شبیه‌سازی عمقی شوری خاک با استفاده از زنجیره مارکف در باغات پسته اردکان

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشگاه تهران

2 دانشگاه گنبد کاووس

3 دانشگاه اردکان

چکیده

در این تحقیق با استفاده از زنجیره مارکف مرتبه اول اقدام به شبیه‌سازی مقادیر شوری در نه عمق و ده کلاس شوری در پسته‌زارهای شهرستان اردکان گردید. با استفاده از ماتریس احتمال انتقال، توزیع یکنواخت و تابع کرنل اقدام به شبیه‌سازی 500000 هزار پروفیل گردید. نتایج نشان داد در حالتی که از تابع کرنل برای شبیه‌سازی استفاده گردید نسبت به حالتی که از توزیع یکنواخت جهت تولید داده‌های مصنوعی استفاده گردید خصوصیات آماری (از قبیل میانگین، انحراف معیار، کشیدگی و چولگی) داده‌های شبیه‌سازی‌شده بیشتر شبیه داده‌های مشاهداتی بودند. همچنین در حالتی که شبیه‌سازی از عمق به سطح نسبت به حالتی که شبیه‌سازی از سطح به عمق صورت گرفت عملکرد مدل بهتر می‌باشد. به‌طورکلی رویکرد شبیه‌سازی با استفاده از زنجیره مارکف قادر است روابط بین کلاس‌های مختلف را به‌خوبی در شبیه‌سازی در نظر بگیرد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Vertical simulation of soil salinity using Markov chain in Ardakan pistachio gardens

نویسندگان [English]

  • Roohollah Taghizadeh Mehrjerdi 1
  • Abolhasan Fathabadi 2
  • Somayeh Asemani 3
1
2
3
چکیده [English]

In this research, a first order Markov chain model was applied to simulate soil salinity in nine standard depths and 10 classes in the cultivated pistachio areas of Ardakan city. Transition probability matrix, kernel and uniform distribution were used to simulate 500000 soil profiles. Results indicate kernel function could reproduce soil salinity values with statistical criteria (i.e. mean, standard deviation, skewness and kurtosis) more closely to the observed data when compared to data simulated by uniform function. Moreover, simulation processes from down-up is more accurate than that of up-down method. Overall, Makov simulation technique is able to consider the relationship between different classes.

کلیدواژه‌ها [English]

  • Kernel function
  • transition probability matrix
  • uniform distribution
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