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معرفی راهکار ارزیابی فازی چندمعیاره (F-MCE) برای قابلیت‌سنجی زنبورداری در جنگل | ||
| تحقیقات جنگل و صنوبر ایران | ||
| مقاله 5، دوره 30، شماره 1 - شماره پیاپی 87، فروردین 1401، صفحه 39-56 اصل مقاله (833.79 K) | ||
| نوع مقاله: علمی- پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22092/ijfpr.2022.352367.2026 | ||
| نویسندگان | ||
| علی نجفی فر* 1؛ ماشاالله محمدپور2؛ منوچهر طهماسبی2 | ||
| 1نویسنده مسئول، استادیار، بخش تحقیقات منابع طبیعی، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی استان ایلام، سازمان تحقیقات، آموزش و ترویج کشاورزی، ایلام، ایران | ||
| 2استادیار، بخش تحقیقات منابع طبیعی، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی استان ایلام، سازمان تحقیقات، آموزش و ترویج کشاورزی، ایلام، ایران | ||
| چکیده | ||
| مدیریت یکپارچه جنگل برای استفاده پایدار از همه قابلیت‌های این بوم‌سازگان، نقش مهمی در کنترل تخریب و ایجاد تعادل بین کارکردهای مختلف آن دارد. زنبورداری، یکی از مناسب‌ترین کاربری‌های چندگانه جنگل محسوب می‌‌شود. هدف این پژوهش، معرفی راهکار ارزیابی فازی چندمعیاره (F-MCE) در قابلیت‌سنجی جنگل برای زنبورداری و مقایسه آن با راهکار غیرفازی مرسوم است. با استفاده از این دو راهکار، قابلیت زنبورداری 16825 هکتار از جنگل‌های زاگرسی در منطقه کبیرکوه استان ایلام در چهار طبقه مقایسه شدند. معیارهای ارزیابی در هر دو راهکار مذکور، یکسان در نظر گرفته شدند. این معیارها شامل طبقه جذابیت گیاهان، دوره گل‌دهی، شیب، دما، رطوبت نسبی، سرعت باد و دسترسی به آب و جاده بودند که با استفاده از فرایند تحلیل شبکه‌ای (ANP) وزن‌دهی شدند. در اجرای F-MCE، معیارها با استفاده از توابع عضویت فازی در واحد پیکسل ارزشگذاری شدند و با روش ترکیب خطی وزن‌‌دارشده (WLC) تلفیق شدند. سپس، قابلیت زنبورداری با روش ارزیابی چندمعیاره (MCE) به‌صورت رقومی بررسی شد. ارزیابی در روش غیرفازی مرسوم نیز در سطح واحدهای کاری انجام شد. براساس نتایج به‌دست‌آمده، 40 درصد سطح طبقه‌های زنبورداری در دو راهکار ارزیابی باهم اختلاف داشتند. بخش اصلی این اختلاف (6/35 درصد) مربوط به عرصه‌هایی است که در راهکار F-MCE در طبقه خوب (1S) و در راهکار مرسوم در طبقه متوسط (2S) قرار گرفتند. این اختلاف را می‌توان ناشی از ارزشگذاری رقومی معیارها با منطق فازی در F-MCE دانست که اثر نامطلوب ارزشگذاری سلیقه‌ای بولین در روش مرسوم را ندارد. | ||
| کلیدواژه‌ها | ||
| ارزیابی چندمعیاره؛ جنگل‌های زاگرس؛ فرایند تحلیل شبکه‌ای؛ منطق فازی | ||
| عنوان مقاله [English] | ||
| A fuzzy-multi criteria evaluation approach for the evaluation of forest capability for beekeeping use | ||
| نویسندگان [English] | ||
| Ali Najafifar1؛ M. Mohammadpour2؛ M. Tahmasebi2 | ||
| 1Corresponding author, Assistant Prof., Research Division of Natural Resources, Ilam Agricultural and Natural Resources Research and Education Center, AREEO, Ilam, Iran | ||
| 2Assistant Prof., Research Division of Natural Resources, Ilam Agricultural and Natural Resources Research and Education Center, AREEO, Ilam, Iran | ||
| چکیده [English] | ||
| Integrated forest ecosystem management plays an important role in controlling degradation and balancing its various functions for the sustainable use of all available capabilities. In this regard, beekeeping is one of the most suitable multiple uses of the forest. The purpose of this study is to introduce a fuzzy multi-criteria Evaluation approach (F-MCE) to determine the forest's capability for beekeeping and compare it with the conventional non-fuzzy approach. In this regard, beekeeping capability in 16825 hectares of Zagros forests in Kabirkouh region of Ilam province, Iran was evaluated by the two approaches in four classes and the results were compared. Evaluation criteria were the same in both approaches and included the percentage of the canopy of plant attractiveness classes, flowering period, slope, air temperature, relative humidity, prevailing wind speed, and access to road and water. The weight of the criteria was determined using the Analytic Network Process (ANP). In F-MCE, the values of the criteria were determined using fuzzy membership functions and the criteria were combined by the Weighted Linear Combination (WLC) method. Then, beekeeping capability was digitally evaluated using the Multi-Criteria Evaluation method (MCE). The results showed that 40% of the area of beekeeping classes differed in the two evaluation approaches and the main part of this difference (35.6%) is related to the areas that were evaluated in the F-MCE approach in the good class (S1) and in the traditional approach in Moderate class (S2). This difference in results can be attributed to the different methods used in F-MCE in which the adverse effect of boolean and subjective criteria evaluation in the traditional method is avoided through their digital evaluation with fuzzy logic. | ||
| کلیدواژه‌ها [English] | ||
| ANP, fuzzy logic, MCE, Zagros forests | ||
| مراجع | ||
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