After about 20 years of exciting improvements in treatment efficacy outcomes of advanced epidermal growth factor receptor(EGFR)mutant and anaplastic lymphoma kinase(ALK)rearranged non-small cell lung cancer(NSCLC),als...After about 20 years of exciting improvements in treatment efficacy outcomes of advanced epidermal growth factor receptor(EGFR)mutant and anaplastic lymphoma kinase(ALK)rearranged non-small cell lung cancer(NSCLC),also combined with a progressively better safety profile,from chemotherapy to new generation tyrosine kinase inhibitors(TKIs)(osimertinib,alectinib,brigatinib),the recent MARIPOSA and CROWN trials have changed this trend.For the first time in the history of EGFR and ALK treatments,we must face the issue of being a step behind in terms of toxicity profile.The combination of amivantamab plus lazertinib in EGFR mutant NSCLC,and lorlatinib in ALK rearranged NSCLC,has improved efficacy outcomes as never before.The story would be easy and totally positive if these two innovative,amazing treatments were not associated with new peculiar features in safety profiles that must be discussed with patients,because they potentially affect their quality of life.When treating these patient populations,the peculiar safety profiles of amivantamab plu lazertinib and lorlatinib require a well-structured shared decision making,“where and when”,both the high probability of a longer survival and the risk of worse quality of life must be well announced and explained to our patients before the shared final treatment choice.展开更多
The global shift towards sustainable energy has intensified research into renewable sources,particularly wave energy.Pakistan,with its long coastline,holds significant potential for wave energy development.However,ide...The global shift towards sustainable energy has intensified research into renewable sources,particularly wave energy.Pakistan,with its long coastline,holds significant potential for wave energy development.However,identifying optimal locations for wave energy plants involves evaluating complex,multi-faceted criteria.This study employs a multi-criteria group decisionmaking(MCGDM)approach using single-valued neutrosophic numbers(SVNNs)to address both qualitative and quantitative uncertainties inherent in real-world scenarios.To enhance decision quality,we introduce two novel operators:the singlevalued neutrosophic prioritised averaging(SVNPAd)operator and the single-valued neutrosophic prioritised geometric(SVNPGd)operator,both incorporating priority degrees.These tools allow decision-makers to express preferences better and handle ambiguous data.The proposed model is validated through comparative analysis with prior studies and demonstrates improved robustness in site selection.Furthermore,we analyse how variations in priority degrees influence decision outcomes,enabling a more dynamic and tailored decision-making process.Our method contributes a more holistic and adaptive framework for selecting locations for wave energy projects,ultimately supporting informed investments in renewable energy infrastructure and improving energy access in underserved coastal regions.展开更多
Embodied intelligent systems integrate perception,control,and decision-making within physical agents,and have become a cornerstone of modern aerospace,autonomous driving,and cooperative robotic applications.When opera...Embodied intelligent systems integrate perception,control,and decision-making within physical agents,and have become a cornerstone of modern aerospace,autonomous driving,and cooperative robotic applications.When operating in uncertain and dynamic environments,such systems must address challenges arising from incomplete sensing,unpredictable maneuvers,communication constraints,disturbances,and evolving network structures.展开更多
I<span style="font-family:Verdana;">n Ghana, freight transport is growing continuously every year due to its location and business processes. However, road transport carries 86% of frei</span><...I<span style="font-family:Verdana;">n Ghana, freight transport is growing continuously every year due to its location and business processes. However, road transport carries 86% of frei</span><span style="font-family:Verdana;">ght despite its numerous negative impacts. Hence, the government has invested in rail transport, with 70% of its capacity is for freight transport in her busy freight transport corridor (eastern transport regions of Ghana). Thus, awareness of criteria considered when deciding on freight transport becomes vital. Hence, this study aims to improve the understanding of the fa</span><span style="font-family:Verdana;">ctors of freight transport mode selection in Ghana from the decision-</span><span style="font-family:Verdana;">making process by identifying criteria that affect their decisions on mode transportation. The combination of Fuzzy AHP and Topsis is used to find the weights and suggest suitable alternatives for the decision-makers