Unleashing the Power of Multi-Agent Reinforcement Learning for Algorithmic Trading in the Digital Financial Frontier and Enterprise Information Systems

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.

Multi-Objective Optimization Algorithm for Grouping Decision Variables Based on Extreme Point Pareto Frontier

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.

Exploring the frontiers of life research

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.

Editorial for special issue on frontiers and advances in cemented paste backfill

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.

THE STEPPE FRONTIERS OF PĀRSA: NEGOTIATING THE NORTHEASTERN BORDERLANDS OF THE TEISPID-ACHAEMENID EMPIRE

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.

2023 new frontier in rare earths application webinar held successfully

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.

Progress and Frontier of Landscape Culture Research

Landscape culture is a new science and a comprehensive creation based on excellent tradition of cultural landscape.The paper has illustrated the generation and development of landscape culture,and introduced the current situation and progress of foreign researches on landscape culture according to the time order and research focuses.In terms of domestic research of landscape culture,it has been analyzed from the perspective of the study of theoretical connotation,landscape ecology,types of landscape culture and crossover study of itself.It considers that there exist some problems in domestic research on landscape culture,which are separation between traditional cultural landscape and modern landscape culture,separation in research methods,the influence of traditional culture on landscape,unbalanced development of regional landscape culture,separation of regional landscape network,and the insufficiency of protection and development.

Syngo.via Frontier工作站在极外侧入路手术治疗腰椎结核中的应用效果

目的探讨Syngo. via Frontier工作站在极外侧入路手术治疗腰椎结核中的应用效果。方法将48例行极外侧入路手术治疗的腰椎结核患者,随机分为研究组和对照组,每组24例。对照组在计算机导航下手术,研究组在对照组基础上增加Syngo. via Frontier工作站辅助。比较两组患者医患沟通满意度、术中出血量、手术时间、相关并发症发生情况、术后6个月美国脊柱损伤协会(ASIA)分级及术后12个月治愈率。结果研究组医患沟通满意度及术后12个月治愈率均高于对照组,而术中出血量、手术时间均少于对照组(均P <0. 05)。两组术后均有患者出现大腿前方麻木(研究组2例,对照组3例),出现屈髋无力各1例,经营养神经治疗后治愈。随访期间两组患者均未见钛网移位、塌陷,内固定无松动、断裂。两组术后6个月ASIA分级均优于术前(均P <0. 05),但两组间差异无统计学意义(P> 0. 05)。结论 Syngo. via Frontier工作站用于极外侧入路手术治疗腰椎结核的疗效确切,可提高医患沟通满意度,减少术中出血量并缩短手术时间。

基于Meta-Frontier-Bootstrap-DEA方法的中国高端装备制造企业效率测度研究

采用Meta-Frontier-Bootstrap-DEA方法对2012—2015年中国高端装备制造企业的效率进行测算,避免了传统DEA方法未考虑决策单元生产技术的行业差异、存在偏差等不足,研究结果表明:先进轨道交通设备、农机装备两个行业技平效高;高档数控机床和机器人、海洋工程装备及高技术船舶两个行业技劣效均;航空航天装备行业技平效均;电力装备、节能与新能源汽车两个行业技优效低。结合中国七大高端装备制造行业的实际情况,从微观企业、中观行业和宏观政府三个层面提出各行业增强技术水平和提高效率的建议。

Full ranking procedure based on best and worst frontiers

In the traditional data envelopment analysis （DEA） structure, the efficiency score for one decision making unit （DMU） is calculated by measuring the distance of the evaluated DMU to the best practice frontier. Recent researches have provided the reasonability of considering the worst practice frontier as a supple- ment to the traditional DEA techniques. The existing researches take only one type of frontier into account, and they cannot com- pare the evaluated DMU with both the best and the worst perform- ing DMUs. A DEA-based procedure is developed to consider the best and the worst frontiers in the same scenario where the ratio of two distances （RDS） measure is proposed. The principal appli- cation of this approach is for ranking, and, as a complement tool, for performance evaluation. The proposed approach can be used in a wide range of applications such as the performance evaluation of employees and others. Finally, a bookstore data set is used to illustrate the proposed approach.

基于modeFRONTIER的离合器碟形弹簧多目标优化设计

分析了离合器碟形弹簧的工作特性,以在摩擦片极限磨损范围内碟形弹簧工作压紧力变化量的平均值最小及碟形弹簧体积最小为优化目标,运用统一目标函数法建立多目标优化设计数学模型,利用modeFRONTIER优化软件进行优化计算。结果表明,优化后碟形弹簧的相关性能得到显著提高,目标函数值分别下降了36%和6%。modeFRONTIER软件解决优化问题,使用简便、算法高效,提高了设计效率。

Technical Efficiency Analysis of Electric Power Industry with Stochastic Frontier Model

A kind of algorithm was provided to resolve the calculating problem of stochastic frontier model and applied to electric power industry.By Matlab,maximum likelihood estimation is adopted to evaluate σ and λ of stochastic frontier model in this paper, then the technical efficiency of electric power companies is calculated. The calculated and analyzed results reflect the situation of the management of electric power industry on the whole,that is ,the electric power companies with high technical efficiency are those which have developed their modern enterprise system successfully.

The quantified analysis of China's GM cotton yield capacity by C-D function and stochastic frontier model

Using a modified C D function and stochastic frontier model, the paper analyzed China's cotton yield capacity and found that the yield and technical efficiency of China's cotton planting system can be increased by the use of genetically modified (GM) varieties.

