Functions are a means to link or transport from a world to another world may be similarly or completely different from the other world. In this paper we addressed the issue of rough functions and the possibility of tr...Functions are a means to link or transport from a world to another world may be similarly or completely different from the other world. In this paper we addressed the issue of rough functions and the possibility of transfer it from the real line to the topological abstract view that can be applied to intelligent information systems. The rough function approach has not been studied much specially from a topological point of view. Here we developed a new type of topological generalizations of rough functions with reference to how it is used in medical applications. Considering that the function is in the original a relation can be based on a review of all circular functions from the perspective of relations. Accordingly, the dream that the generalizations of rough functions are transferred to all papers prior to a comprehensive computer application.展开更多
Deep learning attentionmechanisms have achieved remarkable progress in computer vision,but still face limitations when handling images with ambiguous boundaries and uncertain feature representations.Conventional atten...Deep learning attentionmechanisms have achieved remarkable progress in computer vision,but still face limitations when handling images with ambiguous boundaries and uncertain feature representations.Conventional attention modules such as SE-Net,CBAM,ECA-Net,and CA adopt a deterministic paradigm,assigning fixed scalar weights to features without modeling ambiguity or confidence.To overcome these limitations,this paper proposes the Fuzzy Attention Network Layer(FANL),which integrates intuitionistic fuzzy set theory with convolutional neural networks to explicitly represent feature uncertainty through membership(μ),non-membership(ν),and hesitation(π)degrees.FANLconsists of four coremodules:(1)feature dimensionality reduction via global pooling,(2)fuzzymodeling using learnable clustering centers,(3)adaptive attention generation through weighted fusion of fuzzy components,and(4)feature refinement through residual connections.A cross-layer guidance mechanism is further introduced to enhance hierarchical feature propagation,allowing high-level semantic features to incorporate fine-grained texture information from shallow layers.Comprehensive experiments on three benchmark datasets—PathMNIST-30000,full PathMNIST,and Blood MNIST—demonstrate the effectiveness and generalizability of FANL.The model achieves 84.41±0.56%accuracy and a 1.69%improvement over the baseline CNN while maintaining lightweight computational complexity.Ablation studies show that removing any component causes a 1.7%–2.0%performance drop,validating the synergistic contribution of each module.Furthermore,FANL provides superior uncertainty calibration(ECE=0.0452)and interpretable selective prediction under uncertainty.Overall,FANL presents an efficient and uncertaintyaware attention framework that improves both accuracy and reliability,offering a promising direction for robust visual recognition under ambiguous or noisy conditions.展开更多
A discrete subset S of a topological gyrogroup G with the identity 0 is said to be a suitable set for G if it generates a dense subgyrogroup of G and S∪{0}is closed in G.In this paper,it is proved that each countable...A discrete subset S of a topological gyrogroup G with the identity 0 is said to be a suitable set for G if it generates a dense subgyrogroup of G and S∪{0}is closed in G.In this paper,it is proved that each countable Hausdorff topological gyrogroup has a suitable set;moreover,it is shown that each separable metrizable strongly topological gyrogroup has a suitable set.展开更多
Due to the numerous variables to take into account as well as the inherent ambiguity and uncertainty,evaluating educational institutions can be difficult.The concept of a possibility Pythagorean fuzzy hypersoft set(pP...Due to the numerous variables to take into account as well as the inherent ambiguity and uncertainty,evaluating educational institutions can be difficult.The concept of a possibility Pythagorean fuzzy hypersoft set(pPyFHSS)is more flexible in this regard than other theoretical fuzzy set-like models,even though some attempts have been made in the literature to address such uncertainties.This study investigates the elementary notions of pPyFHSS including its set-theoretic operations union,intersection,complement,OR-and AND-operations.Some results related to these operations are also modified for pPyFHSS.Additionally,the similarity measures between pPyFHSSs are formulated with the assistance of numerical examples and results.Lastly,an intelligent decision-assisted mechanism is developed with the proposal of a robust algorithm based on similarity measures for solving multi-attribute decision-making(MADM)problems.A case study that helps the decision-makers assess the best educational institution is discussed to validate the suggested system.The algorithmic results are compared with the most pertinent model to evaluate the adaptability of pPyFHSS,as it generalizes the classical possibility fuzzy set-like theoretical models.Similarly,while considering significant evaluating factors,the flexibility of pPyFHSS is observed through structural comparison.展开更多
Radio Frequency Fingerprint Identification(RFFI)technology provides a means of identifying spurious signals.This technology has been widely used in solving Automatic Dependent Surveillance–Broadcast(ADS-B)signal spoo...Radio Frequency Fingerprint Identification(RFFI)technology provides a means of identifying spurious signals.This technology has been widely used in solving Automatic Dependent Surveillance–Broadcast(ADS-B)signal spoofing problems.However,the effects of circuit changes over time often lead to a decline in identification accuracy within open-time set.This paper proposes an ADS-B transmitter identification method to solve the degradation of identification accuracy.First,a real-time data processing system is established to receive and store ADS-B signals to meet the conditions for open-time set.The system possesses the following functionalities:data collection,data parsing,feature extraction,and identity recognition.Subsequently,a two-dimensional TimeFrequency Feature Diagram(TFFD)is proposed as a signal pre-processing method.The TFFD is constructed from the received ADS-B signal and the reconstructed signal for input to the recognition model.Finally,incorporating a frequency offset layer into the Swin Transformer architecture,a novel recognition network framework is proposed.This integration can enhance the network recognition accuracy and robustness by tailoring to the specific characteristics of ADSB signals.Experimental results indicate that the proposed recognition architecture achieves recognition accuracy of 95.86%in closed-time set and 84.33%in open-time set,surpassing other algorithms.展开更多
In this paper,we study the Bowen entropy of stable sets in positive entropy G-system of amenable group actions.The lower bound of the Bowen entropy of these sets are estimated.
