为了提高路径寻优算法的效率和实时性,本文实现了一种名为DPO-AC的基于蚁群思想的动态路径寻优算法(the ant colony algorithm with dynamic path optimization),在改进蚁群算法的基础上结合神经网络的实时预测方法和限定区域的搜索方式...为了提高路径寻优算法的效率和实时性,本文实现了一种名为DPO-AC的基于蚁群思想的动态路径寻优算法(the ant colony algorithm with dynamic path optimization),在改进蚁群算法的基础上结合神经网络的实时预测方法和限定区域的搜索方式,解决算法在大型网络路径寻优时实时性差、收敛慢的问题。仿真实验表明DLACO算法有比较好的稳定性、收敛性和实时性。展开更多
燃煤电站脱硝系统在变负荷工况下具有非线性、大滞后的特性,传统的控制方式很难保证喷氨量的精确控制。随着燃煤发电厂超低排放标准的实施,有必要对脱硝系统进行运行优化。通过挖掘海量脱硝系统的历史运行数据,提出一种基于混合群智能...燃煤电站脱硝系统在变负荷工况下具有非线性、大滞后的特性,传统的控制方式很难保证喷氨量的精确控制。随着燃煤发电厂超低排放标准的实施,有必要对脱硝系统进行运行优化。通过挖掘海量脱硝系统的历史运行数据,提出一种基于混合群智能算法优化的核极限学习机NO X 排放动态预测模型。首先,对选择性催化还原(SCR)脱硝反应系统进行理论分析和实际运行研究,研究了采用核函数代替极限学习机中隐含层节点的显式映射的方法,从而无需事先给定隐含层节点数。然后,采用混合蚁群和粒子群优化的混合智能算法,对核极限学习机的学习参数进行优化。最后,以某电站锅炉脱硝系统为例,利用提出的方法进行验证,得到较高的建模精度。该研究为下一步脱硝系统控制优化打下良好基础。展开更多
This study first reviews the numerical manifold method(NMM)which possesses some advantages over the traditional limit equilibrium methods(LEMs)in calculating the factors of safety(Fs)of the slopes.Then,with regard to ...This study first reviews the numerical manifold method(NMM)which possesses some advantages over the traditional limit equilibrium methods(LEMs)in calculating the factors of safety(Fs)of the slopes.Then,with regard to a trial slip surface(TSS),associated stress fields reproduced by NMM as well as the enhanced limit equilibrium method are combined to compute Fs.In order to search for the potential critical slip surface(CSS),the MAX-MIN ant colony optimization algorithm(MMACOA),one of the best performing algorithms for some optimization problems,is adopted.Procedures to obtain Fs in conjunction with the potential CSS are described.Finally,the proposed numerical model and traditional methods are compared with stability analysis of three typical slopes.The numerical results show that Fs and CSSs of the slopes can be accurately calculated with the proposed model.展开更多
文摘为了提高路径寻优算法的效率和实时性,本文实现了一种名为DPO-AC的基于蚁群思想的动态路径寻优算法(the ant colony algorithm with dynamic path optimization),在改进蚁群算法的基础上结合神经网络的实时预测方法和限定区域的搜索方式,解决算法在大型网络路径寻优时实时性差、收敛慢的问题。仿真实验表明DLACO算法有比较好的稳定性、收敛性和实时性。
文摘燃煤电站脱硝系统在变负荷工况下具有非线性、大滞后的特性,传统的控制方式很难保证喷氨量的精确控制。随着燃煤发电厂超低排放标准的实施,有必要对脱硝系统进行运行优化。通过挖掘海量脱硝系统的历史运行数据,提出一种基于混合群智能算法优化的核极限学习机NO X 排放动态预测模型。首先,对选择性催化还原(SCR)脱硝反应系统进行理论分析和实际运行研究,研究了采用核函数代替极限学习机中隐含层节点的显式映射的方法,从而无需事先给定隐含层节点数。然后,采用混合蚁群和粒子群优化的混合智能算法,对核极限学习机的学习参数进行优化。最后,以某电站锅炉脱硝系统为例,利用提出的方法进行验证,得到较高的建模精度。该研究为下一步脱硝系统控制优化打下良好基础。
基金This study is supported by the Youth Innovation Promotion Association of Chinese Academy of Sciences(Grant No.2020327)the National Natural Science Foundation of China(Grant No.51609240).
文摘This study first reviews the numerical manifold method(NMM)which possesses some advantages over the traditional limit equilibrium methods(LEMs)in calculating the factors of safety(Fs)of the slopes.Then,with regard to a trial slip surface(TSS),associated stress fields reproduced by NMM as well as the enhanced limit equilibrium method are combined to compute Fs.In order to search for the potential critical slip surface(CSS),the MAX-MIN ant colony optimization algorithm(MMACOA),one of the best performing algorithms for some optimization problems,is adopted.Procedures to obtain Fs in conjunction with the potential CSS are described.Finally,the proposed numerical model and traditional methods are compared with stability analysis of three typical slopes.The numerical results show that Fs and CSSs of the slopes can be accurately calculated with the proposed model.