in the Eastern transport regions of Ghana. The result of this study shows that the criteria to consider when selecting freight transport mode in the regions are prioritized in other of Transport cost (0.6544), transport Time factors (0.2562), reliability, and flexibility (0.0605), and security, Risk of damage and lose factors (0.0287). Additionally, the suitable mode(s) of transportation in the stated corridor is owned truck carrier transport compared to the railroad, road-barge, and Contracted Carrier, thus, in descending order. The results provide organizations to prioritize these factors when deciding to select freight transport mode. At the same time, the government must remove some inputs that result in high transport cost</span><span style="font-family:Verdana;">s</span><span style="font-family:Verdana;">, enforce</span><span style="font-family:;" "=""> </span><span style="font-family:Verdana;">policies, and invest in the appropriate mode.</span>展开更多
Across four studies,we explore the impact of solitude on consumers’reliance on feelings versus reasons in decision making,along with the underlying mechanism and boundary conditions.The results indicate that solitude...Across four studies,we explore the impact of solitude on consumers’reliance on feelings versus reasons in decision making,along with the underlying mechanism and boundary conditions.The results indicate that solitude individuals(vs.non-solitude)would prefer feeling-based strategy in decision-making,resulting in a higher intention of choosing the affectively superior option over the cognitively superior option(Study 1).Self-focus plays the underlying mechanism in the solitude effect(Study 2).Moreover,we also examine two boundary conditions:motivation(Study 3)and temporal orientation(Study 4),which indicates that involuntary motivation and future orientation can mitigate the solitude effect on affective processing.These findings provide insights into consumers’judgments of product attributes and selection of decision-making strategies according to their situations.展开更多
Overall bank performance in a particular year or period is important to all banking industry stakeholders,as it indicates their success or failure relative to predetermined targets.Due to conflicting criteria and unce...Overall bank performance in a particular year or period is important to all banking industry stakeholders,as it indicates their success or failure relative to predetermined targets.Due to conflicting criteria and uncertainties,assessing bank performance is a complicated decision-making problem.The current paper proposes the Fuzzy Level Based Weight Assessment(F-LBWA),the Fuzzy Logarithm Methodology of Additive Weights(F-LMAW),and the Measurement Alternatives and Ranking according to the Compromise Solution(MARCOS)combination as a practical and robust decisionmaking tool to cope with many complex ambiguities.In the first phase,the suggested hybrid Multi-Criteria Decision-Making(MCDM)approach estimates the weight coefficients of the performance criteria with the aid of a combined version of the F-LBWA and F-LMAW methods.In the second phase,the MARCOS method determines the ranking performance of the decision alternatives.The introduced model is tested and validated on a case study assessing publicly traded bank performance in Pakistan.The findings obtained from the sensitivity analysis revealed that the presented F-LBWAF-LMAW-MARCOS approach produces consistent solutions and is a reliable and effective procedure in rational decision-making.展开更多
The implementation of Countermeasure Techniques(CTs)in the context of Network-On-Chip(NoC)based Multiprocessor System-On-Chip(MPSoC)routers against the Flooding Denial-of-Service Attack(F-DoSA)falls under Multi-Criter...The implementation of Countermeasure Techniques(CTs)in the context of Network-On-Chip(NoC)based Multiprocessor System-On-Chip(MPSoC)routers against the Flooding Denial-of-Service Attack(F-DoSA)falls under Multi-Criteria Decision-Making(MCDM)due to the three main concerns,called:traffic variations,multiple evaluation criteria-based traffic features,and prioritization NoC routers as an alternative.In this study,we propose a comprehensive evaluation of various NoC traffic features to identify the most efficient routers under the F-DoSA scenarios.Consequently,an MCDM approach is essential to address these emerging challenges.While the recent MCDM approach has some issues,such as uncertainty,this study utilizes Fuzzy-Weighted Zero-Inconsistency(FWZIC)to estimate the criteria weight values and Fuzzy Decision by Opinion Score Method(FDOSM)for ranking the routers with fuzzy Single-valued Neutrosophic under names(SvN-FWZIC and SvN-FDOSM)to overcome the ambiguity.The results obtained by using the SvN-FWZIC method indicate that the Max packet count has the highest importance among the evaluated criteria,with a weighted score of 0.1946.In contrast,the Hop count is identified as the least significant criterion,with a weighted score of 0.1090.The remaining criteria fall within a range of intermediate importance,with enqueue time scoring 0.1845,packet count decremented and traversal index scoring 0.1262,packet count incremented scoring 0.1124,and packet count index scoring 0.1472.In terms of ranking,SvN-FDOSM has two approaches:individual and group.Both the individual and group ranking processes show that(Router 4)is the most effective router,while(Router 3)is the lowest router under F-DoSA.The sensitivity analysis provides a high stability in ranking among all 10 scenarios.This approach offers essential feedback in making proper decisions in the design of countermeasure techniques in the domain of NoC-based MPSoC.展开更多
