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:: دوره 6، شماره 2 - ( 6-1397 ) ::
جلد 6 شماره 2 صفحات 64-43 برگشت به فهرست نسخه ها
ارزیابی قابلیت رگرسیون وزنی جغرافیایی در بهبود پیش‌بینی رشد اراضی شهری با استفاده از سلول‌های خودکار
بابک میرباقری* ، عباس علیمحمدی
دانشگاه صنعتی خواجه نصیرالدین طوسی
چکیده:   (4116 مشاهده)
رگرسیون وزنی جغرافیایی منطقی (GWLR) نسخه محلی مدل رگرسیون منطقی (LR) است که در هر مکان رابطه متفاوتی را بین متغیرهای وابسته و مستقل برآورد می‌کند. در تحقیق حاضر از مدل GWLR در توسعه قوانین تبدیل سلولهای خودکار(CA) استفاده و کارایی آن در پیش‌بینی رشد شهری در مقابل مدل CA مبتنی بر رگرسیون منطقی (Logistic-CA) مورد ارزیابی  قرار گرفت. همچنین پارامتری تحت عنوان ضریب رشد حاشیه ای برای تعیین توازن بهینه میان فرایندهای رشد حاشیه ای و رشد خود انگیخته که از جمله فرایندهای مهم در رشد اراضی شهری محسوب می‌شوند، تعریف گردید. جهت ارزیابی دقت مدل نیز از آماره کاپای فازی در کنار ضریب معمول کاپا استفاده شد. مدل پیشنهادی در تحقیق حاضر جهت پیش بینی توسعه بخشی از اراضی شهری واقع در جنوب غرب منطقه کلانشهری تهران برای دوره زمانی 1391-1383 اجرا گردید. نتایج این مطالعه نشان داد استفاده از مدل GWLR در تعریف قوانین تبدیل CA منجر به افزایش قابل توجه دقت پیش بینی رشد شهری در مقایسه با مدل Logistic-CA می گردد. دقت پیش بینی مدل توسعه داده شده در تحقیق حاضر بر حسب ضریب کاپا برابر 54/0 می باشد که افزایش دقتی معادل 24/0 را در مقایسه با مدل Logistic-CA نشان می دهد. همچنین دقت مدل پیشنهادی بر اساس شاخص کاپای فازی با در نظر گرفتن فواصل50 و 100 متری برای تابع نمایی افت فاصله، به 69/0 و 76/0 می‌رسد.
واژه‌های کلیدی: سلول‌های خودکار، رگرسیون وزنی جغرافیایی، رگرسیون منطقی
متن کامل [PDF 1810 kb]   (1419 دریافت)    
نوع مطالعه: پژوهشي | موضوع مقاله: سیستمهای اطلاعات مکانی (عمومی)
دریافت: 1395/3/25 | پذیرش: 1395/11/13 | انتشار: 1397/6/31
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Mirbagheri B, Alimohammadi A. Evaluating the Capability of Geographically Weighted Regression in Improvement of Urban Growth Simulation Performance Using Cellular Automata . jgit 2018; 6 (2) :43-64
URL: http://jgit.kntu.ac.ir/article-1-588-fa.html

میرباقری بابک، علیمحمدی عباس. ارزیابی قابلیت رگرسیون وزنی جغرافیایی در بهبود پیش‌بینی رشد اراضی شهری با استفاده از سلول‌های خودکار. مهندسی فناوری اطلاعات مکانی. 1397; 6 (2) :43-64

URL: http://jgit.kntu.ac.ir/article-1-588-fa.html



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