An improved grey wolf optimizer algorithm for identification and location of gas emission

Identification of the leakage of hazardous gases plays an important role in the environment protection, human health and safety of industry production. However, lots of current optimization algorithms, such as particle swarm optimization (PSO) and Grey Wolf Optimizer (GWO), suffer from poor global optimization capability and estimation accuracy. In this work, a hybrid differential evolutionary and GWO (DE-GWO) algorithm is proposed. Tested by simulation cases and Prairie Grass emission experimental data, DE-GWO shows higher estimation accuracy than GWO. Compared with the other four optimization algorithms, DE-GWO exhibits finer robust stability under different population sizes, fewer iterations, as well as higher estimation accuracy with fewer search agents. Importantly, simulation results demonstrate that DE-GWO is more suitable to apply in the scene with a small number of sensors. Therefore, the proposed in this paper outperforms other optimization algorithms for the gas emission inverse problem. DE-GWO can provide reliable estimation towards gas emission identification and positioning, which shows huge potential as the data analysis module of real-time monitoring and early warning system.     

地震能量辐射系数的测定与预报应用探索

本方法通过对区域地震体波振幅传播特征的研究并测定地震能量辐射系数企图得到中强震孕育的源兆信息。本文给出了方法的思路、介绍了参数的物理意义及正常理论值的估计。这一方法无论在目前模拟台网的观测条件下或将来数字观测台网建成之后均可方便、快捷使用。还对方法的使用误差、震例效果和存在问题进行了讨论。     

成都大气污染物在焚烧秸秆时的溯源初步探究

在空气污染指数(API)的数据基础上,结合卫星遥感、气团后向轨迹及气象数据,通过初步分析秸秆焚烧对本地及区域范围输送对城市空气质量影响,研究不同空气污染类型(本地型、本地区域相结合型、输送型)特征,探索重污染条件的大气污染物溯源方法。