ارزیابی تأثیر مقدار ضریب بتا در عملکرد خوشه‌بندی بتای انعطاف‌پذیر در طبقه‌بندی‌پوشش گیاهی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دکتری جنگلداری، گروه جنگلداری، دانشکدۀ منابع طبیعی، دانشگاه ارومیه، ارومیه

2 استاد، گروه جنگلداری، دانشکدۀ منابع طبیعی، دانشگاه ارومیه، ارومیه

3 استادیار، گروه ریاضی، دانشکدۀ علوم، دانشگاه ارومیه، ارومیه

4 استاد، گروه اکولوژی، دانشگاه مونتانا، مونتانا

چکیده

خوشه‌بندی از پرکاربردترین روش‌های مختلف طبقه‌بندی و خوشه‌بندی بتای انعطاف‌پذیر از روش‌های موفق سلسله‌مراتبی تجمعی در طبقه‌بندی جوامع گیاهی است. هدف این بررسی، تعیین مقدار بتای مناسب در روش خوشه‌بندی بتای انعطاف‌پذیر است. برای این پژوهش داده‌های پوشش گیاهی از جنگل‌های هیرکانی و جنگل‌های بلوط زاگرس انتخاب شدند و مقدار مختلف بتا در نتایج خوشه‌بندی بتای انعطاف‌پذیر (1/0-، 25/0-، 4/0-، 6/0- و 08/- ) با چهار معیار ارزیابی‌کنندۀ MRPP، PARATNA، Silhouette  و همبستگی فی ارزیابی شد و نتایج هر معیار ارزیابی‌کننده از بهترین به بدترین رتبه‌بندی شدند. سپس با برآورد میانگین کل ارزیابی‌کننده‌ها، عملکرد خوشه‌بندی‌ها مشخص شد. نتایج این پژوهش نشان داد که در داده‌های ناحیۀ رویشی هیرکانی خوشه‌بندی بتای انعطاف‌پذیر با مقدار بتای 1/0- بهترین عملکرد را دارد، اما خوشه‌بندی با مقدار بتای 25/0- و 4/0- نیز عملکرد مناسبی دارد. در داده‌های ناحیۀ رویشی زاگرس خوشه‌بندی بتای انعطاف‌پذیر با مقدار بتای 25/0- بهترین عملکرد را دارد و خوشه‌بندی بتای انعطاف‌پذیر با مقدار بتای 1/0- در رتبۀ دوم قرار دارد. بنابراین با توجه به تأثیر اهمیت انتخاب درست روش طبقه‌بندی در تفسیر اکولوژیکی نتایج حاصل، این بررسی با در نظر گرفتن همۀ نتایج، استفاده از ضریب بتای 1/0- و 25/0- را برای طبقه‌بندی پوشش گیاهی پیشنهاد می‌کند.

کلیدواژه‌ها


عنوان مقاله [English]

Evaluating the effect of beta coefficient on the performance of flexible beta clustering in vegetation classification

نویسندگان [English]

  • N. Pakgohar 1
  • J. Eshaghi Rad 2
  • GH. Gholami 3
  • A. Alijanpour 2
  • D. Roberts 4
1 Ph.D. of forestry, Dept. of Forestry, Faculty of Natural Resources, University of Urmia, Urmia, Iran
2 Prof., Dept. of Forestry, Faculty of Natural Resources, University of Urmia, Urmia, Iran
3 Assistant Prof., Dept. of mathematics, Faculty of Science, University of Urmia, Urmia, Iran
4 Prof., Dept. of Ecology, Montana State University, Bozeman MT, US.
چکیده [English]

 
Among different methods for classification, clustering is commonly used methods. Flexible-Beta clustering is successful hierarchical agglomerative clustering which is employed by ecologists as effective clustering method. The aim of the research was to detect the suitable value of beta for flexible-clustering methods. For this purpose, two different forest regions from Hyrcanian and Zagros Oak regions were selected. The clustering algorithms included Flexible-beta algorithms with five value of beta (-0.1, -0.25-, -0.4, -0.6 and -0.8). Five evaluators (Silhouette, MRPP, PARATNA, Phi coefficient) were employed on each cluster solution to evaluate different clustering algorithms. Algorithms were ranked from best to worst on each clustering evaluator for each data set. The results showed that Flexible-beta clustering with beta value -0.1 had best performance and Flexible-beta clustering with beta value -0.25 and -0.4 were proper performance in Hyrcanian regions. Flexible-beta clustering with beta value -0.25 was superior to others and Flexible-beta clustering with beta value -0.1 had the second rank. Since, choosing the most suitable clustering method is critical for achieving maximally ecological interpretable results, therefore, we suggested using flexible beta clustering with beta value equal to -0.1 and -0.25 in the studies area.

کلیدواژه‌ها [English]

  • Hyrcanian forest
  • Hierarchical clustering
  • Zagros forest
 
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