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Intelligent Decision-Making in Warehouse Management: How AI Automation Improves Inventory Tracking, Order Fulfillment, and Logistics Efficiency Compared to Drone Technology
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作者 Somil Nishar 《Intelligent Control and Automation》 2024年第1期1-8,共8页
This paper analyzes how artificial intelligence (AI) automation can improve warehouse management compared to emerging technologies like drone usage. Specifically, we evaluate AI’s impact on crucial warehouse function... This paper analyzes how artificial intelligence (AI) automation can improve warehouse management compared to emerging technologies like drone usage. Specifically, we evaluate AI’s impact on crucial warehouse functions—inventory tracking, order fulfillment, and logistics efficiency. Our findings indicate AI automation enables real-time inventory visibility, optimized picking routes, and dynamic delivery scheduling, which drones cannot match. AI better leverages data insights for intelligent decision-making across warehouse operations, supporting improved productivity and lower operating costs. 展开更多
关键词 Warehouse Management Artificial Intelligence AUTOMATION Inventory Management order Fulfillment
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基于Ordered Probit模型的人车冲突安全影响因素研究
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作者 裴玉龙 杜小敏 沈威宇 《中国安全生产科学技术》 CAS CSCD 北大核心 2024年第3期181-187,共7页
为探究和定量分析人车冲突严重程度的影响因素,通过采集3个信号交叉口的人车冲突视频数据,利用T-Analyst标定人车轨迹并计算冲突指标(PET),采用85%位累计频率曲线法划分人车冲突等级;从人、车、路及环境特征中选取10个因素作为变量,构建... 为探究和定量分析人车冲突严重程度的影响因素,通过采集3个信号交叉口的人车冲突视频数据,利用T-Analyst标定人车轨迹并计算冲突指标(PET),采用85%位累计频率曲线法划分人车冲突等级;从人、车、路及环境特征中选取10个因素作为变量,构建Ordered Probit模型,以确立人车冲突严重程度的显著影响因素,并通过边际效应定量分析不同显著因素的影响程度。研究结果表明:行人闯红灯情况、年龄、行人交通量、人行道占用情况、人行道起点终点、车辆速度变化及车流量是人车冲突严重程度的显著因素,相较于各自参考量,行人闯红灯、车辆加速通过冲突点、人行道起点及老年人造成严重冲突的概率分别增加8.2%,5.9%,5.1%,4.4%;相较于低流量的交通流,较高流量的车流和行人交通流使得严重冲突的概率分别增加3.7%,2.5%,但人行道占用使得严重冲突的概率下降6.8%。研究结果可为信号交叉口行人过街交通安全设施的设计和实施提供理论依据。 展开更多
关键词 信号交叉口 行人安全 人车冲突严重度 ordered Probit模型 边际效应
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基于Ordered Logit模型的民办高校科研成果转化影响因素研究
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作者 张二丽 黄静 +1 位作者 王倩 陈彬彬 《河南财政金融学院学报(自然科学版)》 2024年第2期35-41,共7页
为研究民办高校科研成果转化影响因素,在专家访谈和实地调研的基础上,对K高校、C高校、B高校、Z高校等民办高校教师发放调查问卷收集数据,应用Ordered Logit模型对其影响因素进行了实证分析。分析发现,科研经费支持力度与科研成果数量... 为研究民办高校科研成果转化影响因素,在专家访谈和实地调研的基础上,对K高校、C高校、B高校、Z高校等民办高校教师发放调查问卷收集数据,应用Ordered Logit模型对其影响因素进行了实证分析。分析发现,科研经费支持力度与科研成果数量之间呈正相关关系,高校科研平台设置与服务地方经济建设之间呈正相关关系,高校科研管理制度与科研成果转化成效之间呈正相关关系。由此得出结论:我国民办高校科研成果转化与服务地方经济能力有待提升,民办高校科研成果转化的金融支持不够灵活、公共服务平台不够健全,完善民办高校科研管理制度是提高科研成果转化效率的重要保障。 展开更多
关键词 民办高校 科研成果 转化 ordered Logit模型
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Evolutionary Decision-Making and Planning for Autonomous Driving Based on Safe and Rational Exploration and Exploitation 被引量:2
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作者 Kang Yuan Yanjun Huang +4 位作者 Shuo Yang Zewei Zhou Yulei Wang Dongpu Cao Hong Chen 《Engineering》 SCIE EI CAS CSCD 2024年第2期108-120,共13页
Decision-making and motion planning are extremely important in autonomous driving to ensure safe driving in a real-world environment.This study proposes an online evolutionary decision-making and motion planning frame... Decision-making and motion planning are extremely important in autonomous driving to ensure safe driving in a real-world environment.This study proposes an online evolutionary decision-making and motion planning framework for autonomous driving based on a hybrid data-and model-driven method.First,a data-driven decision-making module based on deep reinforcement learning(DRL)is developed to pursue a rational driving performance as much as possible.Then,model predictive control(MPC)is employed to execute both longitudinal and lateral motion planning tasks.Multiple constraints are defined according to the vehicle’s physical limit to meet the driving task requirements.Finally,two principles of safety and rationality for the self-evolution of autonomous driving are proposed.A motion envelope is established and embedded into a rational exploration and exploitation scheme,which filters out unreasonable experiences by masking unsafe actions so as to collect high-quality training data for the DRL agent.Experiments with a high-fidelity vehicle model and MATLAB/Simulink co-simulation environment are conducted,and the results show that the proposed online-evolution framework is able to generate safer,more rational,and more efficient driving action in a real-world environment. 展开更多
关键词 Autonomous driving decision-making Motion planning Deep reinforcement learning Model predictive control
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Stable immobilization of lithium polysulfides using three-dimensional ordered mesoporous Mn_(2)O_(3) as the host material in lithium-sulfur batteries 被引量:1
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作者 Sung Joon Park Yun Jeong Choi +6 位作者 Hyun-seung Kim Min Joo Hong Hongjun Chang Janghyuk Moon Young-Jun Kim Junyoung Mun Ki Jae Kim 《Carbon Energy》 SCIE EI CAS CSCD 2024年第6期99-112,共14页