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
Making plans is a good idea,but every one's schedule looks differe nt.You may have to talk about your plans before you're able to make some.It could sound like this:You ask,"Do you have plans this Friday ...Making plans is a good idea,but every one's schedule looks differe nt.You may have to talk about your plans before you're able to make some.It could sound like this:You ask,"Do you have plans this Friday night?"If the person already has plans,they may say,"I do.But I'm free on Saturday."If that day doesn't work for you,you can say,"I'm not available that day.How about Sunday after no on?"After you figure out the day and time,mark it on your calendar.展开更多
The high maneuverability of modern fighters in close air combat imposes significant cognitive demands on pilots,making rapid,accurate decision-making challenging.While reinforcement learning(RL)has shown promise in th...The high maneuverability of modern fighters in close air combat imposes significant cognitive demands on pilots,making rapid,accurate decision-making challenging.While reinforcement learning(RL)has shown promise in this domain,the existing methods often lack strategic depth and generalization in complex,high-dimensional environments.To address these limitations,this paper proposes an optimized self-play method enhanced by advancements in fighter modeling,neural network design,and algorithmic frameworks.This study employs a six-degree-of-freedom(6-DOF)F-16 fighter model based on open-source aerodynamic data,featuring airborne equipment and a realistic visual simulation platform,unlike traditional 3-DOF models.To capture temporal dynamics,Long Short-Term Memory(LSTM)layers are integrated into the neural network,complemented by delayed input stacking.The RL environment incorporates expert strategies,curiositydriven rewards,and curriculum learning to improve adaptability and strategic decision-making.Experimental results demonstrate that the proposed approach achieves a winning rate exceeding90%against classical single-agent methods.Additionally,through enhanced 3D visual platforms,we conducted human-agent confrontation experiments,where the agent attained an average winning rate of over 75%.The agent's maneuver trajectories closely align with human pilot strategies,showcasing its potential in decision-making and pilot training applications.This study highlights the effectiveness of integrating advanced modeling and self-play techniques in developing robust air combat decision-making systems.展开更多
We examined the relationship between social support and career adaptability,as well as the mediating roles of proactive personality and career decision-making self-efficacy in this process.A total of 1354 Chinese coll...We examined the relationship between social support and career adaptability,as well as the mediating roles of proactive personality and career decision-making self-efficacy in this process.A total of 1354 Chinese college students(female=964;mean age=19.53 years,SD=1.33 years)completed an online questionnaire.Path analysis indicated that social support was positively associated with higher levels of career adaptability.Both proactive personality and career decision-making self-efficacy served as parallel mediators,strengthening the relationship between social support and career adaptability.The complete chain mediation analysis revealed that social support influences career adaptability primarily through proactive personality,which in turn enhances career decision-making self-efficacy,further contributing to increased career adaptability.These findings extend career capital theory by demonstrating that social and psychological resources jointly facilitate career adaptability.展开更多
WEIFANG City of east China’s Shandong Province is located in the central part of the Shandong Peninsula,bordering the Bohai Sea to the north and the Yellow Sea to the south.In springtime,the region sees little rainfa...WEIFANG City of east China’s Shandong Province is located in the central part of the Shandong Peninsula,bordering the Bohai Sea to the north and the Yellow Sea to the south.In springtime,the region sees little rainfall yet many windy days,with a single prevailing wind direction and minimal turbulence-an environmental condition ideal for kite flying.展开更多
