نتایج جستجو برای: term forecasting purposes

تعداد نتایج: 700517  

Journal: :Energies 2022

Offshore wind turbines (OWTs), in comparison to onshore turbines, are gaining popularity worldwide since they create a large amount of electrical power and have thus become more financially viable recent years. However, OWTs costly as vulnerable damage from extremely high-speed winds thereby affect operation maintenance (O&M) operations (e.g., vessel access, repair, downtime). Therefore, ac...

Journal: :Mathematics and Financial Economics 2021

Abstract We propose an affine term structure model that allows for tenor-dependence of yield curves and thus different risk categories in interbank rates, important feature post-crisis interest rate markets. The has a Nelson–Siegel factor loading economically well interpretable parameters. show the is tractable terms estimation provides good in-sample fit out-of-sample forecasting performance. ...

Journal: :Proceedings of the National Academy of Sciences of the United States of America 2018
Michael C Dietze Andrew Fox Lindsay M Beck-Johnson Julio L Betancourt Mevin B Hooten Catherine S Jarnevich Timothy H Keitt Melissa A Kenney Christine M Laney Laurel G Larsen Henry W Loescher Claire K Lunch Bryan C Pijanowski James T Randerson Emily K Read Andrew T Tredennick Rodrigo Vargas Kathleen C Weathers Ethan P White

Two foundational questions about sustainability are "How are ecosystems and the services they provide going to change in the future?" and "How do human decisions affect these trajectories?" Answering these questions requires an ability to forecast ecological processes. Unfortunately, most ecological forecasts focus on centennial-scale climate responses, therefore neither meeting the needs of ne...

2012
Baochen Yang Shan Liao Yunpeng Su

The dynamic Nelson-Siegel-style models, which are popular in the literature of interest rates term structure forecasting, may be unstable because of the potential existence of unit roots in the parameter series. In this paper, the dynamic Nelson-Siegel-style models are modified by modelling the first-order differenced instead of original parameter series. Empirical study shows that the modified...

2016
Cristian Rodriguez Rivero Daniel Patiño Julian Pucheta Victor Sauchelli

A new predictor algorithm based on Bayesian enhanced approach (BEA) for long-term chaotic time series using artificial neural networks (ANN) is presented. The technique based on stochastic models uses Bayesian inference by means of Fractional Brownian Motion as model data and Beta model as prior information. However, the need of experimental data for specifying and estimating causal models has ...

2013
HERY PURNOMO

This paper presents the application of interval type-2 fuzzy inference systems (IT2FIS) in short term load forecasting (STLF) on special days. This is a continuation work of application interval type-2 fuzzy systems (IT2FSs) using Karnik Mendel algorithm. Special days here mean local Balinese holidays such as national and local culture-based public holidays, consecutive holidays, and days prece...

2005
Stefan Luckner Felix Kratzer Christof Weinhardt

Forecasting markets are a promising approach for predicting future events. The basic idea of a forecasting market is to trade virtual stocks whose final value is tied to a particular future event. The market prices can then be interpreted as predictions of the probability of those future events. The results of recent studies on forecasting markets are encouraging. However, various design issues...

2009
Gautham P. Das Piyush Chandra Ojha

The load forecasting is a tool of utmost important for the power industry as it can influence areas like power generation and trading, infrastructure development planning etc. Implementation of the load forecasting tool in the distribution utilities has a wider impact up to the power generation level. The load forecasting has been an area in power systems where the human experts are still perfo...

2015
Ming-jun Deng Shiru Qu

Traffic flow is widely recognized as an important parameter for road traffic state forecasting. Fuzzy state transform and Kalman filter (KF) have been applied in this field separately. But the studies show that the former method has good performance on the trend forecasting of traffic state variation but always involves several numerical errors. The latter model is good at numerical forecasting...

2011
M. Mordjaoui B. Boudjema

Problem statement: Load forecasting plays an important task in power system planning, operation and control. It has received an increasing attention over the years by academic researchers and practitioners. Control, security assessment, optimum planning of power production required a precise short term load forecasting. Approach: This study tries to combine neural network and fuzzy logic for ne...

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