Multiattribute decision making (MADM) approach is a well-known decision-making process utilized in a variety of fields such as solid waste management, renewable energy resources, air quality assurance, hotel location decision, sustainable supplier selection, partner recognition, green supplier enterprises, game theory, construction development authority, and weapon group target estimation. The aggregation operators (AOs) are essential components of the decision-making process and have a great capability to deal with ambiguous and unpredictable information in the different fields of fuzzy environments. In this article, we expressed the theory concepts of single-valued neutrosophic (SVN) sets (SVNS) and also characterized their basic operations. The power aggregation tools are allowed to input arguments to support each other among different arguments. Recently, Aczel–Alisna aggregation tools conquered great attention from several research scholars. We also exposed some reliable operations of Aczel–Alsina aggregation models under the consideration of SVN information. We established a series of new approaches, including the “single-valued neutrosophic Aczel–Alsina power weighted average” (SVNAAPWA) operator and “single-valued neutrosophic Aczel–Alsina power weighted geometric” (SVNAAPWG) operators. To show the effectiveness and compatibility of derived approaches, some prominent characteristics are also established. We constructed a MADM technique to solve an application of engineering and construction materials under consideration of our derived methodologies. An experimental case study is also presented to determine a suitable optimal option from a group of options. To find the flexibility of our proposed work, we provided a comparative study that compares the results of existing AOs with our proposed work. A comprehensive overview is also presented here.
{"title":"Decision Support System for Single-Valued Neutrosophic Aczel–Alsina Aggregation Operators Based on Known Weights","authors":"Sajid Latif, Kifayat Ullah, Abrar Hussain, Amrullah Awsar","doi":"10.1155/2024/4362151","DOIUrl":"https://doi.org/10.1155/2024/4362151","url":null,"abstract":"Multiattribute decision making (MADM) approach is a well-known decision-making process utilized in a variety of fields such as solid waste management, renewable energy resources, air quality assurance, hotel location decision, sustainable supplier selection, partner recognition, green supplier enterprises, game theory, construction development authority, and weapon group target estimation. The aggregation operators (AOs) are essential components of the decision-making process and have a great capability to deal with ambiguous and unpredictable information in the different fields of fuzzy environments. In this article, we expressed the theory concepts of single-valued neutrosophic (SVN) sets (SVNS) and also characterized their basic operations. The power aggregation tools are allowed to input arguments to support each other among different arguments. Recently, Aczel–Alisna aggregation tools conquered great attention from several research scholars. We also exposed some reliable operations of Aczel–Alsina aggregation models under the consideration of SVN information. We established a series of new approaches, including the “single-valued neutrosophic Aczel–Alsina power weighted average” (SVNAAPWA) operator and “single-valued neutrosophic Aczel–Alsina power weighted geometric” (SVNAAPWG) operators. To show the effectiveness and compatibility of derived approaches, some prominent characteristics are also established. We constructed a MADM technique to solve an application of engineering and construction materials under consideration of our derived methodologies. An experimental case study is also presented to determine a suitable optimal option from a group of options. To find the flexibility of our proposed work, we provided a comparative study that compares the results of existing AOs with our proposed work. A comprehensive overview is also presented here.","PeriodicalId":55177,"journal":{"name":"Discrete Dynamics in Nature and Society","volume":"38 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140171758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Corporate social responsibility (CSR) is widely noticed as an essential tool for business operation and sustainable development. Meanwhile, the fiercely competitive external environment and unpredictable events prompt enterprises’ cooperation to prevent supply chain collapse. We investigate the cooperative strategy in a live-streaming supply chain (LSC) consisting of a dominant brand owner, a retailer, and a live streamer, where the brand owner considers CSR by considering the welfare of stakeholders. We construct one non-cooperative and three cooperative Stackelberg game models to explore the impact of CSR on cooperative strategy and LSC operations. The results show the following. (1) When the brand owner considers CSR, LSC members and systems are more profitable in the four models than when the brand owner does not consider CSR. (2) When the flow effect is small, the brand owner tends to cooperate with the retailer; otherwise, the brand owner prefers to cooperate with the live streamer. (3) The grand coalition C (the brand owner cooperates with the retailer and live streamer) is the consistent strategy for the LSC system, consumers, and society. These findings help enterprises recognize the importance of CSR and collaboration, thus further providing reference opinions on engaging in CSR and how to achieve collaboration.
