Deep Learning(DL)is a subfield of machine learning that significantly impacts extracting new knowledge.By using DL,the extraction of advanced data representations and knowledge can be made possible.Highly effective DL...Deep Learning(DL)is a subfield of machine learning that significantly impacts extracting new knowledge.By using DL,the extraction of advanced data representations and knowledge can be made possible.Highly effective DL techniques help to find more hidden knowledge.Deep learning has a promising future due to its great performance and accuracy.We need to understand the fundamentals and the state‐of‐the‐art of DL to leverage it effectively.A survey on DL ways,advantages,drawbacks,architectures,and methods to have a straightforward and clear understanding of it from different views is explained in the paper.Moreover,the existing related methods are compared with each other,and the application of DL is described in some applications,such as medical image analysis,handwriting recognition,and so on.展开更多
To reduce the uncertainty and reworks in complex projects,a novel mechanism is systematically developed in this paper based on two classical design structure matrix(DSM)clustering methods:Loop searching method(LSM)and...To reduce the uncertainty and reworks in complex projects,a novel mechanism is systematically developed in this paper based on two classical design structure matrix(DSM)clustering methods:Loop searching method(LSM)and function searching method(FSM).Specifically,the optimal working areas for the two clustering methods are first obtained quantitatively in terms of non-zero fraction(NZF)and singular value modularity index(SMI),in which the whole working area is divided into six sub-zones.Then,a judgement procedure is proposed for conveniently choosing the optimal DSM clustering method,which makes it easy to determine which DSM clustering method performs better for a given case.Subsequently,a conceptual model is constructed to assist project managers in effectively analyzing the network of projects and greatly reducing reworks in complex projects by defining preventive actions.Finally,the aircraft design process is presented to show how the proposed judgement mechanism can be utilized to reduce the reworks in actual projects.展开更多
文摘Deep Learning(DL)is a subfield of machine learning that significantly impacts extracting new knowledge.By using DL,the extraction of advanced data representations and knowledge can be made possible.Highly effective DL techniques help to find more hidden knowledge.Deep learning has a promising future due to its great performance and accuracy.We need to understand the fundamentals and the state‐of‐the‐art of DL to leverage it effectively.A survey on DL ways,advantages,drawbacks,architectures,and methods to have a straightforward and clear understanding of it from different views is explained in the paper.Moreover,the existing related methods are compared with each other,and the application of DL is described in some applications,such as medical image analysis,handwriting recognition,and so on.
基金supported by the National Natural Science Foundation of China (Nos. 71471087, 71071076, 61673209)the Funding for Outstanding Doctoral Dissertation in Nanjing University of Aeronautics and Astronautics (No. BCXJ17-11)the Research and Innovation Program for Graduate Education of Jiangsu Province (No. KYZZ160145)
文摘To reduce the uncertainty and reworks in complex projects,a novel mechanism is systematically developed in this paper based on two classical design structure matrix(DSM)clustering methods:Loop searching method(LSM)and function searching method(FSM).Specifically,the optimal working areas for the two clustering methods are first obtained quantitatively in terms of non-zero fraction(NZF)and singular value modularity index(SMI),in which the whole working area is divided into six sub-zones.Then,a judgement procedure is proposed for conveniently choosing the optimal DSM clustering method,which makes it easy to determine which DSM clustering method performs better for a given case.Subsequently,a conceptual model is constructed to assist project managers in effectively analyzing the network of projects and greatly reducing reworks in complex projects by defining preventive actions.Finally,the aircraft design process is presented to show how the proposed judgement mechanism can be utilized to reduce the reworks in actual projects.
