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5. Combining artificial neural network and multi-objective optimization to reduce a heavy-duty diesel e

Combining artificial neural network and multi-objective optimization to reduce a heavy-duty diesel e

来源 :中南大学学报：英文版 | 被引量 : 0次 | 上传用户：dickensking

【摘 要】

：

Nondominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ) is well known for engine optimization problem. Artificial neural networks(ANNs) followed by multi-objective o

【作 者】

：

Amir-Hasan Kakaee Pourya Rahna 

【机 构】

：

SchoolofAutomotiveEngineering

【出 处】

：

中南大学学报：英文版

【发表日期】

：

2015年11期

【关键词】

：

engine fuel CONSUMPTION EMISSIONS neural networks engine fuel consumption emissi 

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论文部分内容阅读

Nondominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ) is well known for engine optimization problem. Artificial neural networks(ANNs) followed by multi-objective optimization including a NSGA-Ⅱ and strength pareto evolutionary algorithm(SPEA2) were used to opt

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