This paper introduces fuzzy N-bipolar soft(FN-BS)sets,a novel mathematical framework designed to enhance multi-criteria decision-making(MCDM)processes under uncertainty.The study addresses a significant limitation in ...This paper introduces fuzzy N-bipolar soft(FN-BS)sets,a novel mathematical framework designed to enhance multi-criteria decision-making(MCDM)processes under uncertainty.The study addresses a significant limitation in existing models by unifying fuzzy logic,the consideration of bipolarity,and the ability to evaluate attributes on a multinary scale.The specific contributions of the FN-BS framework include:(1)a formal definition and settheoretic foundation,(2)the development of two innovative algorithms for solving decision-making(DM)problems,and(3)a comparative analysis demonstrating its superiority over established models.The proposed framework is applied to a real-world case study on selecting vaccination programs across multiple countries,showcasing consistent DM outcomes and exceptional adaptability to complex and uncertain scenarios.These results position FN-BS sets as a versatile and powerful tool for addressing dynamic DM challenges.展开更多
Urban transportation planning involves evaluating multiple conflicting criteria such as accessibility,cost-effectiveness,and environmental impact,often under uncertainty and incomplete information.These complex decisi...Urban transportation planning involves evaluating multiple conflicting criteria such as accessibility,cost-effectiveness,and environmental impact,often under uncertainty and incomplete information.These complex decisions require input from various stakeholders,including planners,policymakers,engineers,and community representatives,whose opinions may differ or contradict.Traditional decision-making approaches struggle to effectively handle such bipolar and multivalued expert evaluations.To address these challenges,we propose a novel decisionmaking framework based on Pythagorean fuzzy N-bipolar soft expert sets.This model allows experts to express both positive and negative opinions on a multinary scale,capturing nuanced judgments with higher accuracy.It introduces algebraic operations and a structured aggregation algorithm to systematically integrate and resolve conflicting expert inputs.Applied to a real-world case study,the framework evaluated five urban transport strategies based on key criteria,producing final scores as follows:improving public transit(−0.70),optimizing traffic signal timing(1.86),enhancing pedestrian infrastructure(3.10),expanding bike lanes(0.59),and implementing congestion pricing(0.77).The results clearly identify enhancing pedestrian infrastructure as the most suitable option,having obtained the highest final score of 3.10.Comparative analysis demonstrates the framework’s superior capability in modeling expert consensus,managing uncertainty,and supporting transparent multi-criteria group decision-making.展开更多
Ensuring a sustainable and eco-friendly environment is essential for promoting a healthy and balanced social life.However,decision-making in such contexts often involves handling vague,imprecise,and uncertain informat...Ensuring a sustainable and eco-friendly environment is essential for promoting a healthy and balanced social life.However,decision-making in such contexts often involves handling vague,imprecise,and uncertain information.To address this challenge,this study presents a novel multi-criteria decision-making(MCDM)approach based on picture fuzzy hypersoft sets(PFHSS),integrating the flexibility of Schweizer-Sklar triangular norm-based aggregation operators.The proposed aggregation mechanisms—weighted average and weighted geometric operators—are formulated using newly defined operational laws under the PFHSS framework and are proven to satisfy essential mathematical properties,such as idempotency,monotonicity,and boundedness.The decision-making model system-atically incorporates both benefit and cost-type criteria,enabling more nuanced evaluations in complex social or environmental decision problems.To enhance interpretability and practical relevance,the study conducts a sensitivity analysis on the Schweizer-Sklar parameter(Δ).The results show that varyingΔaffects the strictness of aggregation,thereby influencing the ranking stability of alternatives.A comparative analysis with existing fuzzy and hypersoft-based MCDM methods confirms the robustness,expressiveness,and adaptability of the proposed approach.Notably,the use of picture fuzzy sets allows for the inclusion of positive,neutral,and negative memberships,offering a richer representation of expert opinions compared to traditional models.A case study focused on green technology adoption for environmental sustainability illustrates the real-world applicability of the proposed method.The analysis confirms that the approach yields consistent and interpretable results,even under varying degrees of decision uncertainty.Overall,this work contributes an efficient and flexible MCDM tool that can support decision-makers in formulating policies aligned with sustainable and socially responsible outcomes.展开更多
