擬預測樣本全部正確;2)閩中海區(qū)69個訓練樣本58個預測正確,正確率達84.06%,4個模擬預測樣本全部正確;3)閩南海區(qū)85個訓練樣本的運算預測結(jié)果63個正確,正確率74.12%,5個模擬預測樣本全部正確,達到預期的結(jié)果。研究表明,以氣象因子為自變量采用BP神經(jīng)網(wǎng)絡模型對赤潮的發(fā)生進行預測是可行的,該方法可為赤潮的預測提供新的途徑。
[Abstract]:The red tide is often harmful to the production of fishery and the safety of human life, but it is very difficult to forecast the red tide because of its complexity. The data of 219 red tide cases occurred from 2000 to 2016 in Fujian sea area were collected, and the nonlinear relation with temperature, precipitation, wind speed, air pressure and sunshine was established by BP neural network artificial intelligence model. The data of these red tide cases and the corresponding meteorological indexes were studied, trained and predicted according to the input models respectively according to the three sea areas in the east, middle and south Fujian. The results showed that: 1) 53 training samples in Mindong area were correctly predicted, the correct rate was 81.91%, the three simulated predictive samples were all correct; 2) 69 training samples were correctly predicted, the correct rate was 84.6%, and the four simulated predictive samples were all correct. 3) The results of operation and prediction of 85 training samples in Minnan sea area are correct, the correct rate is 74. 12%, and the five analog predictive samples are all correct to achieve the expected results. The research shows that using the BP neural network model to forecast the occurrence of red tide is feasible by using meteorological factors as independent variables, and the method can provide a new way for the prediction of red tide.
【作者單位】： 福建省水產(chǎn)研究所;廈門市氣象臺;福建省海洋環(huán)境與漁業(yè)資源監(jiān)測中心;廈門市海洋與漁業(yè)研究所;福建省海洋預報臺;
【基金】：福建省海洋與漁業(yè)結(jié)構(gòu)調(diào)整專項(2015) 福建省海洋與漁業(yè)廳科技外經(jīng)外事處:基于BP神經(jīng)網(wǎng)絡的海區(qū)赤潮預警預報模型研究(閩海漁科2015005)~~
【分類號】：TP183;X55
[Abstract]:The red tide is often harmful to the production of fishery and the safety of human life, but it is very difficult to forecast the red tide because of its complexity. The data of 219 red tide cases occurred from 2000 to 2016 in Fujian sea area were collected, and the nonlinear relation with temperature, precipitation, wind speed, air pressure and sunshine was established by BP neural network artificial intelligence model. The data of these red tide cases and the corresponding meteorological indexes were studied, trained and predicted according to the input models respectively according to the three sea areas in the east, middle and south Fujian. The results showed that: 1) 53 training samples in Mindong area were correctly predicted, the correct rate was 81.91%, the three simulated predictive samples were all correct; 2) 69 training samples were correctly predicted, the correct rate was 84.6%, and the four simulated predictive samples were all correct. 3) The results of operation and prediction of 85 training samples in Minnan sea area are correct, the correct rate is 74. 12%, and the five analog predictive samples are all correct to achieve the expected results. The research shows that using the BP neural network model to forecast the occurrence of red tide is feasible by using meteorological factors as independent variables, and the method can provide a new way for the prediction of red tide.
【作者單位】： 福建省水產(chǎn)研究所;廈門市氣象臺;福建省海洋環(huán)境與漁業(yè)資源監(jiān)測中心;廈門市海洋與漁業(yè)研究所;福建省海洋預報臺;
【基金】：福建省海洋與漁業(yè)結(jié)構(gòu)調(diào)整專項(2015) 福建省海洋與漁業(yè)廳科技外經(jīng)外事處:基于BP神經(jīng)網(wǎng)絡的海區(qū)赤潮預警預報模型研究(閩海漁科2015005)~~
【分類號】：TP183;X55
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