基于TOPSIS-Shapley值法的梯级水电站补偿效益分摊研究

针对流域内联合电站数目众多但利益分配存在纠纷的情况,旨在提出一种更为合理的梯级电站利益分配方法。基于Shapley值法和TOPSIS法,综合考虑电站贡献及电站对不同客观分摊方法的相对满意程度,建立TOPSIS-Shapley值法梯级电站补偿效益分摊模型,同时为解决Shapley值法在求解多利益主体梯级电站联合调度增益分配问题中的局限性,引入聚合降维思想。模型思路如下:将上游电站联合调度前后梯级发电效益的增量作为补偿效益,首先采取四种不同的客观分摊方法对电站特性参数指标进行计算,构成TOPSIS的基础决策矩阵,利用TOPSIS原理得出电站对各个分摊方法的相对满意度,同时采用联盟博弈理论,计算电站所有可能联盟方式下的发电效益,得到基于Shapley值的补偿效益分摊结果,最后将TOPSIS原理得出的分摊系数与由Shapley值法所得的分摊系数结合形成综合分摊权重,应用于黑河上游的八级电站补偿效益分摊中。工程应用实例表明:该方法不仅考虑了联盟电站对整体的边际贡献和各电站的分摊满意程度,且兼顾了电站的特性指标差异,合理量化和分配了各电站间的发电补偿效益,分摊结果公平合理、易被各方接受,可促进流域各级电站参与联合调度从而达到整体效益最大的目标,对于数量较多的梯级水电站补偿效益分配问题具有重要参考意义。

Shapley值及其应用

Shapley值是合作博弈理论中最重要的概念之一,其在经济学、社会管理等领域具有十分广泛的应用.本文回顾了合作博弈的Shapley值的理论研究,并从Shapley-Shubik权力指数、拼车费用分摊、图博弈的Page-Shapley值以及SHAP方法与机器学习等4个方面介绍了Shapley值的应用进展.

基于改进Shapley值法的风-光-水-储多主体互补发电系统合作增益分配策略

为了充分发挥系统中可调节资源的自身优势,利用变速抽水蓄能机组配合小水电机组进行常规调节,并考虑变速抽水蓄能机组的快速响应特性,提出了兼顾系统小时级以及秒级安全性的风-光-水-储多主体互补发电系统的联合优化调度模型。为了降低合作博弈高效性算法线性增长的计算复杂度,基于改进Shapely值法提出了一种大规模利益主体的合作增量效益(增益)分配策略。通过资源聚合,对高维度问题进行降维处理,利用Shapley值法进行初始分配;构建合作增益贡献指标,采用非对称纳什谈判理论对同类型的不同主体进行细化分配。以某流域风-光-水-储10主体互补发电系统为仿真算例,结果表明:抽水蓄能机组与小水电机组互补运行可以提升系统的灵活性和安全性;基于改进Shapley值法的合作增益分配策略具有计算高效性以及应用可行性。

一种改进Shapley值法的林浆纸供应链绿色收益分配研究

林浆纸产业作为关系国计民生的重要行业,在推进生态文明建设中肩负着重要使命。在梳理林浆纸供应链绿色收益分配必要性的基础上,分析了传统Shapley值法的局限,通过引入投入修正系数,构建了基于改进Shapley值法的收益分配模型,并结合案例进行求解,验证了改进方法的合理性和有效性。最后,从健全收益核算、完善利益协调机制、创新金融模式等方面,提出推动林浆纸供应链绿色收益合理分配的政策建议,以期为林浆纸产业高质量发展提供决策参考。

Investigation of feature contribution to shield tunneling-induced settlement using Shapley additive explanations method

Accurate prediction of shield tunneling-induced settlement is a complex problem that requires consideration of many influential parameters.Recent studies reveal that machine learning(ML)algorithms can predict the settlement caused by tunneling.However,well-performing ML models are usually less interpretable.Irrelevant input features decrease the performance and interpretability of an ML model.Nonetheless,feature selection,a critical step in the ML pipeline,is usually ignored in most studies that focused on predicting tunneling-induced settlement.This study applies four techniques,i.e.Pearson correlation method,sequential forward selection(SFS),sequential backward selection(SBS)and Boruta algorithm,to investigate the effect of feature selection on the model’s performance when predicting the tunneling-induced maximum surface settlement(S_(max)).The data set used in this study was compiled from two metro tunnel projects excavated in Hangzhou,China using earth pressure balance(EPB)shields and consists of 14 input features and a single output(i.e.S_(max)).The ML model that is trained on features selected from the Boruta algorithm demonstrates the best performance in both the training and testing phases.The relevant features chosen from the Boruta algorithm further indicate that tunneling-induced settlement is affected by parameters related to tunnel geometry,geological conditions and shield operation.The recently proposed Shapley additive explanations(SHAP)method explores how the input features contribute to the output of a complex ML model.It is observed that the larger settlements are induced during shield tunneling in silty clay.Moreover,the SHAP analysis reveals that the low magnitudes of face pressure at the top of the shield increase the model’s output。

