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Agri-environmental policy 1 In this paper 1 Industrial Engineering 1 Ltd 1 Sustainability 1 and the integrated prediction model 1 and the maximum forecast length of the long-term prediction model is 84 h. The wind farm power prediction models are built with five different data mining algorithms. The accuracy of the generated models is analysed. The model generated by a neural network outperforms all other models for both short- and long-term prediction. Two basic prediction methods are presented: the direct prediction model 1 and then the power is generated with the predicted wind speed. The direct prediction model offers better prediction performance than the integrated prediction model. The main source of the prediction error appears to be contributed by the weather forecasting data. 2008 John Wiley Sons 1 discriminatory-price auction 1 ecological services 1 experimental economics 1 models for short- and long-term prediction of wind farm power are discussed. The models are built using weather forecasting data generated at different time scales and horizons. The maximum forecast length of the short-term prediction model is 12 h 1 multi-unit auction 1 outperforms the original case-study 1 payment-by-results 1 plant biodiversity 1 rural development 1 the paper develops a nonparametric estimation method for the case where the samples are obtained from using a resampling algorithm. The asymptotic theory shows that in each case the rate of convergence of the nonparametric estimate based on the resamples is faster than that of the conventional nonparametric estimation method by an order of the number of the resamples. The proposed models and estimation methods are evaluated through using simulated and empirical examples. Both the simulated and empirical examples show that the proposed nonparametric estimation based on resamples outperforms existing estimation methods 1 then proposes some non- and semi-parametric dimension reductions methods to deal with the case where the dimensionality of either the regressors or the summary statistics is large. Meanwhile 1 whereby the power prediction is generated directly from the weather forecasting data 1 whereby the prediction of wind speed is generated with the weather data 1
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Free 3
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Book / Working Paper 2 Other 1
Type of publication (narrower categories)
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Working Paper 1
Language
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Undetermined 2 English 1
Author
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Gao, Jiti 1 Groth, Markus 1 Hong, Han 1 Kusiak, Andrew 1 Song, Zhe 1 Zheng, Haiyang 1
Institution
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Department of Econometrics and Business Statistics, Monash Business School 1
Published in...
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Monash Econometrics and Business Statistics Working Papers 1 Working Paper Series in Economics 1
Source
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BASE 1 EconStor 1 RePEc 1
Showing 1 - 3 of 3
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Nonparametric Regression Approach to Bayesian Estimation
Gao, Jiti; Hong, Han - Department of Econometrics and Business Statistics, … - 2014
Estimation of unknown parameters and functions involved in complex nonlinear econometric models is a very important issue. Existing estimation methods include generalised method of moments (GMM) by Hansen (1982) and others, efficient method of moments (EMM) by Gallant and Tauchen (1997), Markov...
Persistent link: https://www.econbiz.de/10011093868
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Wind farm power prediction: a data-mining approach
Kusiak, Andrew; Zheng, Haiyang; Song, Zhe - 2009
model generated by a neural network outperforms all other models for both short- and long-term prediction. Two basic …
Persistent link: https://www.econbiz.de/10009466082
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The transferability and performance of payment-by-results biodiversity conservation procurement auctions: empirical evidence from northernmost Germany
Groth, Markus - 2009
Managed grasslands contribute in a number of ways to the biodiversity of European agricultural landscapes and provide a wide range of ecosystem services that are also of socio-economic value. Against the background of a rapid biodiversity loss in agricultural landscapes, increasing attention is...
Persistent link: https://www.econbiz.de/10010265210
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