为提升设施农业的环境感知与预警能力,同时兼顾连续可靠与成本可控,以Arduino UNO R 3为主控,构建了多模态感知与预警平台。集成温湿度和光照等多传感器,电路系统采用三层叠板结构,上位机实现阈值警告与可视化操作界面。基于能量守恒与...为提升设施农业的环境感知与预警能力,同时兼顾连续可靠与成本可控,以Arduino UNO R 3为主控,构建了多模态感知与预警平台。集成温湿度和光照等多传感器,电路系统采用三层叠板结构,上位机实现阈值警告与可视化操作界面。基于能量守恒与水汽守恒提出名义预测环境模型,并结合辐照度分解、传热与换气,推导出温室参数的名义解析表达,并在六个经纬度测试点采集多组数据进行工况验证。实验结果表明,在五档通风条件下,光照校准共180组样本,回归斜率接近1%;温湿度实测与模型预测高度吻合,通风增强可将稳态温升由56—64℃区间显著拉低,并将相对湿度稳定在约35%—50%RH之间;多模态联动测试中,火焰、超声、CO_(2)与可燃气体通道的响应灵敏度分别为99%、89%、95%、91%,实现了从透过辐射到室内多模态响应的闭环集成,为面向不同温室环境测量的推广与应用提供了可行的技术路径。展开更多
定量评估航天侦察装备效能是武器装备体系建设的重要环节之一,对装备发展和作战应用具有重要的现实意义。针对评估样本数据少、效能在多指标因素影响下变化规律非线性等条件下的效能评估问题,提出一种基于改进灰狼(improved grey wolf o...定量评估航天侦察装备效能是武器装备体系建设的重要环节之一,对装备发展和作战应用具有重要的现实意义。针对评估样本数据少、效能在多指标因素影响下变化规律非线性等条件下的效能评估问题,提出一种基于改进灰狼(improved grey wolf optimizer,IGWO)算法优化的支持向量回归机(support vector regression,SVR)评估方法(IGWO-SVR)。引入反向学习策略及余弦非线性收敛因子改进灰狼优化算法收敛性能及全局寻优能力,并将其应用于基于支持SVR效能评估参数的优化。基于航天侦察装备特点,构建评估指标体系及航天侦察装备效能评估模型。最后,通过对一定作战想定背景下航天侦察装备效能进行仿真评估,验证了所提方法的合理性及优化模型的有效性。展开更多
As one of the most important part of weapon system of systems(WSoS),quantitative evaluation of reconnaissance satellite system(RSS)is indispensable during its construction and application.Aiming at the problem of nonl...As one of the most important part of weapon system of systems(WSoS),quantitative evaluation of reconnaissance satellite system(RSS)is indispensable during its construction and application.Aiming at the problem of nonlinear effectiveness evaluation under small sample conditions,we propose an evaluation method based on support vector regression(SVR)to effectively address the defects of traditional methods.Considering the performance of SVR is influenced by the penalty factor,kernel type,and other parameters deeply,the improved grey wolf optimizer(IGWO)is employed for parameter optimization.In the proposed IGWO algorithm,the opposition-based learning strategy is adopted to increase the probability of avoiding the local optima,the mutation operator is used to escape from premature convergence and differential convergence factors are applied to increase the rate of convergence.Numerical experiments of 14 test functions validate the applicability of IGWO algorithm dealing with global optimization.The index system and evaluation method are constructed based on the characteristics of RSS.To validate the proposed IGWO-SVR evaluation method,eight benchmark data sets and combat simulation are employed to estimate the evaluation accuracy,convergence performance and computational complexity.According to the experimental results,the proposed method outperforms several prediction based evaluation methods,verifies the superiority and effectiveness in RSS operational effectiveness evaluation.展开更多
文摘为提升设施农业的环境感知与预警能力,同时兼顾连续可靠与成本可控,以Arduino UNO R 3为主控,构建了多模态感知与预警平台。集成温湿度和光照等多传感器,电路系统采用三层叠板结构,上位机实现阈值警告与可视化操作界面。基于能量守恒与水汽守恒提出名义预测环境模型,并结合辐照度分解、传热与换气,推导出温室参数的名义解析表达,并在六个经纬度测试点采集多组数据进行工况验证。实验结果表明,在五档通风条件下,光照校准共180组样本,回归斜率接近1%;温湿度实测与模型预测高度吻合,通风增强可将稳态温升由56—64℃区间显著拉低,并将相对湿度稳定在约35%—50%RH之间;多模态联动测试中,火焰、超声、CO_(2)与可燃气体通道的响应灵敏度分别为99%、89%、95%、91%,实现了从透过辐射到室内多模态响应的闭环集成,为面向不同温室环境测量的推广与应用提供了可行的技术路径。
基金the National Defense Science and Technology Key Laboratory Fund of China(XM2020XT1023).
文摘As one of the most important part of weapon system of systems(WSoS),quantitative evaluation of reconnaissance satellite system(RSS)is indispensable during its construction and application.Aiming at the problem of nonlinear effectiveness evaluation under small sample conditions,we propose an evaluation method based on support vector regression(SVR)to effectively address the defects of traditional methods.Considering the performance of SVR is influenced by the penalty factor,kernel type,and other parameters deeply,the improved grey wolf optimizer(IGWO)is employed for parameter optimization.In the proposed IGWO algorithm,the opposition-based learning strategy is adopted to increase the probability of avoiding the local optima,the mutation operator is used to escape from premature convergence and differential convergence factors are applied to increase the rate of convergence.Numerical experiments of 14 test functions validate the applicability of IGWO algorithm dealing with global optimization.The index system and evaluation method are constructed based on the characteristics of RSS.To validate the proposed IGWO-SVR evaluation method,eight benchmark data sets and combat simulation are employed to estimate the evaluation accuracy,convergence performance and computational complexity.According to the experimental results,the proposed method outperforms several prediction based evaluation methods,verifies the superiority and effectiveness in RSS operational effectiveness evaluation.
