In the rapidly evolving landscape of today’s digital economy,Financial Technology(Fintech)emerges as a trans-formative force,propelled by the dynamic synergy between Artificial Intelligence(AI)and Algorithmic Trading...In the rapidly evolving landscape of today’s digital economy,Financial Technology(Fintech)emerges as a trans-formative force,propelled by the dynamic synergy between Artificial Intelligence(AI)and Algorithmic Trading.Our in-depth investigation delves into the intricacies of merging Multi-Agent Reinforcement Learning(MARL)and Explainable AI(XAI)within Fintech,aiming to refine Algorithmic Trading strategies.Through meticulous examination,we uncover the nuanced interactions of AI-driven agents as they collaborate and compete within the financial realm,employing sophisticated deep learning techniques to enhance the clarity and adaptability of trading decisions.These AI-infused Fintech platforms harness collective intelligence to unearth trends,mitigate risks,and provide tailored financial guidance,fostering benefits for individuals and enterprises navigating the digital landscape.Our research holds the potential to revolutionize finance,opening doors to fresh avenues for investment and asset management in the digital age.Additionally,our statistical evaluation yields encouraging results,with metrics such as Accuracy=0.85,Precision=0.88,and F1 Score=0.86,reaffirming the efficacy of our approach within Fintech and emphasizing its reliability and innovative prowess.展开更多
The existing algorithms for solving multi-objective optimization problems fall into three main categories:Decomposition-based,dominance-based,and indicator-based.Traditional multi-objective optimization problemsmainly...The existing algorithms for solving multi-objective optimization problems fall into three main categories:Decomposition-based,dominance-based,and indicator-based.Traditional multi-objective optimization problemsmainly focus on objectives,treating decision variables as a total variable to solve the problem without consideringthe critical role of decision variables in objective optimization.As seen,a variety of decision variable groupingalgorithms have been proposed.However,these algorithms are relatively broad for the changes of most decisionvariables in the evolution process and are time-consuming in the process of finding the Pareto frontier.To solvethese problems,a multi-objective optimization algorithm for grouping decision variables based on extreme pointPareto frontier(MOEA-DV/EPF)is proposed.This algorithm adopts a preprocessing rule to solve the Paretooptimal solution set of extreme points generated by simultaneous evolution in various target directions,obtainsthe basic Pareto front surface to determine the convergence effect,and analyzes the convergence and distributioneffects of decision variables.In the later stages of algorithm optimization,different mutation strategies are adoptedaccording to the nature of the decision variables to speed up the rate of evolution to obtain excellent individuals,thusenhancing the performance of the algorithm.Evaluation validation of the test functions shows that this algorithmcan solve the multi-objective optimization problem more efficiently.展开更多
Introduction Life research serves as the vanguard of scientific exploration,where the intricate symphony of living organisms unfolds,unraveling the mysteries of existence.Encompassing biology,genetics,ecology,and beyo...Introduction Life research serves as the vanguard of scientific exploration,where the intricate symphony of living organisms unfolds,unraveling the mysteries of existence.Encompassing biology,genetics,ecology,and beyond,it weaves a narrative delving into life’s essence,propelling us toward a profound comprehension of our world.In the relentless pursuit of knowledge,life researchers decode fundamental processes,from unraveling DNA’s secrets to probing the delicate balances of ecosystems.The hallmark of contemporary life research lies in its interdisciplinary character,fostering collaboration among biologists,chemists,physicists,and computational scientists.This collaborative synergy embraces a holistic approach,enabling researchers to address intricate biological questions,spur innovation,and redefine the limits of what was once deemed possible.展开更多
As an important guarantee for human survival and development,the increasing use of mineral resources has led to the generation of a large amount of tailings and slags.However,with the deep promotion of green concepts ...As an important guarantee for human survival and development,the increasing use of mineral resources has led to the generation of a large amount of tailings and slags.However,with the deep promotion of green concepts such as solid waste resource utilization and sustainable development,adding additives to tailings as filling materials can not only improve resource utilization efficiency and prevent surface collapse,but also reduce solid waste discharge to the surface,which is an effective way to fully utilize tailings resources and achieve land and energy saving,environmental protection,and waste utilization.展开更多
1.Introduction:a history of violence In the eyes of both ancients and moderns,the Central Asian frontier zone(s)of the Achaemenid Empire,here understood as the satrapies of Baktria,Sogdiana,Chorasmia,and the semi-dese...1.Introduction:a history of violence In the eyes of both ancients and moderns,the Central Asian frontier zone(s)of the Achaemenid Empire,here understood as the satrapies of Baktria,Sogdiana,Chorasmia,and the semi-desertic steppes to their north,has traditionally assumed the features of a liminal territory characterized by geopolitical instability and cultural alienation.展开更多
To promote the new applications of high abundance rare earth elements,Rare Earth Industry Association of Inner Mongolia Autonomous Region of China jointly collaborated with Rare Earth Industry Association(REIA)held a ...To promote the new applications of high abundance rare earth elements,Rare Earth Industry Association of Inner Mongolia Autonomous Region of China jointly collaborated with Rare Earth Industry Association(REIA)held a webinar on new frontier in rare earths application on 22 November,which attracted wide attention of rare earth producers,researchers and traders in global industry.The topics covered global rare earth market situation.展开更多
基金This project was funded by Deanship of Scientific Research(DSR)at King Abdulaziz University,Jeddah underGrant No.(IFPIP-1127-611-1443)the authors,therefore,acknowledge with thanks DSR technical and financial support.
