بررسی نقش پارامترهای مکانی در تعیین ظرفیت راه آهن در GIS (مطالعه موردی: ایران)
محورهای موضوعی : کاربرد GIS&RS در برنامه ریزی
بهرام مرادی سلوشی
1
,
سمیرا بلوری
2
,
محمدصادق زنگنه
3
,
اکرم کرامت
4
1 - دکترای سنجش از دور و سیستم اطلاعات جغرافیایی، راه آهن جمهوری اسلامی ایران، ایران.
2 - دکترای سنجش از دور و سیستم اطلاعات جغرافیایی، راه آهن جمهوری اسلامی ایران، ایران
3 - گروه سنجش از دور و سیستم اطلاعات جغرافیایی، واحد دزفول، دانشگاه آزاد اسلامی، دزفول، ایران.
4 - گروه سنجش از دور و سیستم اطلاعات جغرافیایی، واحد دزفول،دانشگاه آزاد اسلامی،دزفول، ایران.
کلید واژه: راه آهن, پارامترهای مکانی, GIS.,
چکیده مقاله :
حمل و نقل ریلی به عنوان یک صنعت ایده‌آل در جهان توسعه یافته در نظر گرفته می‌شود. راه‌آهن در بسیاری از کشورها همچنان در تلاش است تا از نظر تجاری کارآمدتر و با دوام باشد. این روش حمل و نقل ایمن، کارآمد و سازگار با محیط زیست در نظر گرفته می شود. این صنعت با ارائه خدمات قابل اعتماد و مقرون به صرفه باعث رشد اقتصادی می‌شود و نقش مهمی در زندگی انسان ایفا می‌کند. این تحقیق از طریق رگرسیون خطی ظرفیت راه‌آهن را در یک مطالعه موردی برای مسیرهای منتخب تعیین و بلوک‌های بحرانی را مشخص می‌کند تا تأثیر پارامترهای مکانی در تعیین ظرفیت شبکه ریلی مورد بحث قرار گیرد. از طریق داده‌های موجود مربوط به سال 2017، پیش‌بینی ظرفیت سال 2018 در محیط GIS انجام شد و سپس از طریق پارامترهای آماری RMSE، R^2 و MAE صحت پیش‌بینی ظرفیت برای داده‌های موجود سال 2018 انجام شد. نتایج نشان داد که ظرفیت استفاده از مسیرهای انتخابی برای قطارهای باری 82 درصد، قطارهای مسافری در مسیر رفت 56 درصد، در مسیر برگشت 62 درصد و در مسیرهای ترکیبی 79 درصد بوده است. همچنین پیش‌بینی دقت قطارهای باری 35 درصد بهتر از قطارهای مسافری بود. در مسیر مسافری، قطارهای مسافری دقت بیشتری داشتند (تقریباً 45 درصد). به همین ترتیب در مسیر باری ظرفیت قطارهای باری از دقت بالاتری (نزدیک به 45 درصد) برخوردار بود.
Railway transport is considered a mature industry in the developed world. Railways in many countries are still struggling to become more commercially efficient and sustainable. This method of transportation is considered safe, efficient and environmentally friendly. By providing reliable and affordable services, this industry causes economic growth and plays an important role in human life. This research, through the linear regression, determines the capacity of the railway in a case study in Iran for the selected routes and pinpoints the critical blocks to discuss the effect of spatial parameters in determining the capacity of the railway network. Through the existing 2017-related data, the capacity forecast of 2018 was done in GIS environment, and then via the RMSE, R^2, and MAE statistical parameters, the accuracy of the capacity forecast for the extant data of 2018 was performed. The results showed that the capacity of utilizing the selected routes was 82% for cargo trains, 56% for passenger trains on the road, 62% on the way back and 79% on the combined routes. Also, the accuracy prediction of cargo trains was 35% better than that of passenger trains. In the passenger route, the passenger trains were more accurate (approximately 45%). Similarly, in the cargo route, the capacity of cargo trains was of higher accuracy (nearly 45%).
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