Neural Networks in Forecasting Disease Dynamics
نویسندگان
چکیده
منابع مشابه
Monthly runoff forecasting by means of artificial neural networks (ANNs)
Over the last decade or so, artificial neural networks (ANNs) have become one of the most promising tools formodelling hydrological processes such as rainfall runoff processes. However, the employment of a single model doesnot seem to be an appropriate approach for modelling such a complex, nonlinear, and discontinuous process thatvaries in space and time. For this reason, this study aims at de...
متن کاملEfficient Short-Term Electricity Load Forecasting Using Recurrent Neural Networks
Short term load forecasting (STLF) plays an important role in the economic and reliable operation ofpower systems. Electric load demand has a complex profile with many multivariable and nonlineardependencies. In this study, recurrent neural network (RNN) architecture is presented for STLF. Theproposed model is capable of forecasting next 24-hour load profile. The main feature in this networkis ...
متن کاملA Review of Epidemic Forecasting Using Artificial Neural Networks
Background and aims: Since accurate forecasts help inform decisions for preventive health-careintervention and epidemic control, this goal can only be achieved by making use of appropriatetechniques and methodologies. As much as forecast precision is important, methods and modelselection procedures are critical to forecast precision. This study aimed at providing an overview o...
متن کاملNeural networks for financial forecasting
Neural networks demonstrate great potential for discovering non-linear relationships in time-series and extrapolating from them. Results of forecasting using financial data are particularly good [LapFar87, Schöne9O, ChaMeh92]. In contrast, traditional statistical methods are restrictive as they try to express these non-linear relationships as linear models. This thesis investigates the use of t...
متن کاملFlood Forecasting Using Neural Networks
This paper deals with flood routing in rivers using neural networks. The unsteady river flow may be formulated in terms of two one-dimensional partial differential equations. These are the Saint Venant flow continuity and dynamic equations. Several methods of solution of these equations are known. These methods are based upon characteristics of equations, finite difference, finite element and f...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Creative surgery and oncology
سال: 2020
ISSN: 2076-3093,2307-0501
DOI: 10.24060/2076-3093-2020-10-3-198-204