Lithium-sulfur batteries(LSBs)have drawn significant attention owing to their high theoretical discharge capacity and energy density.However,the dissolution of long-chain polysulfides into the electrolyte during the c... Lithium-sulfur batteries(LSBs)have drawn significant attention owing to their high theoretical discharge capacity and energy density.However,the dissolution of long-chain polysulfides into the electrolyte during the charge and discharge process(“shuttle effect”)results in fast capacity fading and inferior electrochemical performance.In this study,Mn_(2)O_(3)with an ordered mesoporous structure(OM-Mn_(2)O_(3))was designed as a cathode host for LSBs via KIT-6 hard templating,to effectively inhibit the polysulfide shuttle effect.OM-Mn_(2)O_(3)offers numerous pores to confine sulfur and tightly anchor the dissolved polysulfides through the combined effects of strong polar-polar interactions,polysulfides,and sulfur chain catenation.The OM-Mn_(2)O_(3)/S composite electrode delivered a discharge capacity of 561 mAh g^(-1) after 250 cycles at 0.5 C owing to the excellent performance of OM-Mn_(2)O_(3).Furthermore,it retained a discharge capacity of 628mA h g^(-1) even at a rate of 2 C,which was significantly higher than that of a pristine sulfur electrode(206mA h g^(-1)).These findings provide a prospective strategy for designing cathode materials for high-performance LSBs. 展开更多
关键词 host material lithium-sulfur battery ordered mesoporous structure shuttle effect transition-metal oxides
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Transformation of long-period stacking ordered structures in Mg-Gd-Y-Zn alloys upon synergistic characterization of first-principles calculation and experiment and its effects on mechanical properties 被引量:1
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作者 Mingyu Li Guangzong Zhang +4 位作者 Siqi Yin Changfeng Wang Ying Fu Chenyang Gu Renguo Guan 《Journal of Magnesium and Alloys》 SCIE EI CAS CSCD 2024年第5期1867-1879,共13页
Based on experiments and first-principles calculations,the microstructures and mechanical properties of as-cast and solution treated Mg-10Gd-4Y-xZn-0.6Zr(x=0,1,2,wt.%)alloys are investigated.The transformation process... Based on experiments and first-principles calculations,the microstructures and mechanical properties of as-cast and solution treated Mg-10Gd-4Y-xZn-0.6Zr(x=0,1,2,wt.%)alloys are investigated.The transformation process of long-period stacking ordered(LPSO)structure during solidification and heat treatment and its effect on the mechanical properties of experimental alloys are discussed.Results reveal that the stacking faults and 18R LPSO phases appear in the as-cast Mg-10Gd-4Y-1Zn-0.6Zr and Mg-10Gd-4Y-2Zn-0.6Zr alloys,respectively.After solution treatment,the stacking faults and 18R LPSO phase transform into 14H LPSO phase.The Enthalpies of formation and reaction energy of 14H and 18R LPSO are calculated based on first-principles.Results show that the alloying ability of 18R is stronger than that of 14H.The reaction energies show that the 14H LPSO phase is more stable than the 18R LPSO.The elastic properties of the 14H and 18R LPSO phases are also evaluated by first-principles calculations,and the results are in good agreement with the experimental results.The precipitation of LPSO phase improves the tensile strength,yield strength and elongation of the alloy.After solution treatment,the Mg-10Gd-4Y-2Zn-0.6Zr alloy has the best mechanical properties,and its ultimate tensile strength and yield strength are 278.7 MPa and 196.4 MPa,respectively.The elongation of Mg-10Gd-4Y-2Zn-0.6Zr reaches 15.1,which is higher than that of Mg-10Gd-4Y0.6Zr alloy.The improving mechanism of elastic modulus by the LPSO phases and the influence on the alloy mechanical properties are also analyzed. 展开更多
关键词 Mg-Gd-Y-Zn alloys Long-period stacking ordered First-principles calculations ENTHALPIES Mechanical properties
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Enhanced activation of peroxymonosulfate by Fe/N co-doped ordered mesoporous carbon with dual active sites for efficient removal of m-cresol 被引量:1
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作者 Donghui Li Wenzhe Wu +6 位作者 Xue Ren Xixi Zhao Hongbing Song Meng Xiao Quanhong Zhu Hengjun Gai Tingting Huang 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2024年第1期130-144,共15页
The novel Fe-N co-doped ordered mesoporous carbon with high catalytic activity in m-cresol removal was prepared by urea-assisted impregnation and simple pyrolysis method.During the preparation of the Fe-NC catalyst,th... The novel Fe-N co-doped ordered mesoporous carbon with high catalytic activity in m-cresol removal was prepared by urea-assisted impregnation and simple pyrolysis method.During the preparation of the Fe-NC catalyst,the complexation of N elements in urea could anchor Fe,and the formation of C3N4during urea pyrolysis could also prevent migration and aggregation of Fe species,which jointly improve the dispersion and stability of Fe.The FeN4sites and highly dispersed Fe nanoparticles synergistically trigger the dual-site peroxymonosulfate (PMS) activation for highly efficient m-cresol degradation,while the ordered mesoporous structure of the catalyst could improve the mass transfer rate of the catalytic process,which together promote catalytic degradation of m-cresol by PMS activation.Reactive oxygen species (ROS) analytic experiments demonstrate that the system degrades m-cresol by free radical pathway mainly based on SO_(4)^(-)·and·OH,and partially based on·OH as the active components,and a possible PMS activation mechanism by 5Fe-50 for m-cresol degradation was proposed.This study can provide theoretical guidance for the preparation of efficient and stable catalysts for the degradation of organic pollutants by activated PMS. 展开更多
