آخرین خبرها
🎥 ویدئو/اخبار ۶۰ ثانیه ای مرکز کنترل و هماهنگی عملیات جمعیت هلال احمر اصفهان
نجات جان یک کارگر چاهکن از عمق ۱۷ متری
۴۰ درصد حوادث بازار تهران مربوط به سیم‌کشی و برق است
سرنوشت نامعلوم ۲کارگر ناپدید شده معدن شازند/ جستجو‌ها ادامه دارد
🎥 ویدئو/تلاش برای مهار آتش سوزی در کالیفرنیای آمریکا
بیمارستان‌های تهران ایمن می‌شوند/ ایمن سازی ۷۰ ساختمان پر خطر پایتخت
Forecasting
Forecasting of heavy metals concentration in groundwater resources of Asadabad plain using artificial neural network approach
Nowadays 90% of the required water of Iran is secured with groundwater resources and forecasting of pollutants content in these resources is vital. Therefore, this research aimed to develop and employ the feedforward artificial neural network (ANN) to forecast the arsenic (As), lead (Pb), and zinc (Zn) concentration in groundwater resources of Asadabad plain.
Application of artificial neural network (ANN) for the prediction of water treatment plant influent characteristics
Application of a reliable forecasting model for any water treatment plant (WTP) is essential in order to provide a tool for predicting influent water quality and to form a basis for controlling the operation of the process. This would minimize the operation and analysis costs, and assess the stability of WTP performances.
Application of artificial neural network (ANN) for the prediction of water treatment plant influent characteristics
Application of a reliable forecasting model for any water treatment plant (WTP) is essential in order to provide a tool for predicting influent water quality and to form a basis for controlling the operation of the process. This would minimize the operation and analysis costs, and assess the stability of WTP performances.
