پیش‌بینی خشکسالی با نمایه SPI به‌روش مدل‌سازی ANFIS بر مبنای خوشه‌بندی C-mean فازی

نوع مقاله: مقاله پژوهشی

نویسندگان

1 دانشجوی دکترا، دانشکده مهندسی عمران، دانشکده تبریز

2 دانشیار، دانشکده مهندسی عمران، دانشگاه تبریز

چکیده

خشکسالی نتیجه اندرکنش بین محیط زیست و چرخه آب در طبیعت است که تهدیدی مخاطره آمیز برای محیط زیست و حیات گونه‌های زیستی محسوب می‌شود. لذا یافتن نمایه‌های اندازه‌گیری خشکسالی برای پیش بینی و ارزیابی مکانی و زمانی این پدیده به‌منظور مدیریت بحران آن ضرروی و حیاتی به‌نظر می‌رسد. در این مقاله ابتدا به بیان مفهوم خشکسالی و مقایسه نمایه‌های اندازه‌گیری آن پرداخته شد و سپس از مبانی شبکه‌های عصبی- فازی به‌همراه آنالیز خوشه‌بندی برای پیش بینی خشکسالی با نمایه بارش استاندارد استفاده شد. نتایجی حاکی از آن است که نمایه SPI قابلیت بیشتری در پیش‌بینی نسبت به نمایه‌هایی چون پالمر، پالفی و دیگر نمایه‌ها دارد و از سویی راهبرد شبکه عصبی- فازی تطبیقی بر مبنای روش خوشه‌بندی C-mean در امر مدل‌سازی برای پیش‌بینی خشکسالی از کارایی بالایی برخودار است.

کلیدواژه‌ها


عنوان مقاله [English]

Drought Forecasting by SPI Index and ANFIS Model Using Fuzzy C-mean Clustering

نویسندگان [English]

  • mehdi Komasi 1
  • Mohammadtaghi Alami 2
  • Vahid Nourani 2
چکیده [English]

Drought is the interaction between environment and water cycle in the world and affects natural environment of an area when it persists for a longer period. So, developing a suitable index to forecast the spatial and temporal distribution of drought plays an important role in the planning and management of natural resources and water resource systems. In this article, firstly, the drought concept and drought indexes were introduced and then the fuzzy neural networks and fuzzy C-mean clustering were applied to forecast drought via standardized precipitation index (SPI). The results of this research indicate that the SPI index is more capable than the other indexes such as PDSI (Palmer Drought Severity Index), PAI (Palfai Aridity Index) and etc. in drought forecasting process. Moreover, application of adaptive nero-fuzzy network accomplished by C-mean clustering has high efficiency in the drought forecasting.

کلیدواژه‌ها [English]

  • Drought
  • SPI
  • adaptive neuro-fuzzy inference system
  • C-mean
  • Lighvanchai
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