Nonlocal set of orthogonal product states(OPSs)can improve the confidentiality of information when it is used to design quantum cryptographic protocols.It is a difficult question how to construct a nonlocal set of OPS...Nonlocal set of orthogonal product states(OPSs)can improve the confidentiality of information when it is used to design quantum cryptographic protocols.It is a difficult question how to construct a nonlocal set of OPSs on general multipartite and high dimensional quantum systems.Different from the previous works,we first present a novel method for constructing a nonlocal product set with 3d-2 members on C^(d)■C^(d)■C^(d)quantum system for d≥3.Then,we extend this construction method to C^(d_(1))■C^(d_(2))■C^(d_(3))quantum system and■_(i=1)^(n)C^(di)quantum system respectively,where 3≤d_(1)≤d_(2)≤d_(3)≤…≤dC_(d_(i))and n≥3.The nonlocal set of OPSs constructed by our method contains fewer elements than those constructed by the existing methods,except for one special case.More importantly,the set of states constructed by our method has a completely different structure from those constructed by the existing methods since our nonlocal set does not contain a“stopper”state.Our result is helpful to further understand the different structures of nonlocal sets on multipartite systems.展开更多
Local strong seismic activity shows the potential to closely follow a renewal process,which is inconsistent with the overall seismic activity that aligns with the Poisson process.Given that existing methods for synthe...Local strong seismic activity shows the potential to closely follow a renewal process,which is inconsistent with the overall seismic activity that aligns with the Poisson process.Given that existing methods for synthesizing stochastic seismic event sets cannot control local seismic activity,a method based on Monte Carlo simulations has been developed for synthesizing random seismic event sets where local strong earthquakes satisfy the renewal process.This method can synthesize seismic activities in a statistical area where the overall activity conforms to the Poisson process and the major seismic activities in local potential sources or faults follow the renewal process.This paper presents long-and short-scale approaches.The long-scale earthquake catalogs are suitable for reflecting the sequential characteristics of seismic activities.Meanwhile,the short-scale catalogs focus on the impacts of specific earthquake events within a group for a detailed understanding of hazards under certain conditions,making them suitable for studies on specific earthquake sequences and geological areas or situations requiring high temporal resolution.In the applications of shortscale sequences,we find that the equivalent occurrence rate method may overestimate the seismic hazard.This synthesis method for earthquake catalogs can simulate realistic seismic activities,thereby enhancing the accuracy of hazard analysis results and is suitable for seismic hazard analysis and earthquake insurance rate setting.展开更多
Despite being ubiquitous in oceans and important in marine biogeochemical cycles,planktonic archaea in the Southern Ocean(SO)remain poorly characterized.Although high-throughput sequencing(HTS)approaches based on 16S ...Despite being ubiquitous in oceans and important in marine biogeochemical cycles,planktonic archaea in the Southern Ocean(SO)remain poorly characterized.Although high-throughput sequencing(HTS)approaches based on 16S ribosomal RNA(rRNA)genes have been used widely to study the diversity and composition of microbial community in natural environments,primer-set selection is critical because of amplicon-sequencing bias during metabarcoding.Here,using surface-seawater samples collected from the area between the South Shetland and South Orkney Islands,Antarctica,we compared primer sets Arch349F/Arch806R,515F-Y/926R,and 524F/Arch958R,which target different 16S rRNA gene hypervariable regions to identify the best one for studying planktonic archaeal communities.With much lower number of bacteria-related sequences,primer set 524F/Arch958R showed higher values of archaeal operational taxonomic units(OTUs)as well as alpha-diversity indices,indicating that this primer set was more specific for detecting archaeal species and could be helpful to obtain more comprehensive information on the archaeal community compositions compared to other two primer sets.Compared with primer set Arch349F/Arch806R revealing four phyla(Halobacteriota,Methanobacteriota,Thermoplasmatota,and Thermoproteota)detected in seawater,additional archaeal phyla were observed by 515F-Y/926R(Asgardarchaeota and Nanoarchaeota)and 524F/Arch958R(Micrarchaeota).In spite of the differences in archaeal community compositions observed among the three investigated primer sets,ammonia-oxidizing(e.g.,Nitrososphaeria)and methane-producing(e.g.,Methanobacteria,Methanomicrobia,and Methanosarcinia)archaea were the main groups detected in the surface seawater,indicating the ecological role of planktonic archaea in carbon and nitrogen cycling in the upper waters of the SO.These results underscore the importance of primer-set selection when studying archaeal community diversity and composition in the Antarctic SO.展开更多
In this paper,the transferable belief model established on power sets is extended to the permutation event space(PES)and is referred to as the layer-2 transferable belief model.Our goal is to provide a comprehensive a...In this paper,the transferable belief model established on power sets is extended to the permutation event space(PES)and is referred to as the layer-2 transferable belief model.Our goal is to provide a comprehensive approach for handling and modeling uncertainty,capable of representing both quantitative and qualitative information.First,the motivation for proposing the layer-2 transferable belief model and its information processing principles are explored from the perspective of weak propensity.Then,based on these principles,the corresponding information processing methods for the credal and pignistic levels are developed.Finally,the advantages of this model are validated through a classifier that leverages attribute fusion to enhance performance and decision-making accuracy.展开更多
