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Asymptotic Inference in the Random Coefficient Autoregressive Model with Time-functional Variance Noises

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Acta Mathematicae Applicatae Sinica 2024年第2期40卷 320-346页

作者： En-wen ZHU Zi-wei DENG Han-jun ZHANG Jun CAO Xiao-hui LIU Department of Mathematics and Statistics Changsha University of Science and TechnologyChangsha 410114China School of Mathematics and Computational Science Xiangtan UniversityXiangtan 411105China School of Statistics and Data Science and Key Laboratory of Data Science in Finance and EconomicsJiangxi University of Finance and EconomicsNanchang 330013China

This paper considers the random coefficient autoregressive model with time-functional variance noises,hereafter the RCA-TFV *** first establish the consistency and asymptotic normality of the conditional least squares estimator for the constant *** semiparametric least squares estimator for the variance of the random coefficient and the nonparametric estimator for the variance function are constructed,and their asymptotic results are reported.A simulation study is presented along with an analysis of real data to assess the performance of our method in finite samples.

关键词： random coefficient autoregressive model time-functional variance conditional least squares semiparametric least squares

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Block Basis for Modular Coinvariants of Pseudo-Reflection Groups

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Algebra Colloquium 2024年第1期31卷 41-48页

作者： Ke Ou School of Statistics and Mathematics Yunnan university of finance and economics Kunming 650221China

We investigate the block basis for modular coinvariants of finite pseudo-reflection *** are particularly interested in the case of a subgroup G of the parabolic subgroups of GLn(q)which generalizes the Weyl groups of ... 详细信息

关键词： modular invariant theory pseudo-reflection group block basis coinvariant

Application of Fuyang Paper Cutting Art in Cultural and Creative Design from the Perspective of Rural Revitalization

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Journal of Landscape Research 2024年第3期16卷 59-62页

作者： KANG Wenwen School of Arts Anhui University of Finance&EconomicsBengbuAnhui 233030China

The application significance of Fuyang paper cutting art in cultural and creative design from the perspective of rural revitalization was discussed,and the implementation principles and specific practices of applying the elements and techniques of Fuyang traditional paper cutting art in cultural and creative products with local features were analyzed to provide reference for rural revitalization and development of cultural industry.

关键词： Rural revitalization Fuyang paper cutting Cultural and creative design

Ergodicity of a Special Class of Markov Chains

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Acta Mathematicae Applicatae Sinica 2024年

作者： Xin-yu HU Ping HE School of Mathematics Shanghai University of Finance and Economics

The paper focuses on the ergodicity of a φ-irreducible Markov chain {X_n, n ≥ 0} that is generated iteratively through the expression Xn+1= f（X_n） + ?n+1. Here, {?_n, n ≥ 1} is a sequence of independent identically distributed centralized random variables, f（·） is an R-valued continuous function, and X0is arbitrary but independent of {?_n, n ≥ 1}. Our main contribution is to provide necessary and sufficient conditions for ergodicity of this special class of Markov chains. We also present a generalized approach for f（·） in the end.

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Generalized Laws of Importation and Cross-Migrativity Based on(D, N)-Implications

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Journal of Mathematical Research with Applications 2024年第5期 583-595页

作者： Nana MA School of Mathematics Xi'an University of Finance and Economics

In the present article we study the generalized laws of importation and crossmigrativity based on(D, N)-implications. On the one hand, we consider the generalized law of importation I(T(x, α), y) = I(x, J(α, y)), when T is concretized as a fuzzy conjunction C, I and J are concretized as(D, N)-implications generated by a fuzzy disjunction D and a fuzzy negation N. On the other hand, we discuss the cross-migrativity of fuzzy disjunctions over fuzzy implications, that is, I(x, D(y, z)) = D(y, I(x, z)), where I is a fuzzy implication, D is a fuzzy disjunction. In addition, we study the relationship between the(α-)cross-migrative of(I, D) and the(α-)cross-law of importation(I, ID,N, C).

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Optimal Reinsurance Strategy Based on the Lundberg Exponent

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Journal of Systems Science & Complexity 2024年

作者： WANG Yeshunying MENG Hui LIAO Pu School of Insurance Central University of Finance and Economics Beijing 100081 China China Institute for Actuarial Science Central University of Finance and Economics

In this paper, the authors investigate the optimal per-claim reinsurance problem under the continuous-time framework to minimize the insurer’s ruin probability based on the Lundberg exponent. Considering reinsurance participants’ diversified risk preferences, the authors assume that the reinsurance premium is calculated by a combined premium principle, including the expected value premium principle and upper moment premium principle. Then, the authors derive the insurer’s optimal reinsurance strategy satisfying the principle of indemnity and the incentive compatibility condition in an infinite reinsurance space based on the point-wise optimization approach. Besides, the proposed work emphasizes the optimality and admissibility of the combination of the excess of loss reinsurance and its dual form when a piecewise reinsurance premium principle is considered. As a special case, the optimal reinsurance strategy under the expected value premium principle reduces to the classic ***, the numerical analyses are provided to illustrate the effects of the main parameters on the maximal Lundberg exponent and the optimal reinsurance strategy.