Transportation systems are rapidly transforming in response to urbanization,sustainability challenges,and advances in digital technologies.This review synthesizes the intersection of artificial intelligence(AI),fuzzy ...Transportation systems are rapidly transforming in response to urbanization,sustainability challenges,and advances in digital technologies.This review synthesizes the intersection of artificial intelligence(AI),fuzzy logic,and multi-criteria decision-making(MCDM)in transportation research.A comprehensive literature search was conducted in the Scopus database,utilizing carefully selected AI,fuzzy,and MCDM keywords.Studies were rigorously screened according to explicit inclusion and exclusion criteria,resulting in 73 eligible publications spanning 2006-2025.The review protocol included transparent data extraction on methodological approaches,application domains,and geographic distribution.Key findings highlight the prevalence of hybrid fuzzyAHPand TOPSIS methods,the widespread integration of machine learning for prediction and optimization,and a predominant focus on logistics and infrastructure planning within the transportation sector.Geographic analysis underscores a marked concentration of research activity in Asia,while other regions remain underrepresented,signaling the need for broader international collaboration.The review also addresses persistent challenges such asmethodological complexity,data limitations,and model interpretability.Future research directions are proposed,including the integration of reinforcement learning,real-time analytics,and big data-driven adaptive solutions.This study offers a comprehensive synthesis and critical perspective,serving as a valuable reference for researchers,practitioners,and policymakers seeking to enhance the efficiency,resilience,and sustainability of transportation systems through intelligent decision-making frameworks.展开更多
This study focuses on the construction and application of intelligent financial decision-making models driven by generative artificial intelligence(AI).It analyzes the mechanisms by which generative AI empowers financ...This study focuses on the construction and application of intelligent financial decision-making models driven by generative artificial intelligence(AI).It analyzes the mechanisms by which generative AI empowers financial decision-making within a dual framework of dynamic knowledge evolution and risk control.The research reveals that generative AI,with its superior data processing,pattern recognition,and autonomous learning capabilities,can transcend the limitations of traditional decision-making models,facilitating a significant shift from causal inference to probabilistic creation in decision-making paradigms.By systematically constructing an intelligent financial decision-making model that includes data governance,core engine,and decision output layers,the study clarifies the functional roles and collaborative mechanisms of each layer.Additionally,it addresses key challenges in technology application,institutional adaptation,and organizational transformation by proposing systematic strategies for technical risk management,institutional innovation,and organizational capability enhancement,aiming to provide robust theoretical support and practical guidance for the intelligent transformation of corporate financial decision-making.展开更多
Enhancing Autonomous Decision-Making (ADM) for unmanned combat aerial vehicle formations in beyond-visual-range air combat is pivotal for future battlefields, whereas the predominant reinforcement learning technique f...Enhancing Autonomous Decision-Making (ADM) for unmanned combat aerial vehicle formations in beyond-visual-range air combat is pivotal for future battlefields, whereas the predominant reinforcement learning technique for ADM has been proven to be inadequately fitting complex tactical Unit Coordination (UC), limiting the integrity of decision-making for formations. This study proposes a knowledge-enhanced ADM method, with a focus on UC, to elevate formation combat effectiveness. The main innovation is integrating data mining technique with tactical knowledge mining and integration. Foremost, based on Frequent Event Arrangement Mining (FEAM) theory, a cross-channel UC knowledge mining method is designed by introducing data flow, which is capable of capturing dynamic coordinative action sequences. Then, a dual-mode knowledge integration method is proposed by employing the Graph Attention Network (GAT) and attenuated structural similarity, bolstering the interplay between autonomous UC tactics fitting and knowledge injection. The experimental results demonstrate that the algorithm surpasses the existing methods, providing more strategic maneuver trajectories and a win rate of more than 90% in different scenarios. The method is promising to augment the autonomous operational capabilities of unmanned formations and drive the evolution of combat effectiveness.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