This study introduces a novel distance measure(DM)for(p,q,r)-spherical fuzzy sets((p,q,to improve decision-making in complex and uncertain environments.Many existing distance measures eitherr)-SFSs)fail to satisfy ess...This study introduces a novel distance measure(DM)for(p,q,r)-spherical fuzzy sets((p,q,to improve decision-making in complex and uncertain environments.Many existing distance measures eitherr)-SFSs)fail to satisfy essential axiomatic properties or produce unintuitive outcomes.To address these limitations,we propose a new three-dimensional divergence-based DM that ensures mathematical consistency,enhances the discrimination of information,and adheres to the axiomatic framework of distance theory.Building on this foundation,we construct a multi-criteria decision-making(MCDM)model that utilizes the proposed DM to evaluate and rank alternatives effectively.The applicability and robustness of the model are validated through a practical case study,demonstrating that it leads to more rational,consistent,and reliable decision outcomes compared to existing approaches.展开更多
Submodular optimization is primarily applied in multi-agent systems for tasks such as resource allocation,task assignment,collaborative decision-making,and optimization problems.Maximization of optimizing submodular s...Submodular optimization is primarily applied in multi-agent systems for tasks such as resource allocation,task assignment,collaborative decision-making,and optimization problems.Maximization of optimizing submodular set functions attracts much attention since the 1970s.A large body of work has been done using approximation algorithms.When the dimension of the independent variable of the set function changes from one tok,it is called ak-submodular set function.Thek-submodular set function,a generalization of the classical submodular set function,arises in diverse fields with varied applications.In many practical scenarios,quantifying the degree of closeness to submodularity becomes essential,leading to concepts such as approximately submodular set functions and the diminishing-return(DR) ratio.This paper investigates ak-dimensional set function under matroid constraints,which may lack full submodularity.Instead,we focus on an approximately non-ksubmodular set function characterized by its DR ratio.Employing a greedy algorithmic approach,we derive an approximation guarantee for this problem.Notably,when the DR ratio is set to one,our results align with existing findings in the literature.Experimental results demonstrate the superiority of our algorithm over the baselines.展开更多
The sustainability of the Internet of Things(IoT)involves various issues,such as poor connectivity,scalability problems,interoperability issues,and energy inefficiency.Although the Sixth Generation of mobile networks(...The sustainability of the Internet of Things(IoT)involves various issues,such as poor connectivity,scalability problems,interoperability issues,and energy inefficiency.Although the Sixth Generation of mobile networks(6G)allows for Ultra-Reliable Low-Latency Communication(URLLC),enhanced Mobile Broadband(eMBB),and massive Machine-Type Communications(mMTC)services,it faces deployment challenges such as the short range of sub-THz and THz frequency bands,low capability to penetrate obstacles,and very high path loss.This paper presents a network architecture to enhance the connectivity of wireless IoT mesh networks that employ both 6G and Wi-Fi technologies.In this architecture,local communications are carried through the mesh network,which uses a virtual backbone to relay packets to local nodes,while remote communications are carried through the 6G network.The virtual backbone is created using a heuristic distributed ConnectedDominating Set(CDS)algorithm.In this algorithm,each node uses information collected from its one-and two-hop neighbors to determine its role and find the set of expansion nodes that are used to select the next CDS nodes.The proposed algorithm has O(n)message and O(K)time complexities,where n is the number of nodes in the network,and K is the depth of the cluster.The study proved that the approximation ratio of the algorithmhas an upper bound of 2.06748(3.4306MCDS+4.8185).Performance evaluations compared the size of the CDS against the theoretical limit and recent CDS clustering algorithms.Results indicate that the proposed algorithm has the smallest average slope for the size of the CDS as the number of nodes increases.展开更多
文摘Functions are a means to link or transport from a world to another world may be similarly or completely different from the other world. In this paper we addressed the issue of rough functions and the possibility of transfer it from the real line to the topological abstract view that can be applied to intelligent information systems. The rough function approach has not been studied much specially from a topological point of view. Here we developed a new type of topological generalizations of rough functions with reference to how it is used in medical applications. Considering that the function is in the original a relation can be based on a review of all circular functions from the perspective of relations. Accordingly, the dream that the generalizations of rough functions are transferred to all papers prior to a comprehensive computer application.