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A Study on Idea Adoption Prediction Model Based on SMOTE-AdaBoost: Taking Salesforce Platform as an Example

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Journal of Systems Science and Information 2024年第4期12卷 476-490页

作者： Yunjiang XI Futao HUANG Lu HUANG Xiao LIAO Juan YU School of Business Administration South China University of Technology School of Internet finance and Information Engineering Guangdong University of Finance School of economics and Management Fuzhou University

In the context of information overload, companies often struggle to effectively identify valuable ideas on their open innovation platforms. In this article, we propose an idea adoption strategy based on machine learning. We used data from a well-known open innovation platform, Salesforce, and extracted characteristic variables using the Information Adoption Model. Four classification models were then constructed based on AdaBoost, Random Forest, SVM and Logistic Regression models. Due to significant differences in the number of positive and negative samples in the OIP, we used the SMOTE method to address the problem of data imbalance. The results of the study showed that the ensemble learning models were more accurate in identifying valuable ideas than the individual machine learning models. When comparing the two ensemble learning models, AdaBoost outperformed Random Forest in predicting both positive and negative class samples. The SMOTE-AdaBoost model achieved a recall of 0.93, a precision of 0.92 and an impressive AUC of 0.98 in identifying adopted ideas, which could well identify valuable ideas and has implications for improving the efficiency and quality of idea adoption in OIP. The shortcoming of this work is that it only investigated a single platform. In the future, we will consider extending this method to different platforms and multiple classification problems.

关键词： open innovation platform AdaBoost information adoption ensemble learning

A Mean-Field Game for a Forward-Backward Stochastic System With Partial Observation and Common Noise

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IEEE/CAA Journal of Automatica Sinica 2024年第3期11卷 746-759页

作者： Pengyan Huang Guangchen Wang Shujun Wang Hua Xiao the School of Control Science and Engineering Shandong University the School of Statistics and Mathematics Shandong University of Finance and Economics IEEE the School of Management Shandong University the School of Mathematics and Statistics Shandong University

This paper considers a linear-quadratic(LQ) meanfield game governed by a forward-backward stochastic system with partial observation and common noise,where a coupling structure enters state equations,cost functionals and observation ***,to reduce the complexity of solving the meanfield game,a limiting control problem is *** virtue of the decomposition approach,an admissible control set is *** a filter technique and dimensional-expansion technique,a decentralized control strategy and a consistency condition system are derived,and the related solvability is also ***,we discuss an approximate Nash equilibrium property of the decentralized control ***,we work out a financial problem with some numerical simulations.

关键词： Decentralized control strategy ϵ-Nash equilibrium forward-backward stochastic system mean-field game partial observation

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A Degradation Type Adaptive and Deep CNN-Based Image Classification Model for Degraded Images

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工程与科学中的计算机建模(英文) 2024年第1期138卷 459-472页

作者： Huanhua Liu Wei Wang Hanyu Liu Shuheng Yi Yonghao Yu Xunwen Yao School of Information Technology and Management Hunan University of Finance and EconomicsChangsha410205China

Deep Convolutional Neural Networks(CNNs)have achieved high accuracy in image classification tasks,however,most existing models are trained on high-quality images that are not subject to image *** practice,images are often affected by various types of degradation which can significantly impact the performance of *** this work,we investigate the influence of image degradation on three typical image classification CNNs and propose a Degradation Type Adaptive Image Classification Model(DTA-ICM)to improve the existing CNNs’classification accuracy on degraded *** proposed DTA-ICM comprises two key components:a Degradation Type Predictor(DTP)and a Degradation Type Specified Image Classifier(DTS-IC)set,which is trained on existing CNNs for specified types of *** DTP predicts the degradation type of a test image,and the corresponding DTS-IC is then selected to classify the *** evaluate the performance of both the proposed DTP and the DTA-ICMon the Caltech 101 *** experimental results demonstrate that the proposed DTP achieves an average accuracy of 99.70%.Moreover,the proposed DTA-ICM,based on AlexNet,VGG19,and ResNet152,exhibits an average accuracy improvement of 20.63%,18.22%,and 12.9%,respectively,compared with the original CNNs in classifying degraded *** suggests that the proposed DTA-ICM can effectively improve the classification performance of existing CNNs on degraded images,which has important practical implications.

关键词： Image recognition image degradation machine learning deep convolutional neural network