{"title":"Impact of Corporate Social Responsibility on Operations of a Live-Streaming Supply Chain","authors":"Suqin Sun, Haodong Zheng, Tao Hang, Xuemei Zhang","doi":"10.1155/2024/2855251","DOIUrl":"https://doi.org/10.1155/2024/2855251","url":null,"abstract":"Corporate social responsibility (CSR) is widely noticed as an essential tool for business operation and sustainable development. Meanwhile, the fiercely competitive external environment and unpredictable events prompt enterprises’ cooperation to prevent supply chain collapse. We investigate the cooperative strategy in a live-streaming supply chain (LSC) consisting of a dominant brand owner, a retailer, and a live streamer, where the brand owner considers CSR by considering the welfare of stakeholders. We construct one non-cooperative and three cooperative Stackelberg game models to explore the impact of CSR on cooperative strategy and LSC operations. The results show the following. (1) When the brand owner considers CSR, LSC members and systems are more profitable in the four models than when the brand owner does not consider CSR. (2) When the flow effect is small, the brand owner tends to cooperate with the retailer; otherwise, the brand owner prefers to cooperate with the live streamer. (3) The grand coalition C (the brand owner cooperates with the retailer and live streamer) is the consistent strategy for the LSC system, consumers, and society. These findings help enterprises recognize the importance of CSR and collaboration, thus further providing reference opinions on engaging in CSR and how to achieve collaboration.","PeriodicalId":55177,"journal":{"name":"Discrete Dynamics in Nature and Society","volume":"46 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2024-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140171761","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this article, a subgrid-sparse-grad-div method for incompressible flow problem was proposed, which is a combination of the subgrid stabilization method and the recently proposed sparse-grad-div method. The method maintains the advantage of both methods: (i) It is robust for solving incompressible flow problem with dominance of the convection, especially when the viscosity is too small. (ii) It can keep mass conservation. Therefore, the method is very efficient for solving incompressible flow. Moreover, based on the Crank–Nicolson extrapolated scheme for temporal discretization, and mixed finite element in spatial discretization, we derive the unconditional stability and optimal convergence of the method. Finally, numerical experiments are proposed to validate the theoretical predictions and demonstrate the efficiency of the method on a test problem for incompressible flow.
{"title":"Numerical Analysis and Computation of a Subgrid-Sparse-Grad-Div Stabilization Method for Incompressible Flow Problems","authors":"Yun-Bo Yang, Bin-Chao Huang","doi":"10.1155/2024/5580918","DOIUrl":"https://doi.org/10.1155/2024/5580918","url":null,"abstract":"In this article, a subgrid-sparse-grad-div method for incompressible flow problem was proposed, which is a combination of the subgrid stabilization method and the recently proposed sparse-grad-div method. The method maintains the advantage of both methods: (i) It is robust for solving incompressible flow problem with dominance of the convection, especially when the viscosity is too small. (ii) It can keep mass conservation. Therefore, the method is very efficient for solving incompressible flow. Moreover, based on the Crank–Nicolson extrapolated scheme for temporal discretization, and mixed finite element in spatial discretization, we derive the unconditional stability and optimal convergence of the method. Finally, numerical experiments are proposed to validate the theoretical predictions and demonstrate the efficiency of the method on a test problem for incompressible flow.","PeriodicalId":55177,"journal":{"name":"Discrete Dynamics in Nature and Society","volume":"15 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2024-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140128687","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Background. Coal washing is a complicated process and difficult to control, which has many controlling parameters with strong coupling relationship. It is still a challenge to realize the self-perception, self-adjustment, and self-evaluation of coal washing machine, improve the quality of coal washing, ensure production safety, and reduce labor cost. Methods. Through the intelligent transformation of jig, this paper proposes an intelligent washing method with cooperated deep reinforcement learning and evolutionary computation. First, it designs a fault warning method based on statistical analysis, helping to recover the normal running state of jig with manual maintenance. Then, it constructs a regulation strategy generation method with deep reinforcement learning supported by the fusion of artificial experience and historical data. Last, for the lack of monitoring data caused by poor communication quality and environment, the regulation strategy prediction method with evolutionary computation and surrogate model is proposed. Results. In practice, this method shows accurate fault warning accuracy and rapid cleaned coal ash adjustment response ability. Conclusions. This shows that the method proposed in this paper is of great significance for intelligent washing and can better cope with the special situation when the washing equipment sensing data are missing.
