آخرین خبرها
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
وقوع آتش‌سوزی بسیار گسترده در پارک ملی کرخه/ مهار آتش پس از ۱۶ ساعت
Time Series
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.
Assessing the Relationship Between Meteorological Parameters, Air Pollution And Cardiovascular Mortality of Mashhad City Based on Time Series Model
Epidemiological studies conducted in the past two decades indicate that air pollution causes increase in cardiovascular, breathing and chronic bronchitis disorders and even causes cardiovascular mortality. Therefore, the aim of this study was to investigate the relationship between meteorological parameters, air pollution and cardiovascular mortality in the city of Mashhad in 2014 by a time series model.