With the civilization and modernization of human society,occupational health has emerged as a fundamental goal of social justice,as highlighted in the United Nations'Sustainable Development Goals(SDGs)since 2016.S...With the civilization and modernization of human society,occupational health has emerged as a fundamental goal of social justice,as highlighted in the United Nations'Sustainable Development Goals(SDGs)since 2016.Specifically,"SDG Goal 1:No Poverty","SDG 3:Good Health and Well-being",and"SDG 8:Decent Work and Economic Growth",are interconnected with other SDGs to support the pursuit of occupational health.展开更多
In this manuscript,the notion of a hesitant fuzzy soft fixed point is introduced.Using this notion and the concept of Suzuki-type(μ,ν)-weak contraction for hesitant fuzzy soft set valued-mapping,some fixed point res...In this manuscript,the notion of a hesitant fuzzy soft fixed point is introduced.Using this notion and the concept of Suzuki-type(μ,ν)-weak contraction for hesitant fuzzy soft set valued-mapping,some fixed point results are established in the framework of metric spaces.Based on the presented work,some examples reflecting decision-making problems related to real life are also solved.The suggested method’s flexibility and efficacy compared to conventional techniques are demonstrated in decision-making situations involving uncertainty,such as choosing the best options in multi-criteria settings.We noted that the presented work combines and generalizes two major concepts,the idea of soft sets and hesitant fuzzy set-valued mapping from the existing literature.展开更多
文摘After about 20 years of exciting improvements in treatment efficacy outcomes of advanced epidermal growth factor receptor(EGFR)mutant and anaplastic lymphoma kinase(ALK)rearranged non-small cell lung cancer(NSCLC),also combined with a progressively better safety profile,from chemotherapy to new generation tyrosine kinase inhibitors(TKIs)(osimertinib,alectinib,brigatinib),the recent MARIPOSA and CROWN trials have changed this trend.For the first time in the history of EGFR and ALK treatments,we must face the issue of being a step behind in terms of toxicity profile.The combination of amivantamab plus lazertinib in EGFR mutant NSCLC,and lorlatinib in ALK rearranged NSCLC,has improved efficacy outcomes as never before.The story would be easy and totally positive if these two innovative,amazing treatments were not associated with new peculiar features in safety profiles that must be discussed with patients,because they potentially affect their quality of life.When treating these patient populations,the peculiar safety profiles of amivantamab plu lazertinib and lorlatinib require a well-structured shared decision making,“where and when”,both the high probability of a longer survival and the risk of worse quality of life must be well announced and explained to our patients before the shared final treatment choice.
基金supported by Science foundation Ireland(22/NCF/DR/11309).
文摘The global shift towards sustainable energy has intensified research into renewable sources,particularly wave energy.Pakistan,with its long coastline,holds significant potential for wave energy development.However,identifying optimal locations for wave energy plants involves evaluating complex,multi-faceted criteria.This study employs a multi-criteria group decisionmaking(MCGDM)approach using single-valued neutrosophic numbers(SVNNs)to address both qualitative and quantitative uncertainties inherent in real-world scenarios.To enhance decision quality,we introduce two novel operators:the singlevalued neutrosophic prioritised averaging(SVNPAd)operator and the single-valued neutrosophic prioritised geometric(SVNPGd)operator,both incorporating priority degrees.These tools allow decision-makers to express preferences better and handle ambiguous data.The proposed model is validated through comparative analysis with prior studies and demonstrates improved robustness in site selection.Furthermore,we analyse how variations in priority degrees influence decision outcomes,enabling a more dynamic and tailored decision-making process.Our method contributes a more holistic and adaptive framework for selecting locations for wave energy projects,ultimately supporting informed investments in renewable energy infrastructure and improving energy access in underserved coastal regions.
文摘Embodied intelligent systems integrate perception,control,and decision-making within physical agents,and have become a cornerstone of modern aerospace,autonomous driving,and cooperative robotic applications.When operating in uncertain and dynamic environments,such systems must address challenges arising from incomplete sensing,unpredictable maneuvers,communication constraints,disturbances,and evolving network structures.
