Selecting proper sites for underground dam construction using Multi-Attribute Utility Theory in arid and semi-arid regions

Although the construction of underground dams is one of the best methods to conserve water resources in arid and semi-arid regions,applying efficient methods for the selection of suitable sites for subsurface dam construction remains a challenge.Due to the costly and time-consuming methods of site selection for underground dam construction,this study aimed to present a new method using geographic information systems techniques and decision-making processes.The exclusionary criteria including fault,slope,hypsometry,land use,soil,stream,geology,and chemical properties of groundwater were selected for site selection of dam construction and inappropriate regions were omitted by integration and scoring layers in ArcGIS based on the Boolean logic.Finally,appropriate sites were prioritized using the Multi-Attribute Utility Theory.According to the results of the utility coefficient,seven sites were selected as the region for underground dam construction based on all criteria and experts’opinions.The site of Nazarabad dam was the best location for underground dam construction with a utility coefficient of 0.7137 followed by sites of Akhavan with a utility coefficient of 0.4633 and Mirshamsi with a utility coefficient of 0.4083.This study proposed a new approach for the construction of the subsurface dam at the proper site and help managers and decision-makers achieve sustainable water resources with limited facilities and capital and avoid wasting national capital.

Fermatean Hesitant Fuzzy Prioritized Heronian Mean Operator and Its Application in Multi-Attribute Decision Making

In real life,incomplete information,inaccurate data,and the preferences of decision-makers during qualitative judgment would impact the process of decision-making.As a technical instrument that can successfully handle uncertain information,Fermatean fuzzy sets have recently been used to solve the multi-attribute decision-making(MADM)problems.This paper proposes a Fermatean hesitant fuzzy information aggregation method to address the problem of fusion where the membership,non-membership,and priority are considered simultaneously.Combining the Fermatean hesitant fuzzy sets with Heronian Mean operators,this paper proposes the Fermatean hesitant fuzzy Heronian mean(FHFHM)operator and the Fermatean hesitant fuzzyweighted Heronian mean(FHFWHM)operator.Then,considering the priority relationship between attributes is often easier to obtain than the weight of attributes,this paper defines a new Fermatean hesitant fuzzy prioritized Heronian mean operator(FHFPHM),and discusses its elegant properties such as idempotency,boundedness and monotonicity in detail.Later,for problems with unknown weights and the Fermatean hesitant fuzzy information,aMADM approach based on prioritized attributes is proposed,which can effectively depict the correlation between attributes and avoid the influence of subjective factors on the results.Finally,a numerical example of multi-sensor electronic surveillance is applied to verify the feasibility and validity of the method proposed in this paper.

A Multi-Attribute Decision-Making Method Using Belief-Based Probabilistic Linguistic Term Sets and Its Application in Emergency Decision-Making

Probabilistic linguistic term sets(PLTSs)are an effective tool for expressing subjective human cognition that offer advantages in the field ofmulti-attribute decision-making(MADM).However,studies have found that PLTSs have lost their ability to accurately capture the views of decision-makers(DMs)in certain circumstances,such as when the DM hesitates between multiple linguistic terms or the decision information is incomplete,thus affecting their role in the decision-making process.Belief function theory is a leading streamof thought in uncertainty processing that is suitable for dealing with the limitations of PLTS.Therefore,the purpose of this study is to extend PLTS to incorporate belief function theory.First,we provide the basic concepts of the extended PLTS(i.e.,belief-based PLTS)through case analyses.Second,the aggregation operator of belief-based PLTS is defined with the ordered weighted average(OWA)-based soft likelihood function,which is improved by considering the reliability of the information source.Third,to measure the magnitude of different belief-based PLTSs,the belief interval of singleton is calculated,and the comparison method of belief-based PLTS is constructed based on probabilities.On the basis of the preceding discussion,we further develop an emergency decision framework that includes several novel techniques,such as attribute weight determination and decision information aggregation.Finally,the usefulness of the framework is demonstrated through a case study,and its effectiveness is illustrated through a series of comparisons.

