Zobrazeno 1 - 10
of 39
pro vyhledávání: '"Xiyu Liu"'
Autor:
Bao Wang, Jianhua Qu, Jie Xue, Chengwei Wang, Xuejun Liu, Xuqun Tang, Xiyu Liu, Yang Ming, Zekun Jiang, Shangchen Xu, Ligang Chen, Dengwang Li, Ying Mao, Yingchao Liu
Publikováno v:
Neuro Oncol
Background Three-dimensional T1 magnetization prepared rapid acquisition gradient echo (3D-T1-MPRAGE) is preferred in detecting brain metastases (BM) among MRI. We developed an automatic deep learning–based detection and segmentation method for BM
Publikováno v:
Complexity, Vol 2019 (2019)
As one of the important techniques to explore unknown places for users, the methods that are proposed for point-of-interest (POI) recommendation have been widely studied in recent years. Compared with traditional recommendation problems, POI recommen
Publikováno v:
IEEE/CAA Journal of Automatica Sinica. 6:1268-1280
Fault diagnosis is an important measure to ensure the safety of production, and all kinds of fault diagnosis methods are of importance in actual production process. However, the complexity and uncertainty of production process often lead to the chang
Autor:
Xiyu Liu, Xiaojian Yang
Publikováno v:
Human Centered Computing ISBN: 9783030706258
HCC
HCC
In the field of financial time series prediction, multivariate time series is increasingly considered as the input of the prediction model and non-stationary time series have always been the most common data sets. However, the processing efficiency i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c89342b4eb22422f141f8f641662a091
https://doi.org/10.1007/978-3-030-70626-5_19
https://doi.org/10.1007/978-3-030-70626-5_19
Publikováno v:
PLoS ONE
PLoS ONE, Vol 15, Iss 12, p e0242083 (2020)
PLoS ONE, Vol 15, Iss 12, p e0242083 (2020)
A DNA (DeoxyriboNucleic Acid) algorithm is proposed to solve the job shop scheduling problem. An encoding scheme for the problem is developed and DNA computing operations are proposed for the algorithm. After an initial solution is constructed, all p
Publikováno v:
Computational Intelligence and Neuroscience, Vol 2020 (2020)
Computational Intelligence and Neuroscience
Computational Intelligence and Neuroscience
A new clustering membrane system using a complex chained P system (CCP) based on evolutionary mechanism is designed, developed, implemented, and tested. The purpose of CCP is to solve clustering problems. In CCP, two kinds of evolution rules in diffe
Publikováno v:
Green, Pervasive, and Cloud Computing ISBN: 9783030150921
GPC
GPC
Forecasting container throughput accurately is crucial to the success of any port operation policy. At present, prediction of container throughput is mainly based on traditional time series analysis or single artificial neural network technology. Rec
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::61fb0bcf80a6f16e71128e19c41f8fe6
https://doi.org/10.1007/978-3-030-15093-8_32
https://doi.org/10.1007/978-3-030-15093-8_32
Autor:
Xiyu Liu, Zhenni Jiang
Publikováno v:
Processes
Volume 8
Issue 10
Processes, Vol 8, Iss 1326, p 1326 (2020)
Volume 8
Issue 10
Processes, Vol 8, Iss 1326, p 1326 (2020)
In this paper, a data clustering method named consensus fuzzy k-modes clustering is proposed to improve the performance of the clustering for the categorical data. At the same time, the coupling DNA-chain-hypergraph P system is constructed to realize
Publikováno v:
Human Centered Computing ISBN: 9783319745206
HCC
HCC
Many consensus clustering methods ensemble all the basic partitionings (BPs) with the same weight and without considering their contribution to consensus result. We use the Normalized Mutual Information (NMI) theory to design weight for BPs that part
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::12d6b351c824dec68309d6a9b595e614
https://doi.org/10.1007/978-3-319-74521-3_6
https://doi.org/10.1007/978-3-319-74521-3_6
Publikováno v:
Entropy, Vol 19, Iss 11, p 578 (2017)
Entropy; Volume 19; Issue 11; Pages: 578
Entropy; Volume 19; Issue 11; Pages: 578
MRI segmentation is critically important for clinical study and diagnosis. Existing methods based on soft clustering have several drawbacks, including low accuracy in the presence of image noise and artifacts, and high computational cost. In this pap