A comparative analysis of multi-output frontier models

Recently, there have been more debates on the methods of measuring efficiency. The main objective of this paper is to make a sensitivity analysis for different frontier models and compare the results obtained from the different methods of estimating multi-output frontier for a specific application. The methods include stochastic distance function frontier, stochastic ray frontier, and data envelopment analysis. The stochastic frontier regressions with and without the inefficiency effects model are also com-pared and tested. The results indicate that there are significant correlations between the results obtained from the alternative estimation methods.

基于ABAQUS及modeFRONTIER的多目标优化方法

在涉及有限元分析的多目标优化设计中,为满足多目标优化算法的数据需求,需要反复进行有限元分析计算,存在设计工作繁琐,效率低的问题,为解决这一问题,提出了一种将有限元分析方法和多目标优化方法进行集成的设计方法。该方法基于ABAQUS软件二次开发实现有限元分析,基于mode FRONTIER软件实现多目标优化和优化数据的后处理工作,将两者集成在同一个优化工作流中来完成多目标优化设计。采用该方法对支架结构进行多目标优化设计,结果表明该方法不但可行,而且可以大大简化优化设计工作步骤,实现了优化设计的自动化,提高了优化设计工作效率。该方法可实现涉及有限元分析的多目标优化设计的自动化,为从事多目标优化设计工作者提供极大便利。

An Analysis on the Frontier Detection of English Teaching Methodology

English teaching methodology is the guidance in the process of English teaching. Based on the analysis of multi-source data, quantitative research and visualized analysis, we are aimed to analyze the frontier of English teaching methodology and try to explore the advanced English teaching methodology, improve the English teaching and provide the scientific data and appropriate methods for the local English teaching.

基于SBM-undesirable和Meta-frontier模型的能源效率研究

在考虑东中西区域间技术集合差异的基础上,采用SBM-Undesirable和Meta-frontier函数模型测算区域间能源效率。同时采用共同技术比率定量分析了各省区能源利用的技术差距,并从生产技术和管理两个维度分析能源利用无效率来源。发现中国能源效率整体存在较大改善空间且呈现出东-西-中递减格局。各省区在共同前沿边界下能源效率技术水平均不大于群组前沿边界下的能源效率,且东-西-中三大地区能源效率的无效率来源各有不同,需要因地制宜制定不同提升策略。

基于SBM-undesirable和Meta-frontier模型的APEC能源效率研究

准确测算能源效率与提升潜力可以为制定有效的节能减排策略提供科学依据。为进一步完善跨国研究中由于技术异质性导致的能源效率测算偏差,采用SBM-Undesirable模型和Meta-frontier生产函数,测算了APEC17个成员1990—2012年期间的能源效率。同时,采用"共同技术比率"定量考察了各成员能源利用的技术差距,并从"生产技术"和"管理"两个维度将能源利用无效率分解为"技术差距无效率"和"管理无效率"来探寻能源效率提升途径。研究发现:发达国家和地区在共同前沿和群组前沿下的能源效率没有差异,发展中国家和地区在两种前沿下的能源效率有显著差异;发展中国家与潜在的最优技术水平的差距有扩大的趋势;发达国家和地区应从管理方面提高能源效率,发展中国家和地区则要从技术和管理双方面来提高能源效率。

基于Factored Frontier算法的动态贝叶斯网络灵敏性分析方法

贝叶斯网络的灵敏性分析是研究模型局部参数或证据微小变化对于目标结点所产生的影响,以发现复杂系统的重要参数和结构.然而对于动态贝叶斯网络,当前还没有一种有效的灵敏性分析算法.针对隐马尔科夫模型(HMM)灵敏性分方法不能用于分析动态贝叶斯网络灵敏性和灵敏性分析计算复杂性高的问题,提出一种可有效处理动态贝叶斯网络灵敏性分析算法(SA_FF).SA_FF算法利用FF近似推理算法(Factored Frontier)思想求解动态贝叶斯网络的灵敏性函数,通过对马尔可夫毯所构成边界(Frontier)的动态推理建立参数与目标结点条件概率分布之间的函数关系;SA_FF算法在灵敏性函数推理计算过程中,通过对局部性边界的边缘化进行信息传播,不需要对模型的联合概率分布进行更新,显著提高了计算的效率,且可用于多参数灵敏性分析,但会引入一定的误差;进而,通过误差分析证明所引入的误差是有界的.最后,通过实例计算的比较和分析显示SA_FF算法的有效性.

Technical efficiency of hybrid maize growers: A stochastic frontier model approach

This study investigated the effect of credit constraints and credit unconstraints on the technical efficiency of hybrid maize growers in the Khyber Pakhtunkhwa Province(KPK) of Pakistan. The primary data were collected by a direct elicitation method from 510 maize growers of KPK Province. Stochastic frontier model techniques were used for technical efficiency analyses. The results revealed that the mean technical efficiency difference between the two groups was 10.2%. The results of technical inefficiency effect modeling demonstrated that education of the household head, family size, number of married family members, off-farm income, farming experience, tractor drill, water irrigation through a lined course, certified seed, extension services, household saving variables, and a credit size variable had positive effects on technical efficiency for both credit constrained farmers(CCFs) and credit unconstrained farmers(UCCFs). In addition, age of household head and fragmented land values had negative effects on technical efficiency for both groups. However, the interest rate had positive and negative impacts on the technical efficiency of CCFs and UCCFs, respectively. Our results have significant implications for policies related to land use, interest rate, and banking sector expansion in the rural areas of Pakistan.