Zobrazeno 1 - 10
of 29
pro vyhledávání: '"Zhao-Qian Chen"'
Autor:
Xiang Gao, Bradley Mattson, Ai-Jing Li, Yi Huang, Shan Li, Ge Chen, Yu-Ning Pan, Zhao-Qian Chen
Publikováno v:
Clinical Neuroradiology. 29:277-284
This study evaluated the quality of computed tomography (CT) and CT angiography images generated using the single-energy metal artifact reduction (SEMAR) algorithm during perfusion examination in patients who had undergone reconstruction with neurosu
Publikováno v:
Journal of Network and Computer Applications. 30:1366-1376
Multi-agent reinforcement learning technologies are mainly investigated from two perspectives of the concurrence and the game theory. The former chiefly applies to cooperative multi-agent systems, while the latter usually applies to coordinated multi
Autor:
Zhi-Hua Zhou, Zhao-Qian Chen
Publikováno v:
Knowledge-Based Systems. 15:515-528
In this paper, a hybrid learning approach named hybrid decision tree (HDT) is proposed. HDT simulates human reasoning by using symbolic learning to do qualitative analysis and using neural learning to do subsequent quantitative analysis. It generates
Publikováno v:
Knowledge and Information Systems. 2:115-129
In this paper, a fast adaptive neural network classifier named FANNC is proposed. FANNC exploits the advantages of both adaptive resonance theory and field theory. It needs only one-pass learning, and achieves not only high predictive accuracy but al
Publikováno v:
GrC
Frequent patterns mining are widely used in many practical data mining applications. Therefore, current research focuses on developing frequent patterns mining algorithms of high performances and FP-growth is proved as an important and efficient freq
Publikováno v:
CIMCA/IAWTIC
Though deeply analyzing and comparing the mechanism of genetic algorithm and reinforcement learning, a novel algorithm for controlling genetic algorithms using reinforcement learning named SCGA, is proposed and analyzed theoretically. In the existing
Publikováno v:
CIMCA/IAWTIC
Options have proven to be useful to accelerate agent's learning in many reinforcement learning tasks, determining useful subgoals is a key step for agent to create options. A K-cluster algorithm for automatic discovery of subgoals is presented in thi
Publikováno v:
ICITA (1)
Multi-agent reinforcement learning technologies are mainly investigated from two perspectives: one is from the concurrence, and the other from the game theory. The former chiefly applies to cooperative multi-agent systems, while the latter usually ap
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783540283256
ICNC (2)
ICNC (2)
The well-known eigenface method uses a single eigenspace to recognize faces. However, it is not enough to represent face images with large variations, such as illumination and pose variations. To overcome this disadvantage, many researchers have intr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::719f96fa7c817e603eb9391e43c290a3
https://doi.org/10.1007/11539117_9
https://doi.org/10.1007/11539117_9
Publikováno v:
PRICAI 2004: Trends in Artificial Intelligence ISBN: 9783540228172
PRICAI
PRICAI
Classical iterated belief revision methods rarely take into account the impact of the uncertain information. In this paper, an approach of believability based iterated belief revision(BIBR) is presented. BIBR relates the belief revision in the multi-
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c08524c1ddd6d7a6e8a3754fb529b6e4
https://doi.org/10.1007/978-3-540-28633-2_102
https://doi.org/10.1007/978-3-540-28633-2_102