关键词 Degradation PEROXYMONOSULFATE Fe(II)/Fe(III)/FeN4 ordered mesopores carbon Catalyst Radical
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Toward Trustworthy Decision-Making for Autonomous Vehicles:A Robust Reinforcement Learning Approach with Safety Guarantees
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作者 Xiangkun He Wenhui Huang Chen Lv 《Engineering》 SCIE EI CAS CSCD 2024年第2期77-89,共13页
While autonomous vehicles are vital components of intelligent transportation systems,ensuring the trustworthiness of decision-making remains a substantial challenge in realizing autonomous driving.Therefore,we present... While autonomous vehicles are vital components of intelligent transportation systems,ensuring the trustworthiness of decision-making remains a substantial challenge in realizing autonomous driving.Therefore,we present a novel robust reinforcement learning approach with safety guarantees to attain trustworthy decision-making for autonomous vehicles.The proposed technique ensures decision trustworthiness in terms of policy robustness and collision safety.Specifically,an adversary model is learned online to simulate the worst-case uncertainty by approximating the optimal adversarial perturbations on the observed states and environmental dynamics.In addition,an adversarial robust actor-critic algorithm is developed to enable the agent to learn robust policies against perturbations in observations and dynamics.Moreover,we devise a safety mask to guarantee the collision safety of the autonomous driving agent during both the training and testing processes using an interpretable knowledge model known as the Responsibility-Sensitive Safety Model.Finally,the proposed approach is evaluated through both simulations and experiments.These results indicate that the autonomous driving agent can make trustworthy decisions and drastically reduce the number of collisions through robust safety policies. 展开更多
关键词 Autonomous vehicle decision-making Reinforcement learning Adversarial attack Safety guarantee
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Orientation and Decision-Making for Soccer Based on Sports Analytics and AI:A Systematic Review
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作者 Zhiqiang Pu Yi Pan +4 位作者 Shijie Wang Boyin Liu Min Chen Hao Ma Yixiong Cui 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2024年第1期37-57,共21页
Due to ever-growing soccer data collection approaches and progressing artificial intelligence(AI) methods, soccer analysis, evaluation, and decision-making have received increasing interest from not only the professio... Due to ever-growing soccer data collection approaches and progressing artificial intelligence(AI) methods, soccer analysis, evaluation, and decision-making have received increasing interest from not only the professional sports analytics realm but also the academic AI research community. AI brings gamechanging approaches for soccer analytics where soccer has been a typical benchmark for AI research. The combination has been an emerging topic. In this paper, soccer match analytics are taken as a complete observation-orientation-decision-action(OODA) loop.In addition, as in AI frameworks such as that for reinforcement learning, interacting with a virtual environment enables an evolving model. Therefore, both soccer analytics in the real world and virtual domains are discussed. With the intersection of the OODA loop and the real-virtual domains, available soccer data, including event and tracking data, and diverse orientation and decisionmaking models for both real-world and virtual soccer matches are comprehensively reviewed. Finally, some promising directions in this interdisciplinary area are pointed out. It is claimed that paradigms for both professional sports analytics and AI research could be combined. Moreover, it is quite promising to bridge the gap between the real and virtual domains for soccer match analysis and decision-making. 展开更多
关键词 Artificial intelligence(AI) decision-making FOOTBALL review SOCCER sports analytics
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Lottery Numbers and Ordered Statistics
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作者 Kung-Kuen Tse 《Applied Mathematics》 2024年第4期287-291,共5页
