Journal of Liaoning Petrochemical University
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Power Load Logistic Curve-Forecasting Model Based on Improved Particle Swarm Optimization
LIU Guo-zhi,HE Peng-qing
Abstract417)      PDF (216KB)(224)      
 
On the basis of the research results published in existing relevant references,the logistic curve methodis are further improved and a new power load logistic curve-forecasting model is proposed based on improved particle swarm optimization(IPSOLM). And the result of the Power load gray-forecasting model based on particle swarm optimization (PSOGM) compares with the result of the new power load forecasting model. The practical example indicates that the new model has the characteristic of better precision and wider application field.
2011, 31 (2): 62-64. DOI: 10.3696/j.issn.1672-6952.2011.02.017
Improved Particle Swarm Optimization Method for Estimating the Parameters of Logistic Curve
LIU Guo-zhi, HE Peng-qing
Abstract385)      PDF (129KB)(201)      
It makes further research on estimating the parameters of logistic curve on based of the present document, and an improved method for estimating the parameters of logistic curve-improved particle swarm optimization method was presented. It does not require gradient computation, and intends to produce faster and more accurate convergence. The sampling calculation shows that parameter estimation method is higher precise.
2010, 30 (4): 88-90. DOI: 10.3696/j.issn.1672-6952.2010.04.024