A New Approach For Weighted Hardy’s Operator In VELS

Akın, Lütfi; Düşünceli, Faruk

doi:10.2478/amns.2019.2.00040

Cited by 8 publications

(5 citation statements)

References 22 publications

(20 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The variation trend of each stock price predicted by deep learning Markov model is basically consistent with the actual situation. Moreover, the errors of deep learning Markov model in stock price prediction of Shanghai Pudong Development Bank (sh600000), Guizhou Moutai (sh600519)V and China Ping An Insurance (Sh601318) are 2.56%, 2.98% [32] and 3.56%, respectively, which indicates that the deep learning Markov model proposed in this study can be used in the prediction of stock prices and has a high prediction accuracy, which is consistent with the research results of Tingwei et al (2018) [33].…”

Section: Stock Price Prediction Based On Deep Learning Markov Modelsupporting

confidence: 89%

Cognitive Computational Model Using Machine Learning Algorithm in Artificial Intelligence Environment

Liu

Khadidos

Abdulrazzqa

2021

Applied Mathematics and Nonlinear Sciences

View full text Add to dashboard Cite

In order to accurately describe the risk dependence structure and correlation between financial variables, carry out scientific financial risk assessment, and provide the basis for accurate financial decision-making, first the basic theory of Copula function is established and the mixed Copula model is constructed. Then the hybrid Copula model is nested in a hidden Markov model (HMM), the risk dependences among banking, insurance, securities and trust industries are analysed, and the Copula–Garch model is constructed for empirical analysis of investment portfolio. Finally, the deep learning Markov model is adopted to predict the financial index. The results show that the mixed Copula model based on HMM is more effective than the single Copula and the mixed Copula models. The empirical structure shows that among the four major financial industries in China, the banking and insurance industries have strong interdependence and high probability of risk contagion. The investment failure rate under 95%, 97.5% and 99% confidence intervals calculated by Copula–Garch model are 4.53%, 2.17% and 1.08%, respectively. Moreover, the errors of deep learning Markov model in stock price prediction of Shanghai Pudong Development Bank (sh600000), Guizhou Moutai (sh600519) and China Ping An Insurance (sh601318) are 2.56%, 2.98% and 3.56% respectively, which indicates that the four major financial industries in China have strong interdependence and risk contagion, so that the macro or systemic risks may arise, and the deep-learning Markov model can be adopted to predict the stock prices.

show abstract

Section: Stock Price Prediction Based On Deep Learning Markov Modelsupporting

confidence: 89%

Cognitive Computational Model Using Machine Learning Algorithm in Artificial Intelligence Environment

Liu

Khadidos

Abdulrazzqa

2021

Applied Mathematics and Nonlinear Sciences

View full text Add to dashboard Cite

show abstract

“…ird, in terms of the weight assignment method based on information amount, the method is further improved, such as the method of topological entropy in [29,30].…”

Section: Discussionmentioning

confidence: 99%

An Optimal Credit Scoring Model Based on the Maximum Default Identification Ability for Chinese Small Business

Bai

Zhao

2022

Discrete Dynamics in Nature and Society

View full text Add to dashboard Cite

The reasonable credit scoring model must have strong default identification ability, which means the credit scoring can effectively distinguish between defaulting and nondefaulting customers. The premise to determine the credit score of small enterprises is to determine the weight of indicators. This paper studies 3,045 Chinese small business loans, and two novel weighting methods “Wilks’ Lambda method” and “AUC value method” are proposed, The greater the weight they meet, the greater the ability of default identification. The five weighting methods of “Wilks’ lambda method,” “AUC value method,” “G1 method,” “entropy method,” and “mean square variance method” are compared. An important contribution of the paper is to discover that Wilks’ Lambda method is the most effective method for small business.

show abstract

“…Moreover, they can be used to solve combinatorial optimization problems. With strong global search capabilities, genetic algorithms are used to find the global optimal solution without falling into a local optimal solution [23][24][25][26].…”

Section: Model Solving Based On Genetic Algorithmmentioning

confidence: 99%

Model and Solution of Complex Emergency Dispatch by Multiple Rescue Centers with Limited Capacity to Different Disaster Areas

Duan

Huang

et al. 2020

Symmetry

View full text Add to dashboard Cite

A disaster emergency consists of many unfavorable factors, such as different disaster areas, the limited capacity of the rescue centers, and complex rescue conditions. After taking into account the resources of the rescue centers, the ability of rescue teams, and the distance between the rescue centers and the disaster areas, this paper has established a complex model for multiple centers with limited capacity to dispatch teams for emergencies in different disaster areas. The model is solved by the genetic algorithm. Firstly, the paper takes the rescue task as the subunit to perform integer programming. Secondly, a rule is designed according to the symmetry of parents’ crossing. According to the rule, single parent crossover only allows two situations, (1) different rescue mission for the same rescue center and (2) different rescue centers under the same rescue mission. Finally, the performance of parent crossing and symmetric single parent crossing is compared. The results show that the two algorithms can converge to the optimal solution, but each of them has unique advantages in terms of convergence speed and stability. It is suggested that the strategy of the single-parent crossover should be used to deal with local emergency responses and that the two-parent crossover strategy is be used for more complicated global emergency responses.

show abstract

A New Approach For Weighted Hardy’s Operator In VELS

Cited by 8 publications

References 22 publications

Cognitive Computational Model Using Machine Learning Algorithm in Artificial Intelligence Environment

Cognitive Computational Model Using Machine Learning Algorithm in Artificial Intelligence Environment

An Optimal Credit Scoring Model Based on the Maximum Default Identification Ability for Chinese Small Business

Model and Solution of Complex Emergency Dispatch by Multiple Rescue Centers with Limited Capacity to Different Disaster Areas

Contact Info

Product

Resources

About