文摘I<span style="font-family:Verdana;">n Ghana, freight transport is growing continuously every year due to its location and business processes. However, road transport carries 86% of frei</span><span style="font-family:Verdana;">ght despite its numerous negative impacts. Hence, the government has invested in rail transport, with 70% of its capacity is for freight transport in her busy freight transport corridor (eastern transport regions of Ghana). Thus, awareness of criteria considered when deciding on freight transport becomes vital. Hence, this study aims to improve the understanding of the fa</span><span style="font-family:Verdana;">ctors of freight transport mode selection in Ghana from the decision-</span><span style="font-family:Verdana;">making process by identifying criteria that affect their decisions on mode transportation. The combination of Fuzzy AHP and Topsis is used to find the weights and suggest suitable alternatives for the decision-makers in the Eastern transport regions of Ghana. The result of this study shows that the criteria to consider when selecting freight transport mode in the regions are prioritized in other of Transport cost (0.6544), transport Time factors (0.2562), reliability, and flexibility (0.0605), and security, Risk of damage and lose factors (0.0287). Additionally, the suitable mode(s) of transportation in the stated corridor is owned truck carrier transport compared to the railroad, road-barge, and Contracted Carrier, thus, in descending order. The results provide organizations to prioritize these factors when deciding to select freight transport mode. At the same time, the government must remove some inputs that result in high transport cost</span><span style="font-family:Verdana;">s</span><span style="font-family:Verdana;">, enforce</span><span style="font-family:;" "=""> </span><span style="font-family:Verdana;">policies, and invest in the appropriate mode.</span>
文摘Across four studies,we explore the impact of solitude on consumers’reliance on feelings versus reasons in decision making,along with the underlying mechanism and boundary conditions.The results indicate that solitude individuals(vs.non-solitude)would prefer feeling-based strategy in decision-making,resulting in a higher intention of choosing the affectively superior option over the cognitively superior option(Study 1).Self-focus plays the underlying mechanism in the solitude effect(Study 2).Moreover,we also examine two boundary conditions:motivation(Study 3)and temporal orientation(Study 4),which indicates that involuntary motivation and future orientation can mitigate the solitude effect on affective processing.These findings provide insights into consumers’judgments of product attributes and selection of decision-making strategies according to their situations.
文摘Overall bank performance in a particular year or period is important to all banking industry stakeholders,as it indicates their success or failure relative to predetermined targets.Due to conflicting criteria and uncertainties,assessing bank performance is a complicated decision-making problem.The current paper proposes the Fuzzy Level Based Weight Assessment(F-LBWA),the Fuzzy Logarithm Methodology of Additive Weights(F-LMAW),and the Measurement Alternatives and Ranking according to the Compromise Solution(MARCOS)combination as a practical and robust decisionmaking tool to cope with many complex ambiguities.In the first phase,the suggested hybrid Multi-Criteria Decision-Making(MCDM)approach estimates the weight coefficients of the performance criteria with the aid of a combined version of the F-LBWA and F-LMAW methods.In the second phase,the MARCOS method determines the ranking performance of the decision alternatives.The introduced model is tested and validated on a case study assessing publicly traded bank performance in Pakistan.The findings obtained from the sensitivity analysis revealed that the presented F-LBWAF-LMAW-MARCOS approach produces consistent solutions and is a reliable and effective procedure in rational decision-making.
文摘The implementation of Countermeasure Techniques(CTs)in the context of Network-On-Chip(NoC)based Multiprocessor System-On-Chip(MPSoC)routers against the Flooding Denial-of-Service Attack(F-DoSA)falls under Multi-Criteria Decision-Making(MCDM)due to the three main concerns,called:traffic variations,multiple evaluation criteria-based traffic features,and prioritization NoC routers as an alternative.In this study,we propose a comprehensive evaluation of various NoC traffic features to identify the most efficient routers under the F-DoSA scenarios.Consequently,an MCDM approach is essential to address these emerging challenges.While the recent MCDM approach has some issues,such as uncertainty,this study utilizes Fuzzy-Weighted Zero-Inconsistency(FWZIC)to estimate the criteria weight values and Fuzzy Decision by Opinion Score Method(FDOSM)for ranking the routers with fuzzy Single-valued Neutrosophic under names(SvN-FWZIC and SvN-FDOSM)to overcome the ambiguity.The results obtained by using the SvN-FWZIC method indicate that the Max packet count has the highest importance among the evaluated criteria,with a weighted score of 0.1946.In contrast,the Hop count is identified as the least significant criterion,with a weighted score of 0.1090.The remaining criteria fall within a range of intermediate importance,with enqueue time scoring 0.1845,packet count decremented and traversal index scoring 0.1262,packet count incremented scoring 0.1124,and packet count index scoring 0.1472.In terms of ranking,SvN-FDOSM has two approaches:individual and group.Both the individual and group ranking processes show that(Router 4)is the most effective router,while(Router 3)is the lowest router under F-DoSA.The sensitivity analysis provides a high stability in ranking among all 10 scenarios.This approach offers essential feedback in making proper decisions in the design of countermeasure techniques in the domain of NoC-based MPSoC.
