Optimization of an artificial neural network dedicated to the multivariate forecasting of daily global radiation

نویسندگان
چکیده

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Optimization of an artificial neural network dedicated to the multivariate forecasting of daily global radiation

This paper presents an application of Artificial Neural Networks (ANNs) to predict daily solar radiation. We look at the Multi-Layer Perceptron (MLP) network which is the most used of ANNs architectures. In previous studies, we have developed an ad-hoc time series preprocessing and optimized a MLP with endogenous inputs in order to forecast the solar radiation on a horizontal surface. We propos...

متن کامل

Daily Runoff Forecasting using Artificial Neural Network

Rainfall-Runoff is the most important hydrological variables used in most of the water resources applications. Watershed based planning and management requires thorough understanding hydrological process and accurate estimation of runoff. An Artificial Neural Network (ANN) methodology was employed to forecast daily runoff for the Kadam watershed of G-5 sub-basin of Godavari river basin. On the ...

متن کامل

scour modeling piles of kambuzia industrial city bridge using hec-ras and artificial neural network

today, scouring is one of the important topics in the river and coastal engineering so that the most destruction in the bridges is occurred due to this phenomenon. whereas the bridges are assumed as the most important connecting structures in the communications roads in the country and their importance is doubled while floodwater, thus exact design and maintenance thereof is very crucial. f...

An application of artificial neural network to maintenance management

This study shows the usefulness of Artificial Neural Network (ANN) in maintenance planning and man-agement. An ANN model based on the multi-layer perceptron having three hidden layers and four processing elements per layer was built to predict the expected downtime resulting from a breakdown or a maintenance activity. The model achieved an accuracy of over 70% in predicting the expected downtime.

متن کامل

Optimization of traits to increasing barley grain yield using an artificial neural network

The grain yield (Y) of crops is determined by several Y components that reflect positive or negative effects. Conventionally, ordinary Y components are screened for the highest direct effect on Y. Increasing one component tends to be somewhat counterbalanced by a concomitant reduction in other component (s) due to competition for assimilates. Therefore, it has been suggested that components...

متن کامل

ذخیره 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: Energy

سال: 2011

ISSN: 0360-5442

DOI: 10.1016/j.energy.2010.10.032