ارزیابی مدل‌های جنگل تصادفی و هیبریدی سری زمانی در شبیه‌سازی دومتغیره هدایت الکتریکی

نوع مقاله : مقاله پژوهشی

نویسنده

گروه مهندسی آب و محیط زیست، دانشکده مهندسی عمران، دانشگاه صنعتی شاهرود، شاهرود، ایران.

چکیده

پارامترهای کیفی رودخانه اعم از هدایت الکتریکی وابستگی زیادی به تغییرات دبی جریان دارند. اضافه‌شدن پارامتر دبی جریان به شبیه­سازی این پارامتر می­تواند قطعیت نتایج شبیه­سازی را افزایش دهد. به همین دلیل در این مطالعه جهت مدل­سازی مقادیر هدایت الکتریکی در ایستگاه­های گردیعقوب، کوتر و بیطاس در زیرحوضه مهابادچای با درنظرگرفتن مقادیر دبی جریان، از مدل­های جنگل تصادفی، CARMA و CARMA-GARCH استفاده شد. در این خصوص از مقادیر ماهانه هدایت الکتریکی و دبی جریان در دوره آماری 1365 تا 1397 بهره گرفته شد. نتایج بررسی­ها با استفاده از آماره نش- ساتکلیف، جذر میانگین مربعات خطا و نمودار ویالونی موردبررسی و مقایسه قرار گرفت. مقادیر آماره­های جذر میانگین مربعات خطا و نش- ساتکلیف بیانگر بهبود نتایج شبیه­سازی مدل CARMA-GARCH نسبت به مدل CARMA در دو ایستگاه بیطاس و کوتر و هم‌چنین مرحله آموزش در ایستگاه گردیعقوب بود. نتایج نشان داد که تلفیق مدل غیرخطی و خطی توانسته است میزان خطای مدل­سازی را در هر سه ایستگاه گرد یعقوب، کوتر و بیطاس در مرحله آموزش به‌ترتیب 56/9، 70/9 و 68/21 درصد بهبود بخشد. بررسی نمودارهای ویالونی حاکی از دقت و عملکرد قابل‌قبول مدل­های CARMA و CARMA-GARCH نسبت به الگوریتم جنگل تصادفی بود. به‌طور کلی نتایج بیانگر آن است که مدل‌های سری زمانی از دقت بالاتری در شبیه­سازی دومتغیره مقادیر هدایت الکتریکی در منطقه موردمطالعه برخوردار هستند.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Evaluation of random forest and hybrid time series models in bivariate simulation of electrical conductivity

نویسنده [English]

  • Emad Mahjoobi
Department of Water and Environmantal Engineering, Faculty of Civil Engineering, Shahrood Univerisity of Technology, Shahrood, Iran.
چکیده [English]

The quality parameters of the river, including electrical conductivity, are highly dependent on changes in flow rate. Adding the flow rate parameter to the simulation of this parameter can increase the certainty of the simulation results. For this reason, in this study, random forest, CARMA and CARMA-GARCH models were used to model the electrical conductivity values in Gerdyaghoub, Kutar and Bitas stations in Mahabadchai basin, taking into account the flow rates. In this regard, the monthly values of electrical conductivity and flow discharge in the statistical period 1986-2018 were used. The results were analyzed using Nash-Sutcliffe statistics, root mean square error and violin plot. The results of evaluation the root mean square error and Nash-Sutcliffe statistics showed that the simulation results of CARMA-GARCH model compared to CARMA model in Bitas and Kuter stations as well as the training step in Gerdyaghoub station were improved. The results showed that the combination of nonlinear and linear models could improve the modeling error in three stations, Gerdyaghoub, Kotar and Bitas in the training step of 9.56, 9.70 and 21.68 percent. By examining the violin plots, the results showed acceptable accuracy and performance of CARMA and CARMA-GARCH models compared to the random forest model. In general, the results showed that time series models have higher accuracy in bivariate simulating of electrical conductivity values in the study area.

کلیدواژه‌ها [English]

  • Autocorrelation
  • Conditional variance
  • Nonlinear model
  • Urmia Lake
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