The lottery has long captivated the imagination of players worldwide, offering the tantalizing possibility of life-changing wins. While winning the lottery is largely a matter of chance, as lottery drawings are typica... The lottery has long captivated the imagination of players worldwide, offering the tantalizing possibility of life-changing wins. While winning the lottery is largely a matter of chance, as lottery drawings are typically random and unpredictable. Some people use the lottery terminal randomly generates numbers for them, some players choose numbers that hold personal significance to them, such as birthdays, anniversaries, or other important dates, some enthusiasts have turned to statistical analysis as a means to analyze past winning numbers identify patterns or frequencies. In this paper, we use order statistics to estimate the probability of specific order of numbers or number combinations being drawn in future drawings. 展开更多
关键词 LOTTERY order Statistics Hypergeometric Distribution EXPECTATION UNIFORM
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Ethical Decision-Making Framework Based on Incremental ILP Considering Conflicts
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作者 Xuemin Wang Qiaochen Li Xuguang Bao 《Computers, Materials & Continua》 SCIE EI 2024年第3期3619-3643,共25页
Humans are experiencing the inclusion of artificial agents in their lives,such as unmanned vehicles,service robots,voice assistants,and intelligent medical care.If the artificial agents cannot align with social values... Humans are experiencing the inclusion of artificial agents in their lives,such as unmanned vehicles,service robots,voice assistants,and intelligent medical care.If the artificial agents cannot align with social values or make ethical decisions,they may not meet the expectations of humans.Traditionally,an ethical decision-making framework is constructed by rule-based or statistical approaches.In this paper,we propose an ethical decision-making framework based on incremental ILP(Inductive Logic Programming),which can overcome the brittleness of rule-based approaches and little interpretability of statistical approaches.As the current incremental ILP makes it difficult to solve conflicts,we propose a novel ethical decision-making framework considering conflicts in this paper,which adopts our proposed incremental ILP system.The framework consists of two processes:the learning process and the deduction process.The first process records bottom clauses with their score functions and learns rules guided by the entailment and the score function.The second process obtains an ethical decision based on the rules.In an ethical scenario about chatbots for teenagers’mental health,we verify that our framework can learn ethical rules and make ethical decisions.Besides,we extract incremental ILP from the framework and compare it with the state-of-the-art ILP systems based on ASP(Answer Set Programming)focusing on conflict resolution.The results of comparisons show that our proposed system can generate better-quality rules than most other systems. 展开更多
关键词 Ethical decision-making inductive logic programming incremental learning conflicts
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Offline Reinforcement Learning with Constrained Hybrid Action Implicit Representation Towards Wargaming Decision-Making
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作者 Liwei Dong Ni Li +1 位作者 Guanghong Gong Xin Lin 《Tsinghua Science and Technology》 SCIE EI CAS CSCD 2024年第5期1422-1440,共19页
Reinforcement Learning(RL)has emerged as a promising data-driven solution for wargaming decision-making.However,two domain challenges still exist:(1)dealing with discrete-continuous hybrid wargaming control and(2)acce... Reinforcement Learning(RL)has emerged as a promising data-driven solution for wargaming decision-making.However,two domain challenges still exist:(1)dealing with discrete-continuous hybrid wargaming control and(2)accelerating RL deployment with rich offline data.Existing RL methods fail to handle these two issues simultaneously,thereby we propose a novel offline RL method targeting hybrid action space.A new constrained action representation technique is developed to build a bidirectional mapping between the original hybrid action space and a latent space in a semantically consistent way.This allows learning a continuous latent policy with offline RL with better exploration feasibility and scalability and reconstructing it back to a needed hybrid policy.Critically,a novel offline RL optimization objective with adaptively adjusted constraints is designed to balance the alleviation and generalization of out-of-distribution actions.Our method demonstrates superior performance and generality across different tasks,particularly in typical realistic wargaming scenarios. 展开更多
关键词 offline Reinforcement Learning(RL) WARGAMING decision-making hybrid action space
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Stroke Risk Assessment Decision-Making Using a Machine Learning Model:Logistic-AdaBoost
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作者 Congjun Rao Mengxi Li +1 位作者 Tingting Huang Feiyu Li 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第4期699-724,共26页