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Making plans is a good idea,but every one's schedule looks differe nt.You may have to talk about your plans before you're able to make some.It could sound like this:You ask,"Do you have plans this Friday night?"If the person already has plans,they may say,"I do.But I'm free on Saturday."If that day doesn't work for you,you can say,"I'm not available that day.How about Sunday after no on?"After you figure out the day and time,mark it on your calendar.
基金co-supported by the National Natural Science Foundation of China(No.91852115)。
文摘The high maneuverability of modern fighters in close air combat imposes significant cognitive demands on pilots,making rapid,accurate decision-making challenging.While reinforcement learning(RL)has shown promise in this domain,the existing methods often lack strategic depth and generalization in complex,high-dimensional environments.To address these limitations,this paper proposes an optimized self-play method enhanced by advancements in fighter modeling,neural network design,and algorithmic frameworks.This study employs a six-degree-of-freedom(6-DOF)F-16 fighter model based on open-source aerodynamic data,featuring airborne equipment and a realistic visual simulation platform,unlike traditional 3-DOF models.To capture temporal dynamics,Long Short-Term Memory(LSTM)layers are integrated into the neural network,complemented by delayed input stacking.The RL environment incorporates expert strategies,curiositydriven rewards,and curriculum learning to improve adaptability and strategic decision-making.Experimental results demonstrate that the proposed approach achieves a winning rate exceeding90%against classical single-agent methods.Additionally,through enhanced 3D visual platforms,we conducted human-agent confrontation experiments,where the agent attained an average winning rate of over 75%.The agent's maneuver trajectories closely align with human pilot strategies,showcasing its potential in decision-making and pilot training applications.This study highlights the effectiveness of integrating advanced modeling and self-play techniques in developing robust air combat decision-making systems.
基金supported by“Planning Subject for the 14th Five Year Plan of National Education Sciences of China(DBA210296)”.
文摘We examined the relationship between social support and career adaptability,as well as the mediating roles of proactive personality and career decision-making self-efficacy in this process.A total of 1354 Chinese college students(female=964;mean age=19.53 years,SD=1.33 years)completed an online questionnaire.Path analysis indicated that social support was positively associated with higher levels of career adaptability.Both proactive personality and career decision-making self-efficacy served as parallel mediators,strengthening the relationship between social support and career adaptability.The complete chain mediation analysis revealed that social support influences career adaptability primarily through proactive personality,which in turn enhances career decision-making self-efficacy,further contributing to increased career adaptability.These findings extend career capital theory by demonstrating that social and psychological resources jointly facilitate career adaptability.
文摘WEIFANG City of east China’s Shandong Province is located in the central part of the Shandong Peninsula,bordering the Bohai Sea to the north and the Yellow Sea to the south.In springtime,the region sees little rainfall yet many windy days,with a single prevailing wind direction and minimal turbulence-an environmental condition ideal for kite flying.
