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مقایسة عملکرد مدلهای خطی تعمیمیافته (GLM) و جنگل تصادفی (RF) در پیشبینی توزیع صید ماهی سفید (Rutilus frisii) | ||
شیلات | ||
دوره 76، شماره 1، فروردین 1402، صفحه 27-38 اصل مقاله (963.6 K) | ||
شناسه دیجیتال (DOI): 10.22059/jfisheries.2023.91491 | ||
نویسندگان | ||
فاتح معزی1؛ هادی پورباقر* 2؛ سهیل ایگدری2؛ جهانگیر فقهی3 | ||
1دانش آموخته دکتری بومشناسی آبزیان، دانشکده منابع طبیعی، دانشگاه تهران، کرج، ایران | ||
2دانشیار گروه شیلات، دانشکده منابع طبیعی، دانشگاه تهران، کرج، ایران | ||
3استاد گروه مهندسی جنگلداری و اقتصاد جنگل، دانشکده منابع طبیعی، دانشگاه تهران، کرج، ایران | ||
چکیده | ||
هدف از انجام مطالعة حاضر، ارزیابی عملکرد مدلهای خطی تعمیمیافته (GLM) و جنگل تصادفی (RF) در پیشبینی توزیع صید ماهی سفید دریای خزر (Rutilus frisii) بود. بدینمنظور، دادههای صید در واحد تلاش (CPUE) ماهی سفید بهعنوان متغیر اصلی و دادههای سنجش از دور 5 متغیر محیطی شامل دمای روزانة سطح آب (SST)، غلظت کلروفیل-a (CHL)، ضخامت اپتیک ریزگردها (ASL)، محتوای کربن آلی ذرهای (POC) و کربن غیرآلی ذرهای (PIC) بهعنوان متغیرهای پیشبین مورد استفاده قرار گرفت. جهت سنجش عملکرد توصیفی و پیشبینی مدلها از شاخصهای ضریب تبیین (R2)، میانگین خطای مطلق (MAE) و ریشة میانگین مربعات خطا (RMSE) استفاده گردید. در بهترین مدل GLM برازشیافته تنها دو پارامتر Log(PIC) و POC معنیدار بودند، در حالیکه در مدل RF تمامی متغیرها بکار گرفته شدند. مدل RF از توان توصیفی بیشتری نسبت به مدل GLM برخوردار بود (0/053GLM: R2=؛ 0/47RF:R2=). همچنین، دقت بیشتری برای مدل RF ((kg/hour.seine) 1326/1RMSE=؛ 972/4MAE=) در مقایسه با GLM ((kg/hour.seine) 1465/6RMSE=؛ 1328/7MAE=) وجود داشت. پارامترهای ASL و CHL بهترتیب دارای بیشترین (%33/31) و کمترین (%27/88) سهم اهمیت نسبی در مدل RF بودند. براساس مجموعه نتایج بهدست آمده، مدل جنگل تصادفی (RF) بهعنوان یک مدل کارآمد جهت مدلسازی توزیع صید ماهیان پیشنهاد میگردد. | ||
کلیدواژهها | ||
: مدل خطی تعمیمیافته؛ مدل جنگل تصادفی؛ متغیرهای زیستگاهی؛ ماهی سفید؛ دریای خزر | ||
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