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Authors: Chen, Wei | Li, Dandan

Article Type: Research Article

Abstract: This paper discusses differential mean value theorems based on uncertainty differential equation. Firstly, we propose some uncertain differential mean value theorems driven by canonical process, in which finite interval and infinite interval cases are considered respectively. Then the stability for uncertain differential mean value theorem is discussed under the Lipschitz conditions. Finally, some examples are given.

Keywords: Mean value theorems, uncertain differential equation, canonical process, stability

DOI: 10.3233/JIFS-171399

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 4, pp. 2343-2350, 2018

Authors: Zhang, Jun | Li, Dandan | Chen, Wei

Article Type: Research Article

Abstract:  This paper presents some continuous dependence theorems on solutions of uncertain differential equations based on uncertain measure. We first introduce some properties on solution of uncertain differential equation. And then, we provide a continuous dependence theorem, and a continuity theorem to the initial value. In the proposed continuity theorem, the solution is regarded as a ternary function of initial values. Furthermore, we discuss how the solution continuously depends on initial value and parameter, and propose two theorems, namely, continuous dependence theorem on parameter, and continuity theorem on parameter to the initial value.

Keywords: Uncertain variable, numerical series, positive numerical series, convergence in measure

DOI: 10.3233/JIFS-182815

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 6455-6465, 2019

Authors: Li, Dandan | Wu, Yuxiang | Zhu, Shilei | Li, Zhongkang

Article Type: Research Article

Abstract: Aiming at the weak capacity of the parameter identification methods of Jiles–Atherton (J–A) hysteresis model, such as slow convergence speed and low convergence accuracy, an improved sparrow search algorithm (IM-SSA) is proposed based on mutation crossover operator and T-distribution perturbation strategy in this paper to improve the convergence speed and accuracy of parameter identification method. Firstly, the initial population of the sparrow search algorithm is enriched by Tent chaotic sequence, which expand the search area. Then, the adaptive crossover and mutation operator is introduced into the finders population to enrich the diversity of the finders population and balance the global …and local search ability of the algorithm. Secondly, the T-distribution perturbation or differential mutation is used to perturb the population after each iteration according to the individual characteristics, which can avoid the population singularity in the later stage of the algorithm and enhance the ability of jump out of the local optimal value of the algorithm. Finally, the proposed parameter identification method is used to identify the parameters of the J–A hysteresis model, which are used to simulate the magnetic properties of Non-oriented silicon steel sheets with different magnetic induction intensity. The calculation result is compared with the experiment ones. The results proved that the proposed method has faster convergence speed and higher convergence accuracy. Show more

Keywords: Cross-mutation operator, improved sparrow search algorithm, J–A hysteresis model, parameter identification, t-distribution perturbation

DOI: 10.3233/JAE-220050

Citation: International Journal of Applied Electromagnetics and Mechanics, vol. 70, no. 4, pp. 525-535, 2022

Authors: Wang, Bin | Miao, Liwen | Niu, Yan | Cao, Rui | Li, Dandan | Yan, Pengfei | Guo, Hao | Yan, Tianyi | Wu, Jinglong | Xiang, Jie | Alzheimer’s Disease Neuroimaging Initiative

Article Type: Research Article

Abstract: Alzheimer’s disease (AD) disrupts the topological architecture of whole-brain connectivity. Minimum spanning tree (MST), which captures the most important connections in a network, has been considered an unbiased method for brain network analysis. However, the alterations in the MST of functional brain networks during the progression of AD remain unclear. Here, we performed an MST analysis to examine the alterations in functional networks among normal controls (NCs), mild cognitive impairment (MCI) patients, and AD patients. We identified substantial differences in the connections among the three groups. The maximum betweenness centrality, leaf number, and tree hierarchy of the MSTs showed significant …group differences, indicating a more star-like topology in the MCI patients and a more line-like topology in the NCs and AD patients. These findings may correspond to changes in the core of the functional brain networks. For nodal properties (degree and betweenness centrality), we determined that brain regions around the cingulate gyrus, occipital lobes, subcortex, and inferior temporal gyrus showed significant differences among the three groups and contributed to the global topological alterations. The leaf number and tree hierarchy, as well as the nodal properties, were significantly correlated with clinical features in the MCI and AD patients, which demonstrated that more star-to-line topology changes were associated with worse cognitive performance in these patients. These findings indicated that MST properties could capture slight alterations in network topology, particularly for the differences between NCs and MCI patients, and may be applicable as neuroimaging markers of the early stage of AD. Show more

Keywords: Alzheimer’s disease, brain networks, functional magnetic resonance imaging, mild cognitive impairment, minimum spanning tree

DOI: 10.3233/JAD-180603

Citation: Journal of Alzheimer's Disease, vol. 65, no. 4, pp. 1093-1107, 2018