将人工神经网络（ANN）与蚁群优化（ACO）算法相结合，对直喷式柴油机的NOx和碳烟排放进行建模与优化。采用前馈多层感知器（MLP）网络来表示输入参数（发动机转速、进气温度、喷油量和功率）与输出参数之间的关系
the combination of artificial neural network (ANN) and ant colony optimization (ACO) algorithm has been utilized for modeling and reducing NOx and soot emissions a direct injection diesel engine. A feed-forward multi-layer perceptron (MLP) network is used to represent the relationship between the input parameters (i.e., engine speed, intake air temperature, rate of fuel mass injected, and power) on the one hand and the output parameters
资源文件列表
aco%ann/ANT_ant_new.m , 4088
aco%ann/ANT_object_func_ant.m , 1492
aco%ann/object_func.m , 1583