文摘In the rapidly evolving landscape of today’s digital economy,Financial Technology(Fintech)emerges as a trans-formative force,propelled by the dynamic synergy between Artificial Intelligence(AI)and Algorithmic Trading.Our in-depth investigation delves into the intricacies of merging Multi-Agent Reinforcement Learning(MARL)and Explainable AI(XAI)within Fintech,aiming to refine Algorithmic Trading strategies.Through meticulous examination,we uncover the nuanced interactions of AI-driven agents as they collaborate and compete within the financial realm,employing sophisticated deep learning techniques to enhance the clarity and adaptability of trading decisions.These AI-infused Fintech platforms harness collective intelligence to unearth trends,mitigate risks,and provide tailored financial guidance,fostering benefits for individuals and enterprises navigating the digital landscape.Our research holds the potential to revolutionize finance,opening doors to fresh avenues for investment and asset management in the digital age.Additionally,our statistical evaluation yields encouraging results,with metrics such as Accuracy=0.85,Precision=0.88,and F1 Score=0.86,reaffirming the efficacy of our approach within Fintech and emphasizing its reliability and innovative prowess.
基金the Liaoning Province Nature Fundation Project(2022-MS-291)the National Programme for Foreign Expert Projects(G2022006008L)+2 种基金the Basic Research Projects of Liaoning Provincial Department of Education(LJKMZ20220781,LJKMZ20220783,LJKQZ20222457)King Saud University funded this study through theResearcher Support Program Number(RSPD2023R704)King Saud University,Riyadh,Saudi Arabia.
文摘The existing algorithms for solving multi-objective optimization problems fall into three main categories:Decomposition-based,dominance-based,and indicator-based.Traditional multi-objective optimization problemsmainly focus on objectives,treating decision variables as a total variable to solve the problem without consideringthe critical role of decision variables in objective optimization.As seen,a variety of decision variable groupingalgorithms have been proposed.However,these algorithms are relatively broad for the changes of most decisionvariables in the evolution process and are time-consuming in the process of finding the Pareto frontier.To solvethese problems,a multi-objective optimization algorithm for grouping decision variables based on extreme pointPareto frontier(MOEA-DV/EPF)is proposed.This algorithm adopts a preprocessing rule to solve the Paretooptimal solution set of extreme points generated by simultaneous evolution in various target directions,obtainsthe basic Pareto front surface to determine the convergence effect,and analyzes the convergence and distributioneffects of decision variables.In the later stages of algorithm optimization,different mutation strategies are adoptedaccording to the nature of the decision variables to speed up the rate of evolution to obtain excellent individuals,thusenhancing the performance of the algorithm.Evaluation validation of the test functions shows that this algorithmcan solve the multi-objective optimization problem more efficiently.
文摘Introduction Life research serves as the vanguard of scientific exploration,where the intricate symphony of living organisms unfolds,unraveling the mysteries of existence.Encompassing biology,genetics,ecology,and beyond,it weaves a narrative delving into life’s essence,propelling us toward a profound comprehension of our world.In the relentless pursuit of knowledge,life researchers decode fundamental processes,from unraveling DNA’s secrets to probing the delicate balances of ecosystems.The hallmark of contemporary life research lies in its interdisciplinary character,fostering collaboration among biologists,chemists,physicists,and computational scientists.This collaborative synergy embraces a holistic approach,enabling researchers to address intricate biological questions,spur innovation,and redefine the limits of what was once deemed possible.
文摘As an important guarantee for human survival and development,the increasing use of mineral resources has led to the generation of a large amount of tailings and slags.However,with the deep promotion of green concepts such as solid waste resource utilization and sustainable development,adding additives to tailings as filling materials can not only improve resource utilization efficiency and prevent surface collapse,but also reduce solid waste discharge to the surface,which is an effective way to fully utilize tailings resources and achieve land and energy saving,environmental protection,and waste utilization.
文摘1.Introduction:a history of violence In the eyes of both ancients and moderns,the Central Asian frontier zone(s)of the Achaemenid Empire,here understood as the satrapies of Baktria,Sogdiana,Chorasmia,and the semi-desertic steppes to their north,has traditionally assumed the features of a liminal territory characterized by geopolitical instability and cultural alienation.
文摘To promote the new applications of high abundance rare earth elements,Rare Earth Industry Association of Inner Mongolia Autonomous Region of China jointly collaborated with Rare Earth Industry Association(REIA)held a webinar on new frontier in rare earths application on 22 November,which attracted wide attention of rare earth producers,researchers and traders in global industry.The topics covered global rare earth market situation.
