Presents the fuzzy neural network optimized by hybrid coded genetic algorithm of decimal encoding and binary encoding, the searching ability and stability of genetic algorithms enhanced by using binary encoding during...Presents the fuzzy neural network optimized by hybrid coded genetic algorithm of decimal encoding and binary encoding, the searching ability and stability of genetic algorithms enhanced by using binary encoding during the crossover operation and decimal encoding during the mutation operation, and the way of accepting new individuals by probability adopted, by which a new individual is accepted and its parent is discarded when its fitness is higher than that of its parent, and a new individual is accepted by probability when its fitness is lower than that of its parent. And concludes with calculations made with an example that these improvements enhance the speed of genetic algorithms to optimize the fuzzy neural network controller.展开更多
Although the wireless network is widely used in many fields,its characteristics such as high bit error rate and broadcast links may block its development.Network coding is an artistic way to exploit its intrinsic char...Although the wireless network is widely used in many fields,its characteristics such as high bit error rate and broadcast links may block its development.Network coding is an artistic way to exploit its intrinsic characteristics to increase the network reliability.Some people research network coding schemes for inter-flow or intra-flow,each type with its own advantages and disadvantages.In this paper,we propose a new mechanism,called MM-NCOPE,which integrates the idea of inter-flow and intra-flow coding.On the one hand,MM-NCOPE utilizes random liner coding to encode the NCOPE packets while NCOPE is a sub-protocol for optimizing the COPE algorithm by iteration.In NCOPE,packets are automatically matched by size to be coded.As a result,it improves the coding gain in some level.On the other hand,we adopt the partial Acknowledgement retransmission scheme to achieve high compactness and robustness.ACK is an independent packet with the highest priority rather than a part of the data packets.Compared with existing works on opportunistic network coding,our approach ensures the reliability of wireless links and improves the coding gain.展开更多
为充分利用机场延误状态信息的时间相关性,提高机场延误预测精度,提出一种基于混合编码和长短时记忆网络(Long Short Term Memory,LSTM)的机场延误预测方法。该方法首先将机场信息、航班信息和气象信息进行数据预处理,得到机场延误数据...为充分利用机场延误状态信息的时间相关性,提高机场延误预测精度,提出一种基于混合编码和长短时记忆网络(Long Short Term Memory,LSTM)的机场延误预测方法。该方法首先将机场信息、航班信息和气象信息进行数据预处理,得到机场延误数据;然后,利用LSTM网络对机场延误数据进行特征提取;最后,构建Softmax分类器对机场延误分类预测。实验结果表明,本文基于机场延误数据在数据预处理阶段提出的混合编码方法,可使预测准确率提高约5%。同时,利用LSTM网络来提取数据的时间相关特征信息,网络模型的预测准确率最终可达94.01%。并且利用不同机场数据对网络的普适性分析结果表明,该算法更适合于原始数据量大的中大型枢纽机场。展开更多
文摘Presents the fuzzy neural network optimized by hybrid coded genetic algorithm of decimal encoding and binary encoding, the searching ability and stability of genetic algorithms enhanced by using binary encoding during the crossover operation and decimal encoding during the mutation operation, and the way of accepting new individuals by probability adopted, by which a new individual is accepted and its parent is discarded when its fitness is higher than that of its parent, and a new individual is accepted by probability when its fitness is lower than that of its parent. And concludes with calculations made with an example that these improvements enhance the speed of genetic algorithms to optimize the fuzzy neural network controller.
基金National Natural Science Foundation of China under Grant No. 60903196,60903175National Critical Patented Projects in the Next Generation Broadband Wireless Mobile Communication Network under Grant No. 2010ZX03006-001-01+1 种基金National High Technical Research and Development Program of China under Grant No. 2009AA01Z418Educational Commission of Hubei Province of China under Grant No. D20114401
文摘Although the wireless network is widely used in many fields,its characteristics such as high bit error rate and broadcast links may block its development.Network coding is an artistic way to exploit its intrinsic characteristics to increase the network reliability.Some people research network coding schemes for inter-flow or intra-flow,each type with its own advantages and disadvantages.In this paper,we propose a new mechanism,called MM-NCOPE,which integrates the idea of inter-flow and intra-flow coding.On the one hand,MM-NCOPE utilizes random liner coding to encode the NCOPE packets while NCOPE is a sub-protocol for optimizing the COPE algorithm by iteration.In NCOPE,packets are automatically matched by size to be coded.As a result,it improves the coding gain in some level.On the other hand,we adopt the partial Acknowledgement retransmission scheme to achieve high compactness and robustness.ACK is an independent packet with the highest priority rather than a part of the data packets.Compared with existing works on opportunistic network coding,our approach ensures the reliability of wireless links and improves the coding gain.
文摘为充分利用机场延误状态信息的时间相关性,提高机场延误预测精度,提出一种基于混合编码和长短时记忆网络(Long Short Term Memory,LSTM)的机场延误预测方法。该方法首先将机场信息、航班信息和气象信息进行数据预处理,得到机场延误数据;然后,利用LSTM网络对机场延误数据进行特征提取;最后,构建Softmax分类器对机场延误分类预测。实验结果表明,本文基于机场延误数据在数据预处理阶段提出的混合编码方法,可使预测准确率提高约5%。同时,利用LSTM网络来提取数据的时间相关特征信息,网络模型的预测准确率最终可达94.01%。并且利用不同机场数据对网络的普适性分析结果表明,该算法更适合于原始数据量大的中大型枢纽机场。