Stroke is a chronic cerebrovascular disease that carries a high risk.Stroke risk assessment is of great significance in preventing,reversing and reducing the spread and the health hazards caused by stroke.Aiming to ob... Stroke is a chronic cerebrovascular disease that carries a high risk.Stroke risk assessment is of great significance in preventing,reversing and reducing the spread and the health hazards caused by stroke.Aiming to objectively predict and identify strokes,this paper proposes a new stroke risk assessment decision-making model named Logistic-AdaBoost(Logistic-AB)based on machine learning.First,the categorical boosting(CatBoost)method is used to perform feature selection for all features of stroke,and 8 main features are selected to form a new index evaluation system to predict the risk of stroke.Second,the borderline synthetic minority oversampling technique(SMOTE)algorithm is applied to transform the unbalanced stroke dataset into a balanced dataset.Finally,the stroke risk assessment decision-makingmodel Logistic-AB is constructed,and the overall prediction performance of this new model is evaluated by comparing it with ten other similar models.The comparison results show that the new model proposed in this paper performs better than the two single algorithms(logistic regression and AdaBoost)on the four indicators of recall,precision,F1 score,and accuracy,and the overall performance of the proposed model is better than that of common machine learning algorithms.The Logistic-AB model presented in this paper can more accurately predict patients’stroke risk. 展开更多
关键词 STROKE risk assessment decision-making CatBoost feature selection borderline SMOTE Logistic-AB
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Research on Maneuver Decision-Making of Multi-Agent Adversarial Game in a Random Interference Environment
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作者 Shiguang Hu Le Ru +4 位作者 Bo Lu Zhenhua Wang Xiaolin Zhao Wenfei Wang Hailong Xi 《Computers, Materials & Continua》 SCIE EI 2024年第10期1879-1903,共25页
The strategy evolution process of game players is highly uncertain due to random emergent situations and other external disturbances.This paper investigates the issue of strategy interaction and behavioral decision-ma... The strategy evolution process of game players is highly uncertain due to random emergent situations and other external disturbances.This paper investigates the issue of strategy interaction and behavioral decision-making among game players in simulated confrontation scenarios within a random interference environment.It considers the possible risks that random disturbances may pose to the autonomous decision-making of game players,as well as the impact of participants’manipulative behaviors on the state changes of the players.A nonlinear mathematical model is established to describe the strategy decision-making process of the participants in this scenario.Subsequently,the strategy selection interaction relationship,strategy evolution stability,and dynamic decision-making process of the game players are investigated and verified by simulation experiments.The results show that maneuver-related parameters and random environmental interference factors have different effects on the selection and evolutionary speed of the agent’s strategies.Especially in a highly uncertain environment,even small information asymmetry or miscalculation may have a significant impact on decision-making.This also confirms the feasibility and effectiveness of the method proposed in the paper,which can better explain the behavioral decision-making process of the agent in the interaction process.This study provides feasibility analysis ideas and theoretical references for improving multi-agent interactive decision-making and the interpretability of the game system model. 展开更多
关键词 Behavior decision-making stochastic evolutionary game nonlinear mathematical modeling MULTI-AGENT MANEUVER
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Determination of the best materials for development and designing product using a multi-criteria decision-making
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作者 Rabia Hassan Zeeshan Ahmad Arfeen +2 位作者 Mehreen Kausar Azam Zain ul Abiden Akhtar Abubakar Siddique 《Railway Sciences》 2024年第5期541-557,共17页
Purpose–Material selection,driven by wide and often conflicting objectives,is an important,sometimes difficult problem in material engineering.In this context,multi-criteria decision-making(MCDM)methodologies are eff... Purpose–Material selection,driven by wide and often conflicting objectives,is an important,sometimes difficult problem in material engineering.In this context,multi-criteria decision-making(MCDM)methodologies are effective.An approach of MCDM is needed to cater to criteria of material assortment simultaneously.More firms are now concerned about increasing their productivity using mathematical tools.To occupy a gap in the previous literature this research recommends an integrated MCDM and mathematical Bi-objective model for the selection of material.In addition,by using the Technique for Order Preference by Similarity to Ideal Solution(TOPSIS),the inherent