نتایج جستجو برای: forecasting performance

تعداد نتایج: 1085145  

ژورنال: انرژی ایران 2018

As the electricity industry has changed and became more competitive, the electricity price forecasting has become more important. Investors need to estimate future prices in order to take proper strategy to maintain their market share and to maximize their profits. In the economic paradigm, this goal is pursued using econometric models. The validity of these models is judged by their forecastin...

Journal: :JACIII 2010
Aymen Chaouachi Rashad M. Kamel Ken Nagasaka

This paper presents the applicability of artificial neural networks for 24 hour ahead solar power generation forecasting of a 20 kW photovoltaic system, the developed forecasting is suitable for a reliable Microgrid energy management. In total four neural networks were proposed, namely: multi-layred perceptron, radial basis function, recurrent and a neural network ensemble consisting in ensembl...

2001
John Kerekes Kristine Farrar Nirmal Keshava J. Kerekes K. Farrar N. Keshava

The quantitative forecasting of hyperspectral system performance is an important capability at every stage of system development including system requirement definition, system design, and sensor operation. In support of this, Lincoln Laboratory has been developing an analytical modeling tool to predict end-to-end spectroradiometric remote sensing system performance. Recently, the model has bee...

Journal: :CoRR 2014
Raffi Sevlian Ram Rajagopal

We propose a simple empirical scaling law that describes load forecasting accuracy at different levels of aggregation. The model is justified based on a simple decomposition of individual consumption patterns. We show that for different forecasting methods and horizons, aggregating more customers improves the relative forecasting performance up to specific point. Beyond this point, no more impr...

Journal: :مدیریت آب و آبیاری 0
مرتضی نبی زاده دانش آموخته کارشناسی ارشد مهندسی منابع آب، دانشکده کشاورزی، دانشگاه علوم کشاورزی و منابع طبیعی گرگان، گرگان - ایران ابوالفضل مساعدی دانشیار دانشکده منابع طبیعی و محیط زیست، دانشگاه فردوسی مشهد، مشهد – ایران امیر احمد دهقانی استادیار گروه مهندسی آب، دانشکده کشاورزی، دانشگاه علوم کشاورزی و منابع طبیعی گرگان، گرگان - ایران

in recent years, use of fuzzy collection theories for modeling of hydrological phenomenon's that is including complexity and uncertainly is considered scholars. so in this research, adaptive neuro-fuzzy inference system (anfis) is used for performance of river flow forecasting process. in this research, three parameters such as raining, temperature and daily discharge of lighvanchai basin ...

2012
Mohamad Ghazali Wasiu Balogun

This work examines recent publications in forecasting in various fields, these include: wind power forecasting; electricity load forecasting; crude oil price forecasting; gold price forecasting energy price forecasting etc. In this review, categorization of the processes involve in forecasting are divided into four major steps namely: input features selection; data pre-processing; forecast mode...

2016
Yingxiao Zhou Peng Zhao

It has been deemed as an effective tool of forecasting performance improvement to combine different component forecasting models. However, current nonlinear combining models are not able to meet the requirement of high forecasting accuracy in practice. To tackle this challenge, this paper constructs a hybrid, named genetic programming and least squared estimation based nonlinear combining metho...

Journal: Iranian Economic Review 2004

Applying nonlinear models to estimation and forecasting economic models are now becoming more common, thanks to advances in computing technology. Artificial Neural Networks (ANN) models, which are nonlinear local optimizer models, have proven successful in forecasting economic variables. Most ANN models applied in Economics use the gradient descent method as their learning algorithm. However, t...

2004
Melike Sah Konstantin Y. Degtiarev

This paper proposes a novel improvement of forecasting approach based on using time-invariant fuzzy time series. In contrast to traditional forecasting methods, fuzzy time series can be also applied to problems, in which historical data are linguistic values. It is shown that proposed time-invariant method improves the performance of forecasting process. Further, the effect of using different n...

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