文摘Deep learning attentionmechanisms have achieved remarkable progress in computer vision,but still face limitations when handling images with ambiguous boundaries and uncertain feature representations.Conventional attention modules such as SE-Net,CBAM,ECA-Net,and CA adopt a deterministic paradigm,assigning fixed scalar weights to features without modeling ambiguity or confidence.To overcome these limitations,this paper proposes the Fuzzy Attention Network Layer(FANL),which integrates intuitionistic fuzzy set theory with convolutional neural networks to explicitly represent feature uncertainty through membership(μ),non-membership(ν),and hesitation(π)degrees.FANLconsists of four coremodules:(1)feature dimensionality reduction via global pooling,(2)fuzzymodeling using learnable clustering centers,(3)adaptive attention generation through weighted fusion of fuzzy components,and(4)feature refinement through residual connections.A cross-layer guidance mechanism is further introduced to enhance hierarchical feature propagation,allowing high-level semantic features to incorporate fine-grained texture information from shallow layers.Comprehensive experiments on three benchmark datasets—PathMNIST-30000,full PathMNIST,and Blood MNIST—demonstrate the effectiveness and generalizability of FANL.The model achieves 84.41±0.56%accuracy and a 1.69%improvement over the baseline CNN while maintaining lightweight computational complexity.Ablation studies show that removing any component causes a 1.7%–2.0%performance drop,validating the synergistic contribution of each module.Furthermore,FANL provides superior uncertainty calibration(ECE=0.0452)and interpretable selective prediction under uncertainty.Overall,FANL presents an efficient and uncertaintyaware attention framework that improves both accuracy and reliability,offering a promising direction for robust visual recognition under ambiguous or noisy conditions.
基金supported by Fujian Provincial Natural Science Foundation of China(2024J02022)the NSFC(11571158)+1 种基金supported by the NSFC(12071199)supported by the Young and middle-aged project in Fujian Province(JAT190397)。
文摘A discrete subset S of a topological gyrogroup G with the identity 0 is said to be a suitable set for G if it generates a dense subgyrogroup of G and S∪{0}is closed in G.In this paper,it is proved that each countable Hausdorff topological gyrogroup has a suitable set;moreover,it is shown that each separable metrizable strongly topological gyrogroup has a suitable set.
基金supported by the Deanship of Graduate Studies and Scientific Research at Qassim University(QU-APC-2024-9/1).
文摘Due to the numerous variables to take into account as well as the inherent ambiguity and uncertainty,evaluating educational institutions can be difficult.The concept of a possibility Pythagorean fuzzy hypersoft set(pPyFHSS)is more flexible in this regard than other theoretical fuzzy set-like models,even though some attempts have been made in the literature to address such uncertainties.This study investigates the elementary notions of pPyFHSS including its set-theoretic operations union,intersection,complement,OR-and AND-operations.Some results related to these operations are also modified for pPyFHSS.Additionally,the similarity measures between pPyFHSSs are formulated with the assistance of numerical examples and results.Lastly,an intelligent decision-assisted mechanism is developed with the proposal of a robust algorithm based on similarity measures for solving multi-attribute decision-making(MADM)problems.A case study that helps the decision-makers assess the best educational institution is discussed to validate the suggested system.The algorithmic results are compared with the most pertinent model to evaluate the adaptability of pPyFHSS,as it generalizes the classical possibility fuzzy set-like theoretical models.Similarly,while considering significant evaluating factors,the flexibility of pPyFHSS is observed through structural comparison.