Benefit allocation model of distributed photovoltaic power generation vehicle shed and energy storage charging pile based on integrated weighting-Shapley method

In this study,to develop a benefit-allocation model,in-depth analysis of a distributed photovoltaic-powergeneration carport and energy-storage charging-pile project was performed;the model was developed using Shapley integrated-empowerment benefit-distribution method.First,through literature survey and expert interview to identify the risk factors at various stages of the project,a dynamic risk-factor indicator system is developed.Second,to obtain a more meaningful risk-calculation result,the subjective and objective weights are combined,the weights of the risk factors at each stage are determined by the expert scoring method and entropy weight method,and the interest distribution model based on multi-dimensional risk factors is established.Finally,an example is used to verify the rationality of the method for the benefit distribution of the charging-pile project.The results of the example indicate that the limitations of the Shapley method can be reasonably avoided,and the applicability of the model for the benefit distribution of the charging-pile project is verified.

Euler’s First-Order Explicit Method–Peridynamic Differential Operator for Solving Population Balance Equations of the Crystallization Process

Using Euler’s first-order explicit(EE)method and the peridynamic differential operator(PDDO)to discretize the time and internal crystal-size derivatives,respectively,the Euler’s first-order explicit method–peridynamic differential operator(EE–PDDO)was obtained for solving the one-dimensional population balance equation in crystallization.Four different conditions during crystallization were studied:size-independent growth,sizedependent growth in a batch process,nucleation and size-independent growth,and nucleation and size-dependent growth in a continuous process.The high accuracy of the EE–PDDO method was confirmed by comparing it with the numerical results obtained using the second-order upwind and HR-van methods.The method is characterized by non-oscillation and high accuracy,especially in the discontinuous and sharp crystal size distribution.The stability of the EE–PDDO method,choice of weight function in the PDDO method,and optimal time step are also discussed.

Energy Stable Nodal DG Methods for Maxwell’s Equations of Mixed-Order Form in Nonlinear Optical Media

In this work,we develop energy stable numerical methods to simulate electromagnetic waves propagating in optical media where the media responses include the linear Lorentz dispersion,the instantaneous nonlinear cubic Kerr response,and the nonlinear delayed Raman molecular vibrational response.Unlike the first-order PDE-ODE governing equations considered previously in Bokil et al.(J Comput Phys 350:420–452,2017)and Lyu et al.(J Sci Comput 89:1–42,2021),a model of mixed-order form is adopted here that consists of the first-order PDE part for Maxwell’s equations coupled with the second-order ODE part(i.e.,the auxiliary differential equations)modeling the linear and nonlinear dispersion in the material.The main contribution is a new numerical strategy to treat the Kerr and Raman nonlinearities to achieve provable energy stability property within a second-order temporal discretization.A nodal discontinuous Galerkin(DG)method is further applied in space for efficiently handling nonlinear terms at the algebraic level,while preserving the energy stability and achieving high-order accuracy.Indeed with d_(E)as the number of the components of the electric field,only a d_(E)×d_(E)nonlinear algebraic system needs to be solved at each interpolation node,and more importantly,all these small nonlinear systems are completely decoupled over one time step,rendering very high parallel efficiency.We evaluate the proposed schemes by comparing them with the methods in Bokil et al.(2017)and Lyu et al.(2021)(implemented in nodal form)regarding the accuracy,computational efficiency,and energy stability,by a parallel scalability study,and also through the simulations of the soliton-like wave propagation in one dimension,as well as the spatial-soliton propagation and two-beam interactions modeled by the two-dimensional transverse electric(TE)mode of the equations.

The forecasting efficiency under different selected regions by Pattern Informatics Method and seismic potential estimation in the North-South Seismic Zone