{"title":"Deep Reinforcement Learning and Auto-Differential Evolution Co-Guided Coal Washing","authors":"Mingcheng Zuo","doi":"10.1155/2024/7843835","DOIUrl":"https://doi.org/10.1155/2024/7843835","url":null,"abstract":"<i>Background</i>. Coal washing is a complicated process and difficult to control, which has many controlling parameters with strong coupling relationship. It is still a challenge to realize the self-perception, self-adjustment, and self-evaluation of coal washing machine, improve the quality of coal washing, ensure production safety, and reduce labor cost. <i>Methods</i>. Through the intelligent transformation of jig, this paper proposes an intelligent washing method with cooperated deep reinforcement learning and evolutionary computation. First, it designs a fault warning method based on statistical analysis, helping to recover the normal running state of jig with manual maintenance. Then, it constructs a regulation strategy generation method with deep reinforcement learning supported by the fusion of artificial experience and historical data. Last, for the lack of monitoring data caused by poor communication quality and environment, the regulation strategy prediction method with evolutionary computation and surrogate model is proposed. <i>Results</i>. In practice, this method shows accurate fault warning accuracy and rapid cleaned coal ash adjustment response ability. <i>Conclusions</i>. This shows that the method proposed in this paper is of great significance for intelligent washing and can better cope with the special situation when the washing equipment sensing data are missing.","PeriodicalId":55177,"journal":{"name":"Discrete Dynamics in Nature and Society","volume":"37 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2024-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140106142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Motivating active participation in e-commerce logistics alliances to enhance delivery efficiency and customer satisfaction has long been a societal interest. Leveraging the quantum game theory, this paper develops a model for incentivizing collaboration within these alliances. This model enables theoretical and numerical analysis of members’ strategies and entanglement levels. The findings show that quantum strategies increase members’ profits, achieving Nash equilibriums and Pareto optimal outcomes, outperforming the classical game theory. In addition, the size of quantum entanglement emerges as a critical determinant influencing members’ active participation in collaborative distribution. Strengthening information sharing and aligning interests can enhance entanglement levels among members, making them more inclined to adopt strategies promoting active involvement in collaborative distribution. Moreover, members can adapt their strategies based on the initial entanglement in collaborative distribution, thereby incentivizing participation and reducing ethical risks. In conclusion, through numerical analysis, we present relevant strategies and recommendations for incentivizing collaborative distribution within e-commerce logistics alliances.
{"title":"Quantum Game-Based Study on the Incentive Mechanism for the Cooperative Distribution of E-Commerce Logistics Alliance","authors":"Liying Zhang, Fujian Chen","doi":"10.1155/2024/2590861","DOIUrl":"https://doi.org/10.1155/2024/2590861","url":null,"abstract":"Motivating active participation in e-commerce logistics alliances to enhance delivery efficiency and customer satisfaction has long been a societal interest. Leveraging the quantum game theory, this paper develops a model for incentivizing collaboration within these alliances. This model enables theoretical and numerical analysis of members’ strategies and entanglement levels. The findings show that quantum strategies increase members’ profits, achieving Nash equilibriums and Pareto optimal outcomes, outperforming the classical game theory. In addition, the size of quantum entanglement emerges as a critical determinant influencing members’ active participation in collaborative distribution. Strengthening information sharing and aligning interests can enhance entanglement levels among members, making them more inclined to adopt strategies promoting active involvement in collaborative distribution. Moreover, members can adapt their strategies based on the initial entanglement in collaborative distribution, thereby incentivizing participation and reducing ethical risks. In conclusion, through numerical analysis, we present relevant strategies and recommendations for incentivizing collaborative distribution within e-commerce logistics alliances.","PeriodicalId":55177,"journal":{"name":"Discrete Dynamics in Nature and Society","volume":"30 5","pages":""},"PeriodicalIF":1.4,"publicationDate":"2024-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140054055","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this article, we consider a class of nonlocal p(x)-Laplace equations with nonlinear boundary conditions. When the nonlinear boundary involves critical exponents, using the concentration compactness principle, mountain pass lemma, and fountain theorem, we can prove the existence and multiplicity of solutions.
