【摘要】 电水转换法是一种经济有效的农业用水计量方法,构建合理的电水转换模型,提出适宜的模型参数优化方法对于提高计量精度具有重要的研究意义。对传统的电水转换模型进行优化改进,并提出了一种基于自适应调整惯性权重和变邻域混沌搜索的改进粒子群的模型参数寻优方法。最后分别采用最小二乘法、粒子群算法、改进粒子群算法进行模型参数拟合,结果表明改进粒子群算法寻优精度更高、有更好的收敛速度,拟合的特征关系曲线能够更真实的反应耗电量和供水量的关系,为农业用水计量设备的研制提供理论基础。更多还原

【Abstract】 Electricity-water conversion is an economical and effective method for measuring agricultural water. Building a reasonable transformation model of electricity-water and proposing an appropriate optimization method for model parameters is important for improving the accuracy of measurement. In this study,the traditional electricity-water conversion model is optimized and improved. An improved particle swarm optimization algorithm based on self-adaptive adjustment of inertia weight and variable neighborhood chaotic search is proposed. At last,LSM,PSO and IPSO are used to optimize the model parameters. The results show that the IPSO has higher optimization precision and better convergence speed; the fitting characteristic curve can reflect the relationship between the power consumption and the water supply more truly. This study provides a theoretical basis for the development of agricultural water metering equipment.更多还原