In 2022,four earthquakes with M_(S)≥6.0 including the Menyuan M_(S)6.9 and Luding M_(S)6.8 earthquakes occurred in the North-South Seismic Zone(NSSZ),which demonstrated high and strong seismicity.Pattern Informatics(PI)method,as an effective long and medium term earthquake forecasting method,has been applied to the strong earthquake forecasting in Chinese mainland and results have shown the positive performance.The earthquake catalog with magnitude above M_(S)3.0 since 1970 provided by China Earthquake Networks Center was employed in this study and the Receiver Operating Characteristic(ROC)method was applied to test the forecasting efficiency of the PI method in each selected region related to the North-South Seismic Zone systematically.Based on this,we selected the area with the best ROC testing result and analyzed the evolution process of the PI hotspot map reflecting the small seismic activity pattern prior to the Menyuan M_(S)6.9 and Luding M_(S)6.8 earthquakes.A“forward”forecast for the area was carried out to assess seismic risk.The study shows the following.1)PI forecasting has higher forecasting efficiency in the selected study region where the difference of seismicity in any place of the region is smaller.2)In areas with smaller differences of seismicity,the activity pattern of small earthquakes prior to the Menyuan M_(S)6.9 and Luding M_(S)6.8 earthquakes can be obtained by analyzing the spatio-temporal evolution process of the PI hotspot map.3)The hotspot evolution in and around the southern Tazang fault in the study area is similar to that prior to the strong earthquakes,which suggests the possible seismic hazard in the future.This study could provide some ideas to the seismic hazard assessment in other regions with high seismicity,such as Japan,Californi,Turkey,and Indonesia.

Research on the Application of Montessori Education Method in Cognitive Training of Patients with Alzheimer’s Disease

Objective:To study the application of the Montessori education method in cognitive training in patients with Alzheimer’s disease(AD).Methods:40 cases of senile dementia patients who were admitted to our hospital from January 2022 to January 2023 were selected and randomly divided into an intervention group and a control group according to the single and double number table method,with 20 cases in each group.The intervention group used the Montessori education method,the principle of which was to implement individualized health interventions based on the individual conditions of the patients,for a period of 6 months;the control group was given conventional treatment and nursing of the disease.The Mini-Mental State Examination(MMSE)was used to compare the effects of the two groups of patients before and after health intervention and conduct statistical analysis.Results:The score of the intervention group was higher than that of the control group,and there was a statistical difference between the two(P<0.05).Conclusion:Implementing the Montessori education method for diagnosed Alzheimer’s patients can effectively improve their cognitive function and delay the progress of further dementia.

Solid Waste Management:A MADM Approach Using Fuzzy Parameterized Possibility Single-Valued Neutrosophic Hypersoft Expert Settings

The dramatic rise in the number of people living in cities has made many environmental and social problems worse.The search for a productive method for disposing of solid waste is the most notable of these problems.Many scholars have referred to it as a fuzzy multi-attribute or multi-criteria decision-making problem using various fuzzy set-like approaches because of the inclusion of criteria and anticipated ambiguity.The goal of the current study is to use an innovative methodology to address the expected uncertainties in the problem of solid waste site selection.The characteristics(or sub-attributes)that decision-makers select and the degree of approximation they accept for various options can both be indicators of these uncertainties.To tackle these problems,a novel mathematical structure known as the fuzzy parameterized possibility single valued neutrosophic hypersoft expert set(ρˆ-set),which is initially described,is integrated with a modified version of Sanchez’s method.Following this,an intelligent algorithm is suggested.The steps of the suggested algorithm are explained with an example that explains itself.The compatibility of solid waste management sites and systems is discussed,and rankings are established along with detailed justifications for their viability.This study’s strengths lie in its application of fuzzy parameterization and possibility grading to effectively handle the uncertainties embodied in the parameters’nature and alternative approximations,respectively.It uses specific mathematical formulations to compute the fuzzy parameterized degrees and possibility grades that are missing from the prior literature.It is simpler for the decisionmakers to look at each option separately because the decision is uncertain.Comparing the computed results,it is discovered that they are consistent and dependable because of their preferred properties.

Critical care nurses and their clinical reasoning for customizing monitor alarms:a mixed-method study

Objective:To explore the clinical rationale of critical care nurses for personalizing monitor alarms.One of the most crucial jobs assigned to critical care nurses is monitoring patients'physiological indicators and carrying out the necessary associated interventions.Successful use of equipment in the nursing practice environment will be improved by a thorough understanding of the nurse's approach to alarm configuration.Methods:A mixed-method design integrating quantitative and qualitative components was used.The sample of this study recruited a convenience sample of 60 nurses who have worked in critical care areas.This study took place at Lebanese American University Medical Center Rizk Hospital,utilizing a semi-structured interview with participants.Results:The study demonstrated the high incidence of nuisance alarms and the desensitization of critical care nurses to vital ones.According to the nurses,frequent false alarms and a shortage of staff are the 2 main causes of alarm desensitization.Age was significantly associated with the perception of Smart alarms,according to the data(P=0.03).Four interconnected themes and subcategories that reflect the clinical reasoning process for alarm customization were developed as a result of the study's qualitative component:(1)unit alarm environment;(2)nursing style;(3)motivation to customize;and(4)clinical and technological customization.Conclusions:According to this study,nurses believe that alarms are valuable.However,a qualitative analysis of the experiences revealed that customization has been severely limited since the healthcare team depends on nurses to complete these tasks independently.Additionally,a staffing shortage and lack of technical training at the start of placement have also hindered customization.