ambiguities of decision-makers in paired evaluations are considered in this research.It goes on to construct a mathematical bi-objective model for determining the best item to purchase.Design/methodology/approach–The entropy perspective is implemented in this paper to evaluate the weight parameters,while the TOPSIS technique is used to determine the best and worst intermediate pipe materials for automotive exhaust system.The intermediate pipes are used to join the components of the exhaust systems.The materials usually used to manufacture intermediate pipe are SUS 436LM,SUS 430,SUS 304,SUS 436L,SUH 409 L,SUS 441 L and SUS 439L.These seven materials are evaluated based on tensile strength(TS),hardness(H),elongation(E),yield strength(YS)and cost(C).A hybrid methodology combining entropy-based criteria weighting,with the TOPSIS for alternative ranking,is pursued to identify the optimal design material for an engineered application in this paper.This study aims to help while filling the information gap in selecting the most suitable material for use in the exhaust intermediate pipes.After that,the authors searched for and considered eight materials and evaluated them on the following five criteria:(1)TS,(2)YS,(3)H,(4)E and(5)C.The first two criteria have been chosen because they can have a lot of influence on the behavior of the exhaust intermediate pipes,on their performance and on the cost.In this structure,the weights of the criteria are calculated objectively through the entropy method in order to have an unbiased assessment.This essentially measures the quantity of information each criterion contribution,indicating the relative importance of these criteria better.Subsequently,the materials were ranked using the TOPSIS method in terms of their relative performance by measuring each material from an ideal solution to determine the best alternative.The results show that SUS 309,SUS 432L and SUS 436 LM are the first three materials that the exhaust intermediate pipe optimal design should consider.Findings–The material matrix of the decision presented in Table 3 was normalized through Equation 5,as shown in Table 5,and the matrix was multiplied with weighting criteriaß_j.The obtained weighted normalized matrix V_ij is presented in Table 6.However,the ideal,worst and best value was ascertained by employing Equation 7.This study is based on the selection of material for the development of intermediate pipe using MCDM,and it involves four basic stages,i.e.method of translation criteria,screening process,method of ranking and search for methods.The selection was done through the TOPSIS method,and the criteria weight was obtained by the entropy method.The result showed that the top three materials are SUS 309,SUS 432L and SUS 436 LM,respectively.For the future work,it is suggested to select more alternatives and criteria.The comparison can also be done by using different MCDM techniques like and Choice Expressing Reality(ELECTRE),Decision-Making Trial and Evaluation Laboratory(DEMATEL)and Preference Ranking Organization Method for Enrichment Evaluation(PROMETHEE).Originality/value–The results provide important conclusions for material selection in this targeted application,verifying the employment of mutual entropy-TOPSIS methodology for a series of difficult engineering decisions in material engineering concepts that combine superior capacity with better performance as well as cost-efficiency in various engineering design. 展开更多
关键词 TOPSIS Multi-criteria decision-making Entropy method Material selection
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The Spherical q-Linear Diophantine Fuzzy Multiple-Criteria Group Decision-Making Based on Differential Measure
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作者 Huzaira Razzaque Shahzaib Ashraf +1 位作者 Muhammad Naeem Yu-Ming Chu 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第2期1925-1950,共26页
Spherical q-linearDiophantine fuzzy sets(Sq-LDFSs)provedmore effective for handling uncertainty and vagueness in multi-criteria decision-making(MADM).It does not only cover the data in two variable parameters but is a... Spherical q-linearDiophantine fuzzy sets(Sq-LDFSs)provedmore effective for handling uncertainty and vagueness in multi-criteria decision-making(MADM).It does not only cover the data in two variable parameters but is also beneficial for three parametric data.By Pythagorean fuzzy sets,the difference is calculated only between two parameters(membership and non-membership).According to human thoughts,fuzzy data can be found in three parameters(membership uncertainty,and non-membership).So,to make a compromise decision,comparing Sq-LDFSs is essential.Existing measures of different fuzzy sets do,however,can have several flaws that can lead to counterintuitive results.For instance,they treat any increase or decrease in the membership degree as the same as the non-membership degree because the uncertainty does not change,even though each parameter has a different implication.In the Sq-LDFSs comparison,this research develops the differentialmeasure(DFM).Themain goal of the DFM is to cover the unfair