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• The modified CES function takes into account the stages of technological progress. • The improved PSO algorithm has fast convergence speed and high accuracy. • The method of calculating the contribution rate is scientific and reliable. • China's economic growth factor contribution rate is given. In the analysis of the economic growth factors, people often use the CES (constant elasticity of substitution) production function model to calculate the contribution rate of influencing factors to economic growth. However, the traditional CES production function model does not consider the period characteristic of technological progress on economic growth, so this paper puts forward a modified CES production function model. On the parameter estimation of the model, this paper presents an improved PSO (particle swarm optimization) algorithm with high precision and fast convergence. Using the modified CES production function model, this paper provides a scientific method to calculate the contribution rates of all factors influencing the economic growth. Finally, this paper performs the empirical analysis of the contribution rates of all factors influencing China's economic growth. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, firstly a modified particle swarm optimization algorithm (MPSO) is developed, in which the mean value of past optimal positions for each particle and the mutation operation are considered for avoiding premature. In the optimization test, MPSO performs better than particle swarm optimization algorithm (PSO). Then MPSO is applied to solve four portfolio optimization models with the real data from the Hong Kong Stock Market, and optimal values are obtained when the number of swarm , respectively. Finally, actual return rates of these models are calculated in numerical experiments, and it is illustrated from these graphs of actual return rates that when considering higher return, Cai’s model performs better in short-term investment. [Copyright &y& Elsevier]

In this paper, we re-study an ancient Chinese algorithm, the Ying Buzu Shu, in about second century BC, known as the rule of double false position in West after 1202 AD. The method can powerfully applied to solve nonlinear equations. Some examples are given. [Copyright &y& Elsevier]