Calculation of Parameters of Crop Water Production Function of Jensen Model Based on Stochastic Particle Swarm Optimization Algorithm

Abstract:

In this paper, Stochastic Particle Swarm Optimization Algorithm (SPSO) is introduced to calculate parameters of crop water production function directly. SPSO is an improvement of the standard PSO, compared with which, it can be guaranteed to converge to the global optimization solution with probability one in theory, and speed up the convergence. The dimension of space of a particulate is determined by the phases of crop growth and development period in SPSO, and the sensitive index , an important parameter of crop water production function, is regarded as optimized variable to be calculated directly. This method can eliminate some problems existing in linear regression method, such as biased estimate and distortion of result and it can search the global optimization value more easily than the PSO. Through example analysis, we can see that the SPSO is better than PSO in accuracy and calculation speed.

• Periodical: Advanced Materials Research (Volume 937)
• Pages: 548-553
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.937.548
• Online since: May 2014
• Authors: Shu Hui Chang*, Zhi Hong Qie
• Keywords: Correlation Coefficient, Crop Water Production Function, Jensen Model, Sensitive Index, Stochastic Particle Swarm Optimization Algorithm

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