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Institution

Anhui University of Finance and Economics

EducationBengbu, China
About: Anhui University of Finance and Economics is a education organization based out in Bengbu, China. It is known for research contribution in the topics: China & Hopf bifurcation. The organization has 933 authors who have published 1070 publications receiving 11500 citations. The organization is also known as: AUFE.


Papers
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Journal ArticleDOI
TL;DR: In this article, the existence of periodic solutions for more general state-dependent delay logistic equations is investigated by using the continuation theorem of coincidence degree theory, and several sufficient conditions are given.
Abstract: In this paper, by using the continuation theorem of coincidence degree theory, we investigate the existence of periodic solutions for more general state-dependent delay logistic equations. Several sufficient conditions are given, and the obtained conditions possess important significance in both theories and applications.

9 citations

Journal Article
TL;DR: Composition operators with closed range on the Bloch space were studied in this paper, where sufficient and necessary conditions were given for the composition operators with a closed range and sufficient conditions for the compositional operators with the closed range.
Abstract: Composition operators with closed range on the Bloch space was studiedNew sufficient and necessary conditions were given for the composition operators with closed range on the Bloch space

9 citations

Journal ArticleDOI
TL;DR: This paper proposes a novel method for Visual-Inertial Odometry (VIO) based on a RGB-D camera and an Inertial Measurement Unit (IMU) and combines feature- and ICP-based visual odometry to provide accurate and robust estimation.
Abstract: This paper proposes a novel method for Visual-Inertial Odometry (VIO) based on a RGB-D camera and an Inertial Measurement Unit (IMU). To fuse the data from visual and inertial measurements, an Extended Kalman Filter (EKF) is deployed, while we propose an iterative procedure to reduce the linearization error. Our method not only estimates the trajectory of the camera, but also calibrates the gravity and the camera extrinsics, i.e. the relative pose between camera and IMU. For what concerns visual odometry, a KeyFrame strategy is employed, as it tends to outperform frame-to-frame alignment. Moreover, we combine feature- and ICP-based visual odometry, so to provide accurate and robust estimation. Evaluation results on simulation and real data show the effectiveness of our approach.

9 citations

Journal ArticleDOI
TL;DR: The deep belief model has a good development prospect in agricultural product price forecasting, and it can provide relevant reference for the establishment and research of other agricultural productprice forecasting models.
Abstract: To study the impact of the agricultural information system based on the Internet of Things (IoT) on the income of agricultural products, an agricultural information system was constructed based on the agricultural IoT technology, and its impact on the income of agricultural products was discussed through the deep belief network. First, the relevant theories of agricultural IoT were introduced. Then, an agricultural information system based on agricultural IoT technology was constructed, and a deep belief network model was proposed. The vegetable prices and influencing factors were collected. The data were distributed in the range of 0–1 after normalization. The collinearity between the data was eliminated through principal component analysis. Then, the principal component analysis of vegetable prices and influencing factors from 2015 to 2019 was performed. A total of 96 sample data of calibration set and 24 sample data of test machine were collected. The optimal number of hidden layers of the deep belief network model and the number of nodes contained in the hidden layer were obtained through experiments. The results show that the first, second, and third hidden layers have 8, 6, and 10 nodes, respectively; the prediction accuracy of the deep belief network model is more accurate than that of the BP neural network and wavelet neural network. Besides, the absolute value of the prediction error of the deep belief model is within 0.1, which has good prediction accuracy. In short, the deep belief model has a good development prospect in agricultural product price forecasting, and it can provide relevant reference for the establishment and research of other agricultural product price forecasting models.

9 citations

Journal ArticleDOI
TL;DR: In this article, sufficient and realistic conditions are obtained for the existence of positive periodic solutions of a class of neutral delays equation, and an algebraic criterion of existence for a more general neutral Lotka-Volterra equation with several delays is obtained, which extends and improves the previous results.
Abstract: Applying the theory of topological degree, sufficient and realistic conditions are obtained for the existence of positive periodic solutions of a class of neutral delays equation. From those conditions, an algebraic criterion of existence for a more general neutral Lotka–Volterra equation with several delays is obtained, which extends and improves the previous results. In addition, this method is of great interest in many applications such as biomathematics.

9 citations


Authors

Showing all 949 results

NameH-indexPapersCitations
Xiaoping Liu5926810535
Malin Song421905961
Jose Luis Menaldi22861804
Ming-Hsiang Chen22952766
Jung Wan Lee20891850
Xueli Chen191281273
Umer Shahzad1846979
Tony Fang18631008
Yan Zhang16961742
Zhiyang Shen1231345
Zeya Wang1229870
Kai Wang1130401
Zizhen Zhang938240
Lianbiao Cui912630
Kefei You929299
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202312
202222
2021230
2020162
201992
201863