基金supported by the National Key Research and Development Program of China(No.2022YFB4300902)。
文摘Radio Frequency Fingerprint Identification(RFFI)technology provides a means of identifying spurious signals.This technology has been widely used in solving Automatic Dependent Surveillance–Broadcast(ADS-B)signal spoofing problems.However,the effects of circuit changes over time often lead to a decline in identification accuracy within open-time set.This paper proposes an ADS-B transmitter identification method to solve the degradation of identification accuracy.First,a real-time data processing system is established to receive and store ADS-B signals to meet the conditions for open-time set.The system possesses the following functionalities:data collection,data parsing,feature extraction,and identity recognition.Subsequently,a two-dimensional TimeFrequency Feature Diagram(TFFD)is proposed as a signal pre-processing method.The TFFD is constructed from the received ADS-B signal and the reconstructed signal for input to the recognition model.Finally,incorporating a frequency offset layer into the Swin Transformer architecture,a novel recognition network framework is proposed.This integration can enhance the network recognition accuracy and robustness by tailoring to the specific characteristics of ADSB signals.Experimental results indicate that the proposed recognition architecture achieves recognition accuracy of 95.86%in closed-time set and 84.33%in open-time set,surpassing other algorithms.
基金Supported by NSFC(No.11861010),also supported by NSFC(No.12171175),also supported by NSFC(No.12261006)NSF of Guangxi Province(No.2018GXNSFFA281008)Project of Guangxi First Class Disciplines of Statistics(No.GJKY-2022-01)。
文摘In this paper,we study the Bowen entropy of stable sets in positive entropy G-system of amenable group actions.The lower bound of the Bowen entropy of these sets are estimated.
文摘This paper introduces fuzzy N-bipolar soft(FN-BS)sets,a novel mathematical framework designed to enhance multi-criteria decision-making(MCDM)processes under uncertainty.The study addresses a significant limitation in existing models by unifying fuzzy logic,the consideration of bipolarity,and the ability to evaluate attributes on a multinary scale.The specific contributions of the FN-BS framework include:(1)a formal definition and settheoretic foundation,(2)the development of two innovative algorithms for solving decision-making(DM)problems,and(3)a comparative analysis demonstrating its superiority over established models.The proposed framework is applied to a real-world case study on selecting vaccination programs across multiple countries,showcasing consistent DM outcomes and exceptional adaptability to complex and uncertain scenarios.These results position FN-BS sets as a versatile and powerful tool for addressing dynamic DM challenges.
文摘Urban transportation planning involves evaluating multiple conflicting criteria such as accessibility,cost-effectiveness,and environmental impact,often under uncertainty and incomplete information.These complex decisions require input from various stakeholders,including planners,policymakers,engineers,and community representatives,whose opinions may differ or contradict.Traditional decision-making approaches struggle to effectively handle such bipolar and multivalued expert evaluations.To address these challenges,we propose a novel decisionmaking framework based on Pythagorean fuzzy N-bipolar soft expert sets.This model allows experts to express both positive and negative opinions on a multinary scale,capturing nuanced judgments with higher accuracy.It introduces algebraic operations and a structured aggregation algorithm to systematically integrate and resolve conflicting expert inputs.Applied to a real-world case study,the framework evaluated five urban transport strategies based on key criteria,producing final scores as follows:improving public transit(−0.70),optimizing traffic signal timing(1.86),enhancing pedestrian infrastructure(3.10),expanding bike lanes(0.59),and implementing congestion pricing(0.77).The results clearly identify enhancing pedestrian infrastructure as the most suitable option,having obtained the highest final score of 3.10.Comparative analysis demonstrates the framework’s superior capability in modeling expert consensus,managing uncertainty,and supporting transparent multi-criteria group decision-making.
基金supported by the National Natural Science Foundation of China(No.62172095).
