Zobrazeno 1 - 10
of 43
pro vyhledávání: '"Zhan, Tianxiang"'
Determining the reliability of evidence sources is a crucial topic in Dempster-Shafer theory (DST). Previous approaches have addressed high conflicts between evidence sources using discounting methods, but these methods may not ensure the high effici
Externí odkaz:
http://arxiv.org/abs/2411.00848
In pattern recognition, handling uncertainty is a critical challenge that significantly affects decision-making and classification accuracy. Dempster-Shafer Theory (DST) is an effective reasoning framework for addressing uncertainty, and the Random P
Externí odkaz:
http://arxiv.org/abs/2410.22772
In practical scenarios, time series forecasting necessitates not only accuracy but also efficiency. Consequently, the exploration of model architectures remains a perennially trending topic in research. To address these challenges, we propose a novel
Externí odkaz:
http://arxiv.org/abs/2405.06419
Developing a general information processing model in uncertain environments is fundamental for the advancement of explainable artificial intelligence. Dempster-Shafer theory of evidence is a well-known and effective reasoning method for representing
Externí odkaz:
http://arxiv.org/abs/2405.02653
In wireless sensor networks (WSNs), coverage and deployment are two most crucial issues when conducting detection tasks. However, the detection information collected from sensors is oftentimes not fully utilized and efficiently integrated. Such sensi
Externí odkaz:
http://arxiv.org/abs/2403.15728
Evidence theory is widely used in decision-making and reasoning systems. In previous research, Transferable Belief Model (TBM) is a commonly used evidential decision making model, but TBM is a non-preference model. In order to better fit the decision
Externí odkaz:
http://arxiv.org/abs/2402.13058
Fuzzy time series forecasting (FTSF) is a typical forecasting method with wide application. Traditional FTSF is regarded as an expert system which leads to loss of the ability to recognize undefined features. The mentioned is the main reason for poor
Externí odkaz:
http://arxiv.org/abs/2305.08890
Autor:
Zhan, Tianxiang, Wu, Chunwang, Zhang, Manchao, Qin, Qingqing, Yang, Xueying, Hu, Han, Su, Wenbo, Zhang, Jie, Chen, Ting, Xie, Yi, Wu, Wei, Chen, Pingxing
Leggett-Garg inequality (LGI) studies the temporal correlation in the evolution of physical systems. Classical systems obey the LGI but quantum systems may violate it. The extent of the violation depends on the dimension of the quantum system and the
Externí odkaz:
http://arxiv.org/abs/2209.07254
Time series forecasting is a hot spot in recent years. Visibility Graph (VG) algorithm is used for time series forecasting in previous research, but the forecasting effect is not as good as deep learning prediction methods such as methods based on Ar
Externí odkaz:
http://arxiv.org/abs/2111.04071