{"title":"Multiple Solutions of a Nonlocal Problem with Nonlinear Boundary Conditions","authors":"Jie Liu, Qing Miao","doi":"10.1155/2024/3621001","DOIUrl":"https://doi.org/10.1155/2024/3621001","url":null,"abstract":"In this article, we consider a class of nonlocal <i>p</i>(<i>x</i>)-Laplace equations with nonlinear boundary conditions. When the nonlinear boundary involves critical exponents, using the concentration compactness principle, mountain pass lemma, and fountain theorem, we can prove the existence and multiplicity of solutions.","PeriodicalId":55177,"journal":{"name":"Discrete Dynamics in Nature and Society","volume":"55 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2024-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140018359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Shahzaib Ashraf, Muhammad Ahmed, Muhammad Naeem, Quashie Duodu
The key objective of this article is to introduce the innovative idea of a complex intuitionistic hesitant fuzzy set (CIHFS), which blends the intuitionistic hesitant fuzzy set with the complex fuzzy set to address the uncertain information in real-life complex problems. In CIHFS, the range of the membership functions is extended from the subset of the real number to the unit disc under the hesitant environment. To determine how well the CIHFSs can be distinguished from one another, we first propose generalized distance measures and weighted generalized distance measures based on the Hamming, Euclidean, and Hausdorff metrics. Some interesting properties and their relationships are thoroughly discussed. Furthermore, a decision-making framework for selecting the optimal option from the feasible set has been proposed, which is grounded in these distance metrics. For the purpose of proving the method’s efficacy, we included examples from pattern recognition and medical diagnostics.
{"title":"Novel Complex Intuitionistic Hesitant Fuzzy Distance Measures for Solving Decision-Support Problems","authors":"Shahzaib Ashraf, Muhammad Ahmed, Muhammad Naeem, Quashie Duodu","doi":"10.1155/2024/7498053","DOIUrl":"https://doi.org/10.1155/2024/7498053","url":null,"abstract":"The key objective of this article is to introduce the innovative idea of a complex intuitionistic hesitant fuzzy set (CIHFS), which blends the intuitionistic hesitant fuzzy set with the complex fuzzy set to address the uncertain information in real-life complex problems. In CIHFS, the range of the membership functions is extended from the subset of the real number to the unit disc under the hesitant environment. To determine how well the CIHFSs can be distinguished from one another, we first propose generalized distance measures and weighted generalized distance measures based on the Hamming, Euclidean, and Hausdorff metrics. Some interesting properties and their relationships are thoroughly discussed. Furthermore, a decision-making framework for selecting the optimal option from the feasible set has been proposed, which is grounded in these distance metrics. For the purpose of proving the method’s efficacy, we included examples from pattern recognition and medical diagnostics.","PeriodicalId":55177,"journal":{"name":"Discrete Dynamics in Nature and Society","volume":"7 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2024-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139921052","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Uncertain events such as earthquakes, epidemics, and wars have increased the risk of supply chain disruption. Due to the needs of carbon reduction policies and environmental protection, a large number of enterprises have started to produce both traditional and green products. Studying the issue of supply chain disruption for such enterprises has significant practical significance. We have developed a system dynamics model for a substitutable dual product supply chain with two levels of supply sources. Through simulation analysis, we found that (1) supply chain disruption can cause fluctuations in the manufacturer’s inventory, and disruptions from second tier suppliers have a higher impact on the manufacturer’s inventory than that from primary suppliers. In addition, the disruption of traditional products will cause consumers to flow to the green product market, resulting in a sudden increase in order for green products and components in a short period of time, causing a delayed impact on the inventory of suppliers and manufacturers of green products. (2) The disruption of upstream suppliers in traditional products causes the highest profit losses for all traditional product suppliers, while the disruption of downstream suppliers in green products causes the highest profit losses for the manufacturer and all green product suppliers. (3) From the perspective of the service level, compared to other components, the disruption of critical components in traditional products poses the highest risk of out of stock in the supply chain, while the risk of out-of-stock in the intermediate component of green product is the smallest. (4) Common sense may suggest that the more the suppliers disrupt, the higher the damage of the supply chain. However, due to the ripple effect, this article finds that from the perspectives of profit, inventory, and service level, multisupplier disruption is not necessarily inferior to single supplier disruption.