基于叠加定理和Aumann-Shapley法的发电权交易网损分摊

发电权交易使得电网的潮流以及损耗发生变化,对电网的运行成本产生影响,因此如何有效计及这种影响并对电网进行相应的补偿是亟待解决的问题。为解决此问题,首先针对断面网损进行研究,在断面下将输电网等效为线性电路,发电机和负荷等效为电流源,通过叠加原理确定各支路潮流及功率损耗与各电流源的关系式,进而确定发电权交易量与网损变化量的关系式。其次,将网损分摊看作一个合作博弈问题,即网损是由所有参与者共同合作的结果。应用Aumann-Shapley法对支路的互耦合功率损耗进行分摊,可保证结果公平合理,且具有经济一致性。最后,通过IEEE9节点标准算例进行仿真,验证了所提方法的正确性和有效性。

基于Shapley值法的动态联盟伙伴企业利益分配策略

动态联盟被认为是21世纪最有前途的企业组织模式,它增强了企业自身的竞争力,使企业能更好地应对市场的不确定性。然而作为一种崭新的组织形态,它仍有许多问题值得研究。利益分配就是其中之一。本文首先介绍了用于解决多人合作对策问题的Shapley值法,并将之应用于动态联盟伙伴企业的利益分配,然后分析了用Shapley值法进行动态联盟利益分配的成功与不足,最后针对其不足提出了一种基于风险因子的修正算法。

基于PCA-Shapley复合权重的盾构地铁施工安全管理模糊评价研究

提出了影响盾构法地铁施工安全的影响因素集合,并对集合中24个影响因素进行PCA降维处理,对得到的9个主成分进行整合重组,形成计划、技术、环境、组织监控4类安全管理评价指标,建立基于主成分分析的地铁施工安全管理评价指标体系,利用Shapley值基本原理计算基于非可加测度的各指标权重,并结合Fuzzy理论构建地铁施工安全管理评估模型,对某实际工程分析盾构法地铁施工安全管理效果,确定了影响盾构地铁施工安全的关键因素,并给出了针对盾构法地铁施工的安全管理改进意见,通过模型信息反馈指导现场施工,验证了该模型的可行性。

基于熵权Shapley值法的梯级水电站补偿效益分摊

为使梯级水电站补偿效益分摊较好地兼顾到各水电站的利益、调动其参与联合调度的积极性,将熵权法与Shapley值法相结合,提出熵权Shapley值法,并建立熵权Shapley值效益分摊模型,将其应用于某流域梯级的三个水电站的效益分摊中。结果表明,该法不仅考虑了各水电站之间的公平性,同时兼顾了自身的装机容量、调节库容、额定水头和保证出力等个体特征;分摊结果公平合理,调动了龙头水电站参与梯级联合运行的积极性,有利于实现流域梯级联合运行及总效益最大的目标。

基于Shapley值法的梯级水库收益分配研究

梯级水库联合调度产生的收益应在各参与水库之间进行合理分配。分析了梯级水库调度的几种模式,应用Shapley值法对联合调度所产生收益在各参与水库间进行分配,得到了各种模式下各水库应得到的实际收益。Shapley值法可以促进梯级水库群的联合调度,有利于实现梯级水库群总收益最大的目标。

基于Shapley值法的VMI下合作企业间的费用分担策略

讨论由一个供应商和两个零售商组成的四种不同组合的连续时间VM I管理模式,得到系统的总费用与各成员的费用。基此,运用合作对策中的Shap ley值法对VM I下库存管理费用的节约进行合理的分配。

不确定AHP和Shapley值应用于投标联合体利益分配

从合作博弈论视角分析了施工企业投标联合体利益合理分配的问题,运用Shapley值法给出了投标联合体的初次分配,从参与成员的贡献度出发,建立了相应的评价指标体系模型,基于不确定型AHP在此基础上进行了适当的改进,以具体的数据为算例,结果表明改进的分配方法与成员在联合体中的价值相匹配,有利于联合体的稳定。

VMI模式下3PL介入的供应链Shapley利益分配机制

针对汽车制造业中各方成员利益分配不均带来的合作压力,探讨一类供应商管理库存模式下第三方物流介入的三类主体供应链利益分配机制。基于大型制造商往往在供应链中拥有主导权这一现实背景,考虑一个制造商处于主导地位的供应链,该供应链由多个供应商、一个第三方物流和一个制造商构成。合作前第三方物流分别至供应商处取货并运送至制造商处,合作后第三方物流采用循环取货模式至各供应商取货。借助Shapley值方法得到供应链合作前后成本节约额在供应链成员间的分配方案,并通过算例进行验证。结果表明,循环取货模式下采用Shapley分配法可使供应链成员各方均获益。