In order to optimize test flow after the default flow is modified by a tester, a new software framework for the radar fault isolation is illustrated. This framework separates all mapping algorithms from test flows so ...In order to optimize test flow after the default flow is modified by a tester, a new software framework for the radar fault isolation is illustrated. This framework separates all mapping algorithms from test flows so as to modify flow and to insert mapping algorithm dynamically in testing process. Based on this framework, a kind of optimization method of test flow is proposed and studied. By defining an objective function, we can evaluate all candidate test flows so as to get an optimized flow. An example explains how to search the flow from candidate flows.展开更多
针对黑猩猩优化算法存在全局搜索能力弱、寻优精度低、收敛速度慢等问题,提出一种混沌精英池协同教与学改进的黑猩猩优化算法(chimp optimization algorithm improved by the elite chaos pool collaborative teaching-learning,ECTChOA...针对黑猩猩优化算法存在全局搜索能力弱、寻优精度低、收敛速度慢等问题,提出一种混沌精英池协同教与学改进的黑猩猩优化算法(chimp optimization algorithm improved by the elite chaos pool collaborative teaching-learning,ECTChOA)。采用混沌精英池策略生成初始种群,增强初始解的质量和种群的多样性,为算法全局寻优奠定基础;引入自适应振荡因子平衡ChOA的全局探索和局部开发能力;结合教与学优化算法的教学阶段和粒子群优化算法的个体记忆思想优化种群位置更新过程,提高算法的寻优精度和收敛速度。仿真实验将ECTChOA与标准ChOA、其他元启发式优化算法和最新改进ChOA在12个基准测试函数下进行寻优对比,实验结果与Wilcoxon秩和检验p值结果均表明所提改进算法具有更高搜索精度、更快的收敛速度和更好的鲁棒性。另外,将ECTChOA应用于机械工程设计案例中,进一步验证ECTChOA在实际工程问题中的可行性和适用性。展开更多
针对微电网分布式电源和负荷增多的问题,提出将人工智能算法和纳什均衡博弈策略用于微电网运行和交易优化。该方法以循环神经网络RNN(recurrent neural network)和长短期记忆LSTM(long-short term memory)的方式实现对微电网行为的准确...针对微电网分布式电源和负荷增多的问题,提出将人工智能算法和纳什均衡博弈策略用于微电网运行和交易优化。该方法以循环神经网络RNN(recurrent neural network)和长短期记忆LSTM(long-short term memory)的方式实现对微电网行为的准确时空预测;同时,纳什均衡博弈被应用于多目标优化的快速、准确求解。仿真模型结果表明,所提微电网行为优化策略能促进新能源消纳,提升微电网利润达30.79%,降低了用户用能成本。多个微电网案例验证了所提方法的有效性和稳定性。展开更多
文摘In order to optimize test flow after the default flow is modified by a tester, a new software framework for the radar fault isolation is illustrated. This framework separates all mapping algorithms from test flows so as to modify flow and to insert mapping algorithm dynamically in testing process. Based on this framework, a kind of optimization method of test flow is proposed and studied. By defining an objective function, we can evaluate all candidate test flows so as to get an optimized flow. An example explains how to search the flow from candidate flows.
文摘针对黑猩猩优化算法存在全局搜索能力弱、寻优精度低、收敛速度慢等问题,提出一种混沌精英池协同教与学改进的黑猩猩优化算法(chimp optimization algorithm improved by the elite chaos pool collaborative teaching-learning,ECTChOA)。采用混沌精英池策略生成初始种群,增强初始解的质量和种群的多样性,为算法全局寻优奠定基础;引入自适应振荡因子平衡ChOA的全局探索和局部开发能力;结合教与学优化算法的教学阶段和粒子群优化算法的个体记忆思想优化种群位置更新过程,提高算法的寻优精度和收敛速度。仿真实验将ECTChOA与标准ChOA、其他元启发式优化算法和最新改进ChOA在12个基准测试函数下进行寻优对比,实验结果与Wilcoxon秩和检验p值结果均表明所提改进算法具有更高搜索精度、更快的收敛速度和更好的鲁棒性。另外,将ECTChOA应用于机械工程设计案例中,进一步验证ECTChOA在实际工程问题中的可行性和适用性。
文摘针对微电网分布式电源和负荷增多的问题,提出将人工智能算法和纳什均衡博弈策略用于微电网运行和交易优化。该方法以循环神经网络RNN(recurrent neural network)和长短期记忆LSTM(long-short term memory)的方式实现对微电网行为的准确时空预测;同时,纳什均衡博弈被应用于多目标优化的快速、准确求解。仿真模型结果表明,所提微电网行为优化策略能促进新能源消纳,提升微电网利润达30.79%,降低了用户用能成本。多个微电网案例验证了所提方法的有效性和稳定性。