arguments that come from treating different types of FSs opposing criteria equally.Due to their relative positions in the attribute space and the similarity of their membership and non-membership degrees,two Sq-LDFSs formthis preference connectionwhen the uncertainty remains same in both sets.According to the degree of superiority or inferiority,two Sq-LDFSs are shown as identical,equivalent,superior,or inferior over one another.The suggested DFM’s fundamental characteristics are provided.Based on the newly developed DFM,a unique approach tomultiple criterion group decision-making is offered.Our suggestedmethod verifies the novel way of calculating the expert weights for Sq-LDFSS as in PFSs.Our proposed technique in three parameters is applied to evaluate solid-state drives and choose the optimum photovoltaic cell in two applications by taking uncertainty parameter zero.The method’s applicability and validity shown by the findings are contrasted with those obtained using various other existing approaches.To assess its stability and usefulness,a sensitivity analysis is done. 展开更多
关键词 Multi-criteria group decision-making spherical q-linear Diophantine fuzzy sets differencemeasures photovoltaic cells medical diagnosis
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A NovelMethod for Determining Tourism Carrying Capacity in a Decision-Making Context Using q−Rung Orthopair Fuzzy Hypersoft Environment
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作者 Salma Khan Muhammad Gulistan +2 位作者 NasreenKausar Seifedine Kadry Jungeun Kim 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第2期1951-1979,共29页
Tourism is a popular activity that allows individuals to escape their daily routines and explore new destinations for various reasons,including leisure,pleasure,or business.A recent study has proposed a unique mathema... Tourism is a popular activity that allows individuals to escape their daily routines and explore new destinations for various reasons,including leisure,pleasure,or business.A recent study has proposed a unique mathematical concept called a q−Rung orthopair fuzzy hypersoft set(q−ROFHS)to enhance the formal representation of human thought processes and evaluate tourism carrying capacity.This approach can capture the imprecision and ambiguity often present in human perception.With the advanced mathematical tools in this field,the study has also incorporated the Einstein aggregation operator and score function into the q−ROFHS values to supportmultiattribute decision-making algorithms.By implementing this technique,effective plans can be developed for social and economic development while avoiding detrimental effects such as overcrowding or environmental damage caused by tourism.A case study of selected tourism carrying capacity will demonstrate the proposed methodology. 展开更多
关键词 q−Rung orthopair fuzzy hypersoft set decision-making tourism carrying capacity aggregation operator
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The Disintegration of a Floating Ferrofluid Layer into an Ordered Drop System in a Vertical Magnetic Field
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作者 Christina Khokhryakova Konstantin Kostarev Irina Mizeva 《Fluid Dynamics & Materials Processing》 EI 2024年第10期2205-2218,共14页
Magnetic fluids,also known as ferrofluids,are versatile functional materials with a wide range of applications.These applications span from industrial uses such as vacuum seals,actuators,and acoustic devices to medica... Magnetic fluids,also known as ferrofluids,are versatile functional materials with a wide range of applications.These applications span from industrial uses such as vacuum seals,actuators,and acoustic devices to medical uses,including serving as contrast agents for magnetic resonance imaging(MRI),delivering medications to specific locations within the body,and magnetic hyperthermia for cancer treatment.The use of a non-wettable immiscible liquid substrate to support a layer of magnetic fluid opens up new possibilities for studying various fluid flows and related instabilities in multi-phase systems with both a free surface and an interface.The presence of two deformable boundaries within a ferrofluid layer significantly reduces the critical magnetic field strength required to transform the layer into an organized system of drops or polygonal figures evolving according to the intensity,frequency and direction of the considered magnetic field.This paper experimentally investigates this problem by assuming a uniform magnetic field perpendicular to the surface.This specific subject has not been previously explored experimentally.The critical magnetic field intensity required to destabilize the ferrofluid layer is determined based on the layer’s thickness and the fluid’s initial magnetic susceptibility.It is demonstrated that the critical magnetic field strength needed to disrupt the initially continuous ferrofluid layer increases with the layer’s thickness.Conversely,an increase in the ferrofluid’s magnetic susceptibility results in a decrease in the critical magnetic field strength.The emerging droplet structures are analyzed