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      2. 基于被動水聲信號的淡水魚混合數量預測
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        國家重點研發計劃重點專項子項目(2018YFC1604001);國家現代農業產業技術體系建設專項(CARS-45-27)


        Mixed quantities prediction of freshwater fish based on passive underwater
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          摘要:

          針對淡水魚數量評估問題,通過水聽器和聲學記錄儀采集鳊(Parabramis pekinensis)和鯽(Carassius auratus)在相同比例、不同混合數量下的水聲信號,提取54個特征參數,進行相關性分析,挑選與淡水魚混合數量顯著相關的特征參數,采用Rank-RS法進行樣本劃分,建立多元線性回歸模型,并與偏最小二乘回歸模型的預測效果進行比較。結果顯示,平均Mel頻率倒譜系數與淡水魚混合數量的相關性整體上最顯著,多元線性回歸模型的擬合效果較好,預測模型R〖DD(-*2〗—〖DD)〗2為0.950,RPD為4.492,說明所建立的模型適用于淡水魚混合數量預測,將被動水聲技術應用于淡水魚數量研究具有一定的可行性。

          Abstract:

          The quantities prediction is an important part of fishery resource assessment and aquaculture.Traditional active sonar and large-scale fishing gear trials and other methods have certain defects.For the quantitative assessment of freshwater fish,the hydroacoustic signals of bream and crucian carp in the same proportion and different mixed quantities were collected by hydrophone and acoustic recorder.54 characteristic parameters were extracted and used for correlation analysis.The characteristic parameters significantly correlated with the mixed quantities of freshwater fish were selected.The Rank-RS method was used to divide the samples.The multiple linear regression model was established and compared with the prediction effect of the partial least squares regression model.The results showed that the correlation between the average Mel frequency cepstrum coefficient and mixed quantity of freshwater fish was the most significant on the whole.The fitting effect of the multiple linear regression model was better.The prediction model R〖DD(-*2〗—〖DD)〗2 and the RPD was 0.950 and 4.492,indicating that the established model was suitable for predicting the mixed numbers of freshwater fish.It is feasible to apply passive underwater acoustic technology in studying quantities of freshwater fish.

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        楊詠文,黃漢英,馮婉嫻,李路,熊善柏,趙思明.基于被動水聲信號的淡水魚混合數量預測[J].華中農業大學學報,2020,39(5):147-152

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        • 收稿日期:2019-12-13
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        • 在線發布日期: 2020-10-05
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