文摘Ensuring a sustainable and eco-friendly environment is essential for promoting a healthy and balanced social life.However,decision-making in such contexts often involves handling vague,imprecise,and uncertain information.To address this challenge,this study presents a novel multi-criteria decision-making(MCDM)approach based on picture fuzzy hypersoft sets(PFHSS),integrating the flexibility of Schweizer-Sklar triangular norm-based aggregation operators.The proposed aggregation mechanisms—weighted average and weighted geometric operators—are formulated using newly defined operational laws under the PFHSS framework and are proven to satisfy essential mathematical properties,such as idempotency,monotonicity,and boundedness.The decision-making model system-atically incorporates both benefit and cost-type criteria,enabling more nuanced evaluations in complex social or environmental decision problems.To enhance interpretability and practical relevance,the study conducts a sensitivity analysis on the Schweizer-Sklar parameter(Δ).The results show that varyingΔaffects the strictness of aggregation,thereby influencing the ranking stability of alternatives.A comparative analysis with existing fuzzy and hypersoft-based MCDM methods confirms the robustness,expressiveness,and adaptability of the proposed approach.Notably,the use of picture fuzzy sets allows for the inclusion of positive,neutral,and negative memberships,offering a richer representation of expert opinions compared to traditional models.A case study focused on green technology adoption for environmental sustainability illustrates the real-world applicability of the proposed method.The analysis confirms that the approach yields consistent and interpretable results,even under varying degrees of decision uncertainty.Overall,this work contributes an efficient and flexible MCDM tool that can support decision-makers in formulating policies aligned with sustainable and socially responsible outcomes.
基金supported by the National Natural Science Foundation of China(Grant No.62171264)the Natural Science Foundation of Shandong Province of China(Grant No.ZR2023MF080)the Natural Science Foundation of Beijing(Grant No.4252014).
文摘Nonlocal set of orthogonal product states(OPSs)can improve the confidentiality of information when it is used to design quantum cryptographic protocols.It is a difficult question how to construct a nonlocal set of OPSs on general multipartite and high dimensional quantum systems.Different from the previous works,we first present a novel method for constructing a nonlocal product set with 3d-2 members on C^(d)■C^(d)■C^(d)quantum system for d≥3.Then,we extend this construction method to C^(d_(1))■C^(d_(2))■C^(d_(3))quantum system and■_(i=1)^(n)C^(di)quantum system respectively,where 3≤d_(1)≤d_(2)≤d_(3)≤…≤dC_(d_(i))and n≥3.The nonlocal set of OPSs constructed by our method contains fewer elements than those constructed by the existing methods,except for one special case.More importantly,the set of states constructed by our method has a completely different structure from those constructed by the existing methods since our nonlocal set does not contain a“stopper”state.Our result is helpful to further understand the different structures of nonlocal sets on multipartite systems.
基金funded by the National Key Research and Development Program of China(2022YFC3003502)。
文摘Local strong seismic activity shows the potential to closely follow a renewal process,which is inconsistent with the overall seismic activity that aligns with the Poisson process.Given that existing methods for synthesizing stochastic seismic event sets cannot control local seismic activity,a method based on Monte Carlo simulations has been developed for synthesizing random seismic event sets where local strong earthquakes satisfy the renewal process.This method can synthesize seismic activities in a statistical area where the overall activity conforms to the Poisson process and the major seismic activities in local potential sources or faults follow the renewal process.This paper presents long-and short-scale approaches.The long-scale earthquake catalogs are suitable for reflecting the sequential characteristics of seismic activities.Meanwhile,the short-scale catalogs focus on the impacts of specific earthquake events within a group for a detailed understanding of hazards under certain conditions,making them suitable for studies on specific earthquake sequences and geological areas or situations requiring high temporal resolution.In the applications of shortscale sequences,we find that the equivalent occurrence rate method may overestimate the seismic hazard.This synthesis method for earthquake catalogs can simulate realistic seismic activities,thereby enhancing the accuracy of hazard analysis results and is suitable for seismic hazard analysis and earthquake insurance rate setting.
基金The National Key Research and Development Program of China under contract No.2022YFC2807501.
文摘Despite being ubiquitous in oceans and important in marine biogeochemical cycles,planktonic archaea in the Southern Ocean(SO)remain poorly characterized.Although high-throughput sequencing(HTS)approaches based on 16S ribosomal RNA(rRNA)genes have been used widely to study the diversity and composition of microbial community in natural environments,primer-set selection is critical because of amplicon-sequencing bias during metabarcoding.Here,using surface-seawater samples collected from the area between the South Shetland and South Orkney Islands,Antarctica,we compared primer sets Arch349F/Arch806R,515F-Y/926R,and 524F/Arch958R,which target different 16S rRNA gene hypervariable regions to identify the best one for studying planktonic archaeal communities.With much lower number of bacteria-related sequences,primer set 524F/Arch958R showed higher values of archaeal operational taxonomic units(OTUs)as well as alpha-diversity indices,indicating that this primer set was more specific for detecting archaeal species and could be helpful to obtain more comprehensive information on the archaeal community compositions compared to other two primer sets.Compared with primer set Arch349F/Arch806R revealing four phyla(Halobacteriota,Methanobacteriota,Thermoplasmatota,and Thermoproteota)detected in seawater,additional archaeal phyla were observed by 515F-Y/926R(Asgardarchaeota and Nanoarchaeota)and 524F/Arch958R(Micrarchaeota).In spite of the differences in archaeal community compositions observed among the three investigated primer sets,ammonia-oxidizing(e.g.,Nitrososphaeria)and methane-producing(e.g.,Methanobacteria,Methanomicrobia,and Methanosarcinia)archaea were the main groups detected in the surface seawater,indicating the ecological role of planktonic archaea in carbon and nitrogen cycling in the upper waters of the SO.These results underscore the importance of primer-set selection when studying archaeal community diversity and composition in the Antarctic SO.