文摘Transportation systems are rapidly transforming in response to urbanization,sustainability challenges,and advances in digital technologies.This review synthesizes the intersection of artificial intelligence(AI),fuzzy logic,and multi-criteria decision-making(MCDM)in transportation research.A comprehensive literature search was conducted in the Scopus database,utilizing carefully selected AI,fuzzy,and MCDM keywords.Studies were rigorously screened according to explicit inclusion and exclusion criteria,resulting in 73 eligible publications spanning 2006-2025.The review protocol included transparent data extraction on methodological approaches,application domains,and geographic distribution.Key findings highlight the prevalence of hybrid fuzzyAHPand TOPSIS methods,the widespread integration of machine learning for prediction and optimization,and a predominant focus on logistics and infrastructure planning within the transportation sector.Geographic analysis underscores a marked concentration of research activity in Asia,while other regions remain underrepresented,signaling the need for broader international collaboration.The review also addresses persistent challenges such asmethodological complexity,data limitations,and model interpretability.Future research directions are proposed,including the integration of reinforcement learning,real-time analytics,and big data-driven adaptive solutions.This study offers a comprehensive synthesis and critical perspective,serving as a valuable reference for researchers,practitioners,and policymakers seeking to enhance the efficiency,resilience,and sustainability of transportation systems through intelligent decision-making frameworks.
文摘This study focuses on the construction and application of intelligent financial decision-making models driven by generative artificial intelligence(AI).It analyzes the mechanisms by which generative AI empowers financial decision-making within a dual framework of dynamic knowledge evolution and risk control.The research reveals that generative AI,with its superior data processing,pattern recognition,and autonomous learning capabilities,can transcend the limitations of traditional decision-making models,facilitating a significant shift from causal inference to probabilistic creation in decision-making paradigms.By systematically constructing an intelligent financial decision-making model that includes data governance,core engine,and decision output layers,the study clarifies the functional roles and collaborative mechanisms of each layer.Additionally,it addresses key challenges in technology application,institutional adaptation,and organizational transformation by proposing systematic strategies for technical risk management,institutional innovation,and organizational capability enhancement,aiming to provide robust theoretical support and practical guidance for the intelligent transformation of corporate financial decision-making.
文摘Enhancing Autonomous Decision-Making (ADM) for unmanned combat aerial vehicle formations in beyond-visual-range air combat is pivotal for future battlefields, whereas the predominant reinforcement learning technique for ADM has been proven to be inadequately fitting complex tactical Unit Coordination (UC), limiting the integrity of decision-making for formations. This study proposes a knowledge-enhanced ADM method, with a focus on UC, to elevate formation combat effectiveness. The main innovation is integrating data mining technique with tactical knowledge mining and integration. Foremost, based on Frequent Event Arrangement Mining (FEAM) theory, a cross-channel UC knowledge mining method is designed by introducing data flow, which is capable of capturing dynamic coordinative action sequences. Then, a dual-mode knowledge integration method is proposed by employing the Graph Attention Network (GAT) and attenuated structural similarity, bolstering the interplay between autonomous UC tactics fitting and knowledge injection. The experimental results demonstrate that the algorithm surpasses the existing methods, providing more strategic maneuver trajectories and a win rate of more than 90% in different scenarios. The method is promising to augment the autonomous operational capabilities of unmanned formations and drive the evolution of combat effectiveness.
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.
文摘With the civilization and modernization of human society,occupational health has emerged as a fundamental goal of social justice,as highlighted in the United Nations'Sustainable Development Goals(SDGs)since 2016.Specifically,"SDG Goal 1:No Poverty","SDG 3:Good Health and Well-being",and"SDG 8:Decent Work and Economic Growth",are interconnected with other SDGs to support the pursuit of occupational health.
基金funded by National Science,Research and Innovation Fund(NSRF)King Mongkut's University of Technology North Bangkok with Contract No.KMUTNB-FF-68-B-46.
文摘In this manuscript,the notion of a hesitant fuzzy soft fixed point is introduced.Using this notion and the concept of Suzuki-type(μ,ν)-weak contraction for hesitant fuzzy soft set valued-mapping,some fixed point results are established in the framework of metric spaces.Based on the presented work,some examples reflecting decision-making problems related to real life are also solved.The suggested method’s flexibility and efficacy compared to conventional techniques are demonstrated in decision-making situations involving uncertainty,such as choosing the best options in multi-criteria settings.We noted that the presented work combines and generalizes two major concepts,the idea of soft sets and hesitant fuzzy set-valued mapping from the existing literature.
