An optimized forecasting approach based on grey theory and cuckoo search algorithm: a case study for electricity consumption in New South Wales

DOI10.1155/2014/183095zbMath1406.91284OpenAlexW2040176427WikidataQ59035843 ScholiaQ59035843MaRDI QIDQ1722287

Haiyan Jiang, Ping Jiang, Yao Dong, Qing-Ping Zhou

Publication date: 14 February 2019

Published in: Abstract and Applied Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2014/183095

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Inference from stochastic processes and prediction (62M20) Approximation methods and heuristics in mathematical programming (90C59) Economic models of real-world systems (e.g., electricity markets, etc.) (91B74)

Related Items (1)

Short-term wind speed forecasting using support vector regression optimized by cuckoo optimization algorithm

Cites Work

• Parameter optimization of nonlinear grey Bernoulli model using particle swarm optimization
• Control problems of grey systems
• Generalized GM (1,1) model and its application in forecasting of fuel production
• The effect of sample size on the grey system model
• Forecasting electricity demand in Japan: a Bayesian spatial autoregressive ARMA approach
• Electricity consumption prediction with functional linear regression using spline estimators

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