文摘In this paper,the transferable belief model established on power sets is extended to the permutation event space(PES)and is referred to as the layer-2 transferable belief model.Our goal is to provide a comprehensive approach for handling and modeling uncertainty,capable of representing both quantitative and qualitative information.First,the motivation for proposing the layer-2 transferable belief model and its information processing principles are explored from the perspective of weak propensity.Then,based on these principles,the corresponding information processing methods for the credal and pignistic levels are developed.Finally,the advantages of this model are validated through a classifier that leverages attribute fusion to enhance performance and decision-making accuracy.
文摘This study introduces a novel distance measure(DM)for(p,q,r)-spherical fuzzy sets((p,q,to improve decision-making in complex and uncertain environments.Many existing distance measures eitherr)-SFSs)fail to satisfy essential axiomatic properties or produce unintuitive outcomes.To address these limitations,we propose a new three-dimensional divergence-based DM that ensures mathematical consistency,enhances the discrimination of information,and adheres to the axiomatic framework of distance theory.Building on this foundation,we construct a multi-criteria decision-making(MCDM)model that utilizes the proposed DM to evaluate and rank alternatives effectively.The applicability and robustness of the model are validated through a practical case study,demonstrating that it leads to more rational,consistent,and reliable decision outcomes compared to existing approaches.
基金Supported by the Natural Science Foundation of Shandong Province (No.ZR2023MA031)the Natural Science Foundation of China (No.12201619)。
文摘Submodular optimization is primarily applied in multi-agent systems for tasks such as resource allocation,task assignment,collaborative decision-making,and optimization problems.Maximization of optimizing submodular set functions attracts much attention since the 1970s.A large body of work has been done using approximation algorithms.When the dimension of the independent variable of the set function changes from one tok,it is called ak-submodular set function.Thek-submodular set function,a generalization of the classical submodular set function,arises in diverse fields with varied applications.In many practical scenarios,quantifying the degree of closeness to submodularity becomes essential,leading to concepts such as approximately submodular set functions and the diminishing-return(DR) ratio.This paper investigates ak-dimensional set function under matroid constraints,which may lack full submodularity.Instead,we focus on an approximately non-ksubmodular set function characterized by its DR ratio.Employing a greedy algorithmic approach,we derive an approximation guarantee for this problem.Notably,when the DR ratio is set to one,our results align with existing findings in the literature.Experimental results demonstrate the superiority of our algorithm over the baselines.
基金Deputyship for Research&Innovation,Ministry of Education in Saudi Arabia for funding this research work through the project number RI-44-0028.
文摘The sustainability of the Internet of Things(IoT)involves various issues,such as poor connectivity,scalability problems,interoperability issues,and energy inefficiency.Although the Sixth Generation of mobile networks(6G)allows for Ultra-Reliable Low-Latency Communication(URLLC),enhanced Mobile Broadband(eMBB),and massive Machine-Type Communications(mMTC)services,it faces deployment challenges such as the short range of sub-THz and THz frequency bands,low capability to penetrate obstacles,and very high path loss.This paper presents a network architecture to enhance the connectivity of wireless IoT mesh networks that employ both 6G and Wi-Fi technologies.In this architecture,local communications are carried through the mesh network,which uses a virtual backbone to relay packets to local nodes,while remote communications are carried through the 6G network.The virtual backbone is created using a heuristic distributed ConnectedDominating Set(CDS)algorithm.In this algorithm,each node uses information collected from its one-and two-hop neighbors to determine its role and find the set of expansion nodes that are used to select the next CDS nodes.The proposed algorithm has O(n)message and O(K)time complexities,where n is the number of nodes in the network,and K is the depth of the cluster.The study proved that the approximation ratio of the algorithmhas an upper bound of 2.06748(3.4306MCDS+4.8185).Performance evaluations compared the size of the CDS against the theoretical limit and recent CDS clustering algorithms.Results indicate that the proposed algorithm has the smallest average slope for the size of the CDS as the number of nodes increases.
