A second-order dual problem is formulated for a class of continuous programming problem in which both objective and constrained functions contain support functions, hence it is nondifferentiable. Under second-order in...A second-order dual problem is formulated for a class of continuous programming problem in which both objective and constrained functions contain support functions, hence it is nondifferentiable. Under second-order invexity and second-order pseudoinvexity, weak, strong and converse duality theorems are established for this pair of dual problems. Special cases are deduced and a pair of dual continuous problems with natural boundary values is constructed. A close relationship between duality results of our problems and those of the corresponding (static) nonlinear programming problem with support functions is briefly outlined.展开更多
A second-order Mond-Weir type dual problem is formulated for a class of continuous programming problems in which both objective and constraint functions contain support functions;hence it is nondifferentiable. Under s...A second-order Mond-Weir type dual problem is formulated for a class of continuous programming problems in which both objective and constraint functions contain support functions;hence it is nondifferentiable. Under second-order strict pseudoinvexity, second-order pseudoinvexity and second-order quasi-invexity assumptions on functionals, weak, strong, strict converse and converse duality theorems are established for this pair of dual continuous programming problems. Special cases are deduced and a pair of dual continuous problems with natural boundary values is constructed. A close relationship between the duality results of our problems and those of the corresponding (static) nonlinear programming problem with support functions is briefly outlined.展开更多
为应对复杂多变的未知环境对海洋航行器运动预测所造成的挑战,提出了一种融合级联滤波与误差触发支持向量回归(error-triggered support vector regression,ETSVR)的智能预测系统。首先,该系统基于移动平均滤波对原始数据进行预处理,以...为应对复杂多变的未知环境对海洋航行器运动预测所造成的挑战,提出了一种融合级联滤波与误差触发支持向量回归(error-triggered support vector regression,ETSVR)的智能预测系统。首先,该系统基于移动平均滤波对原始数据进行预处理,以剔除异常值并抑制高频噪声,为后续预测提供高质量的数据集;其次,引入二阶扩展卡尔曼滤波对系统状态进行精确估计,进一步增强数据的平稳度和可靠性;最后,设计ETSVR算法对处理后的高质量数据集进行学习,以构建海洋航行器的运动预测模型,实现精准运动预测,并借助误差触发机制提升系统的实时性与计算效率。基于湖试数据的实验结果表明,所提出的智能运动预测系统在多项误差指标上均显著优于传统的线性回归算法。例如,在侧向速度预测中,均方误差较线性回归算法降低约53.2%;在转艏角速度预测中,最大误差减少了约58.2%。这些结果表明,提出的级联滤波与ETSVR算法相结合的智能预测系统,能够显著提升海洋航行器在复杂未知环境中的运动预测精度,具有较好的应用前景和重要的研究意义。展开更多
Binary oxide systems（Cu Cr2O4, Cu Co2O4）, deposited onto cordierite monoliths of honeycomb structure with a second support（finely dispersed Al2O3）, were prepared as filters for catalytic combustion of diesel soot ...Binary oxide systems（Cu Cr2O4, Cu Co2O4）, deposited onto cordierite monoliths of honeycomb structure with a second support（finely dispersed Al2O3）, were prepared as filters for catalytic combustion of diesel soot using internal combustion engine’s gas exhausts（O2, NOx, H2 O, CO2） and O3 as oxidizing agents. It is shown that the second support increases soot capacity of aforementioned filters, and causes dispersion of the particles of spinel phases as active components enhancing thereby catalyst activity and selectivity of soot combustion to CO2. Oxidants used can be arranged with reference to decreasing their activity in a following series： O3 NO2〉 H2 O 〉 NO 〉 O2〉 CO2. Ozone proved to be the most efficient oxidizing agent： the diesel soot combustion by O3 occurs intensively（in the presence of copper chromite based catalyst） even at closing to ambient temperatures.Results obtained give a basis for the conclusion that using a catalytic coating on soot filters in the form of aforementioned binary oxide systems and ozone as the initiator of the oxidation processes is a promising approach in solving the problem of comprehensive purification of automotive exhaust gases at relatively low temperatures, known as the ＂cold start＂ problem.展开更多
文摘A second-order dual problem is formulated for a class of continuous programming problem in which both objective and constrained functions contain support functions, hence it is nondifferentiable. Under second-order invexity and second-order pseudoinvexity, weak, strong and converse duality theorems are established for this pair of dual problems. Special cases are deduced and a pair of dual continuous problems with natural boundary values is constructed. A close relationship between duality results of our problems and those of the corresponding (static) nonlinear programming problem with support functions is briefly outlined.
文摘A second-order Mond-Weir type dual problem is formulated for a class of continuous programming problems in which both objective and constraint functions contain support functions;hence it is nondifferentiable. Under second-order strict pseudoinvexity, second-order pseudoinvexity and second-order quasi-invexity assumptions on functionals, weak, strong, strict converse and converse duality theorems are established for this pair of dual continuous programming problems. Special cases are deduced and a pair of dual continuous problems with natural boundary values is constructed. A close relationship between the duality results of our problems and those of the corresponding (static) nonlinear programming problem with support functions is briefly outlined.
文摘为应对复杂多变的未知环境对海洋航行器运动预测所造成的挑战,提出了一种融合级联滤波与误差触发支持向量回归(error-triggered support vector regression,ETSVR)的智能预测系统。首先,该系统基于移动平均滤波对原始数据进行预处理,以剔除异常值并抑制高频噪声,为后续预测提供高质量的数据集;其次,引入二阶扩展卡尔曼滤波对系统状态进行精确估计,进一步增强数据的平稳度和可靠性;最后,设计ETSVR算法对处理后的高质量数据集进行学习,以构建海洋航行器的运动预测模型,实现精准运动预测,并借助误差触发机制提升系统的实时性与计算效率。基于湖试数据的实验结果表明,所提出的智能运动预测系统在多项误差指标上均显著优于传统的线性回归算法。例如,在侧向速度预测中,均方误差较线性回归算法降低约53.2%;在转艏角速度预测中,最大误差减少了约58.2%。这些结果表明,提出的级联滤波与ETSVR算法相结合的智能预测系统,能够显著提升海洋航行器在复杂未知环境中的运动预测精度,具有较好的应用前景和重要的研究意义。
文摘Binary oxide systems（Cu Cr2O4, Cu Co2O4）, deposited onto cordierite monoliths of honeycomb structure with a second support（finely dispersed Al2O3）, were prepared as filters for catalytic combustion of diesel soot using internal combustion engine’s gas exhausts（O2, NOx, H2 O, CO2） and O3 as oxidizing agents. It is shown that the second support increases soot capacity of aforementioned filters, and causes dispersion of the particles of spinel phases as active components enhancing thereby catalyst activity and selectivity of soot combustion to CO2. Oxidants used can be arranged with reference to decreasing their activity in a following series： O3 NO2〉 H2 O 〉 NO 〉 O2〉 CO2. Ozone proved to be the most efficient oxidizing agent： the diesel soot combustion by O3 occurs intensively（in the presence of copper chromite based catalyst） even at closing to ambient temperatures.Results obtained give a basis for the conclusion that using a catalytic coating on soot filters in the form of aforementioned binary oxide systems and ozone as the initiator of the oxidation processes is a promising approach in solving the problem of comprehensive purification of automotive exhaust gases at relatively low temperatures, known as the ＂cold start＂ problem.