{"title":"Disruption Risk Analysis of Substitutable Dual Product Supply Chain: A System Dynamics Framework","authors":"Jing Ke, Weiqiang Jia, Ye Zhou, Xin Wang","doi":"10.1155/2024/9920879","DOIUrl":"https://doi.org/10.1155/2024/9920879","url":null,"abstract":"Uncertain events such as earthquakes, epidemics, and wars have increased the risk of supply chain disruption. Due to the needs of carbon reduction policies and environmental protection, a large number of enterprises have started to produce both traditional and green products. Studying the issue of supply chain disruption for such enterprises has significant practical significance. We have developed a system dynamics model for a substitutable dual product supply chain with two levels of supply sources. Through simulation analysis, we found that (1) supply chain disruption can cause fluctuations in the manufacturer’s inventory, and disruptions from second tier suppliers have a higher impact on the manufacturer’s inventory than that from primary suppliers. In addition, the disruption of traditional products will cause consumers to flow to the green product market, resulting in a sudden increase in order for green products and components in a short period of time, causing a delayed impact on the inventory of suppliers and manufacturers of green products. (2) The disruption of upstream suppliers in traditional products causes the highest profit losses for all traditional product suppliers, while the disruption of downstream suppliers in green products causes the highest profit losses for the manufacturer and all green product suppliers. (3) From the perspective of the service level, compared to other components, the disruption of critical components in traditional products poses the highest risk of out of stock in the supply chain, while the risk of out-of-stock in the intermediate component of green product is the smallest. (4) Common sense may suggest that the more the suppliers disrupt, the higher the damage of the supply chain. However, due to the ripple effect, this article finds that from the perspectives of profit, inventory, and service level, multisupplier disruption is not necessarily inferior to single supplier disruption.","PeriodicalId":55177,"journal":{"name":"Discrete Dynamics in Nature and Society","volume":"14 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2024-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139765062","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Class noise is a common issue that affects the performance of classification techniques on real-world data sets. Class noise appears when a class variable in data sets has incorrect class labels. In the case of noisy data, the robustness of classification techniques against noise could be more important than the performance results on noise-free data sets. The decision tree method is one of the most popular techniques for classification tasks. The C4.5, CART, and random forest (RF) algorithms are considered to be three of the most used algorithms in decision trees. The aim of this paper is to reach conclusions on which decision tree algorithm is better to use for building decision trees in terms of its performance and robustness against class noise. In order to achieve this aim, we study and compare the performance of the models when applied to class variables with noise. The results obtained indicate that the RF algorithm is more robust to data sets with noisy class variable than other algorithms.
{"title":"Classification Performance Analysis of Decision Tree-Based Algorithms with Noisy Class Variable","authors":"Abdulmajeed Atiah Alharbi","doi":"10.1155/2024/6671395","DOIUrl":"https://doi.org/10.1155/2024/6671395","url":null,"abstract":"Class noise is a common issue that affects the performance of classification techniques on real-world data sets. Class noise appears when a class variable in data sets has incorrect class labels. In the case of noisy data, the robustness of classification techniques against noise could be more important than the performance results on noise-free data sets. The decision tree method is one of the most popular techniques for classification tasks. The C4.5, CART, and random forest (RF) algorithms are considered to be three of the most used algorithms in decision trees. The aim of this paper is to reach conclusions on which decision tree algorithm is better to use for building decision trees in terms of its performance and robustness against class noise. In order to achieve this aim, we study and compare the performance of the models when applied to class variables with noise. The results obtained indicate that the RF algorithm is more robust to data sets with noisy class variable than other algorithms.","PeriodicalId":55177,"journal":{"name":"Discrete Dynamics in Nature and Society","volume":"60 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139656695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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