خاشعی سیوکی, عباس, سربازی, محبوبه. (1394). بررسی توزیع مکانی کیفیت آب زیرزمینی با استفاده از مدل‌های MLP ، LS-SVM و زمین آماری. دو ماهنامه علمی- پژوهشی آب و فاضلاب, 26(3), 93-103.
عباس خاشعی سیوکی; محبوبه سربازی. "بررسی توزیع مکانی کیفیت آب زیرزمینی با استفاده از مدل‌های MLP ، LS-SVM و زمین آماری". دو ماهنامه علمی- پژوهشی آب و فاضلاب, 26, 3, 1394, 93-103.
خاشعی سیوکی, عباس, سربازی, محبوبه. (1394). 'بررسی توزیع مکانی کیفیت آب زیرزمینی با استفاده از مدل‌های MLP ، LS-SVM و زمین آماری', دو ماهنامه علمی- پژوهشی آب و فاضلاب, 26(3), pp. 93-103.
خاشعی سیوکی, عباس, سربازی, محبوبه. بررسی توزیع مکانی کیفیت آب زیرزمینی با استفاده از مدل‌های MLP ، LS-SVM و زمین آماری. دو ماهنامه علمی- پژوهشی آب و فاضلاب, 1394; 26(3): 93-103.
بررسی توزیع مکانی کیفیت آب زیرزمینی با استفاده از مدل‌های MLP ، LS-SVM و زمین آماری
2کارشناس ارشد مدیریت مناطق بیابانی، دانشکده منابع طبیعی، دانشگاه تهران
چکیده
کنترل کیفیت آب زیرزمینی به‌علت کمبود آب در مناطق خشک و نیمه‌خشک از اهمیت ویژه‌ای برخوردار است. مدل‌های زمین آماری، روش‌های توسعه یافته پهنه‌بندی برای پیش‌بینی مکانی ومیانیابی پارامترهای آب زیرزمینی محسوب می‌شود. در این پژوهش روش‌های IDW، کریجینگ و کوکریجینگ در زمین آمار با مدل‌های پرسپترون چند لایه و مدل حداقل مربعات ماشین بردار پشتیبان برای پیش‌بینی توزیع مکانی پارامتر EC آب زیرزمینی بررسی و با یکدیگر مقایسه شد. داده‌ها از 120 چاه در دشت مشهد جمع‌آوری شد. بعد از نرمال‌کردن داده‌ها به‌منظور استفاده در مدل‌های زمین آماری، واریوگرام‌ها ترسیم و برای انتخاب مدل مناسب، کمترین RSS استفاده شد. سپس با استفاده از اعتبارسنجی متقابل و معیار RMSE، بهترین مدل درونیابی انتخاب شد. برای مقایسه سه مدل از 25 درصد داده‌های مشاهده‌ای استفاده و پارامترهای آماری RMSE، R2 و MAE تعیین شدند. نتایج نشان داد که برای درونیابی کیفیت آب زیرزمینی روش کوکریجینگ نسبت به کریجینگ ارجحیت دارند. مدل پرسپترون چند لایه با دقت RMSE برابر 9/369میکروموس بر سانتی‌متر، R2 برابر 932/0 و MAE برابر 78/265 میکروموس بر سانتی‌متر نسبت به دیگر مدل‌ها از دقت بیشتری برخوردار است.
Study of Spatial Distribution of Groundwater Quality Using LS-SVM, MLP, and Geostatistical Models
نویسندگان [English]
Abbas Khashei-siuki1؛ Mahboobeh Sarbazi2
1Assist. Prof. of Water Resources Engineering, Birjand University, Birjand
2MSc in Deserts Management, Dept. of Natural Resources, Tehran University, Tehran
چکیده [English]
Groundwater quality control is of great importance in (semi-)arid zones due to the water deficit in these regions. Geostatistical models are techniques commonly developed for the interpolation and spatial prediction of groundwater quality parameters. In this study, IDW, Kriging, and CoKriging methods were used in the geostatistical, LS-SVM, and MLP models to predict the spatial distribution of groundwater EC. The models were then compared in terms of their efficiency. For the purposes of this study, data were collected from 120 wells in the Mashhad plain. Variograms were then drawn after normalizing the data for application in the geostatistical models. In the next stage, the lowest RSS value was used for selecting the one model that was suitable for fitting the experimental variogram while cross-validation and RMSE were used to select the best method for interpolation. Comparison of the three models in question was accomplished by using 25% of the observation data and the statistical parameters of RMSE, R2, and MAE were determined. Results showed that the CoKriging method outperformed its Kriging counterpart in the geostatistic model for interpolating groundwater quality. Finally, the most accurate values for the quality parameters (i.e., R2=0.932, RMSE=367.9, MAE=265.78() were obtained with the MLP model.
کلیدواژه ها [English]
Variogram, Multilayered perceptron (MLP), Least Squares Support Vector Machine
(LS-SVM)
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