in terms of the number of drops,their size,and the periodicity of their arrangement.The number of droplets formed depends on the initial thickness of the layer,the presence or absence of a stable rupture in the upper layer,and the rate at which the magnetic field strength is increased to the critical value.A characteristic viscous time is proposed to evaluate the decomposition of the ferrofluid layer,which depends on the duration of the magnetic field’s application.The experimental data on the instability of a ferrofluid layer on a liquid substrate are compared with the theoretical results from the study of“magnetic fluid sandwich structures”conducted by Rannacher and Engel.This comparison highlights the similarities and differences between experimental observations and theoretical predictions,providing a deeper understanding of the behavior of ferrofluid layers under the influence of magnetic fields. 展开更多
关键词 FERROFLUID liquid substrate normal field instability ordered droplet structure
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Ordered mesoporous materials for water pollution treatment:Adsorption and catalysis
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作者 Peng Zhang Mingming He +4 位作者 Wei Teng Fukuan Li Xinyuan Qiu Kexun Li Hao Wang 《Green Energy & Environment》 SCIE EI CAS CSCD 2024年第8期1239-1256,共18页
To meet the growing emission of water contaminants,the development of new materials that enhance the efficiency of the water treatment system is urgent.Ordered mesoporous materials provide opportunities in environment... To meet the growing emission of water contaminants,the development of new materials that enhance the efficiency of the water treatment system is urgent.Ordered mesoporous materials provide opportunities in environmental processing applications due to their exceptionally high surface areas,large pore sizes,and enough pore volumes.These properties might enhance the performance of materials concerning adsorption/catalysis capability,durability,and stability.In this review,we enumerate the ordered mesoporous materials as adsorbents/catalysts and their modifications in water pollution treatment from the past decade,including heavy metals(Hg^(2+),Pb^(2+),Cd^(2+),Cr^(6+),etc.),toxic anions(nitrate,phosphate,fluoride,etc.),and organic contaminants(organic dyes,antibiotics,etc.).These contributions demonstrate a deep understanding of the synergistic effect between the incorporated framework and homogeneous active centers.Besides,the challenges and perspectives of the future developments of ordered mesoporous materials in wastewater treatment are proposed.This work provides a theoretical basis and complete summary for the application of ordered mesoporous materials in the removal of contaminants from aqueous solutions. 展开更多
关键词 Water pollution treatment ordered mesoporous materials Toxic contaminants ADSORPTION CATALYSIS
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UAV maneuvering decision-making algorithm based on deep reinforcement learning under the guidance of expert experience
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作者 ZHAN Guang ZHANG Kun +1 位作者 LI Ke PIAO Haiyin 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2024年第3期644-665,共22页
Autonomous umanned aerial vehicle(UAV) manipulation is necessary for the defense department to execute tactical missions given by commanders in the future unmanned battlefield. A large amount of research has been devo... Autonomous umanned aerial vehicle(UAV) manipulation is necessary for the defense department to execute tactical missions given by commanders in the future unmanned battlefield. A large amount of research has been devoted to improving the autonomous decision-making ability of UAV in an interactive environment, where finding the optimal maneuvering decisionmaking policy became one of the key issues for enabling the intelligence of UAV. In this paper, we propose a maneuvering decision-making algorithm for autonomous air-delivery based on deep reinforcement learning under the guidance of expert experience. Specifically, we refine the guidance towards area and guidance towards specific point tasks for the air-delivery process based on the traditional air-to-surface fire control methods.Moreover, we construct the UAV maneuvering decision-making model based on Markov decision processes(MDPs). Specifically, we present a reward shaping method for the guidance towards area and guidance towards specific point tasks using potential-based function and expert-guided advice. The proposed algorithm could accelerate the convergence of the maneuvering decision-making policy and increase the stability of the policy in terms of the output during the later stage of training process. The effectiveness of the proposed maneuvering decision-making policy is illustrated by the curves of training parameters and extensive experimental results for testing the trained policy. 展开更多
关键词 unmanned aerial vehicle(UAV) maneuvering decision-making autonomous air-delivery deep reinforcement learning reward shaping expert experience
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