Two-Sided Matching Decision Making with Multi-Attribute Probabilistic Hesitant Fuzzy Sets

In previous research on two-sided matching(TSM)decision,agents’preferences were often given in the form of exact values of ordinal numbers and linguistic phrase term sets.Nowdays,the matching agent cannot perform the exact evaluation in the TSM situations due to the great fuzziness of human thought and the complexity of reality.Probability hesitant fuzzy sets,however,have grown in popularity due to their advantages in communicating complex information.Therefore,this paper develops a TSM decision-making approach with multi-attribute probability hesitant fuzzy sets and unknown attribute weight information.The agent attribute weight vector should be obtained by using the maximum deviation method and Hamming distance.The probabilistic hesitancy fuzzy information matrix of each agent is then arranged to determine the comprehensive evaluation of two matching agent sets.The agent satisfaction degree is calculated using the technique for order preference by similarity to ideal solution(TOPSIS).Additionally,the multi-object programming technique is used to establish a TSM method with the objective of maximizing the agent satisfaction of two-sided agents,and the matching schemes are then established by solving the built model.The study concludes by providing a real-world supply-demand scenario to illustrate the effectiveness of the proposed method.The proposed method is more flexible than prior research since it expresses evaluation information using probability hesitating fuzzy sets and can be used in scenarios when attribute weight information is unclear.

Multi-Model Approach for Assessing the Influence of Calibration Criteria on the Water Balance in Ouémé Basin

Hydrological models are very useful tools for evaluating water resources, and the hydroclimatic hazards associated with the water cycle. However, their calibration and validation require the use of performance criteria which choice is not straightforward. This paper aims to evaluate the influence of the performance criteria on water balance components and water extremes using two global rainfall-runoff models (HBV and GR4J) over the Ouémé watershed at the Bonou and Savè outlets. Three (3) Efficacy criteria (Nash, coefficient of determination, and KGE) were considered for calibration and validation. The results show that the Nash criterion provides a good assessment of the simulation of the different parts of the hydrograph. KGE is better for simulating peak flows and water balance elements than other efficiency criteria. This study could serve as a basis for the choice of performance criteria in hydrological modelling.

Unequal Distribution of Innovation Efforts for Neglected Tropical Diseases: The Role of Funding Evaluation Criteria

Background: International research and innovation efforts for neglected tropical diseases have increased in recent decades due to disparities in overall health research funding in relation to global burden of disease. However, within the field of neglected tropical diseases some seem far more neglected than others. In this research the aim is to investigate the distribution of resources and efforts, as well as the mechanisms that underpin funding allocation for neglected tropical diseases. Methodology: A systematic literature review was conducted to establish a comprehensive overview of known indicators for innovation efforts related to a wide range of neglected tropical diseases. Articles were selected based on a subjective evaluation of their relevance, the presence of original data, and the breadth of their scope. This was followed by thirteen in-depth open-ended interviews with representatives of private, public and philanthropic funding organizations, concerning evaluation criteria for funding research proposals. Results: The findings reveal a large difference in the extent to which the individual diseases are neglected with notable differences between absolute and relative efforts. Criteria used in the evaluation of research proposals relate to potential impact, the probability of success and strategic fit. Private organizations prioritize strategic fit and economic impact;philanthropic organizations prioritize short-term societal impact;and public generally prioritize the probability of success by accounting for follow-up funding and involvement of industry. Funding decisions of different types of organizations are highly interrelated. Conclusions: This study shows that the evaluation of funding proposals introduces and retains unequal funding distribution, reinforcing the relative neglect of diseases. Societal impact is the primary rationale for funding but application of it as a funding criterion is associated with significant challenges. Furthermore, current application of evaluation criteria leads to a primary focus on short-term impact. Through current practice, the relatively most neglected diseases will remain so, and a long-term strategy is needed to resolve this.

Local Criteria Used by Farmers to Evaluate the Agronomic Performance and the Fertilizing Capacity of Cowpea Varieties: Diversity, Variability and Proximal Relation with Agronomic Measurements in Contrasted Sahelian Locations

When contributing to participatory research, farmers usually appreciate the performance of cowpea varieties using qualitative scores. The score they attribute to each variety are based on local knowledge. The specific criteria they individually use to attribute a score are not well described. The objectives of this work were to: 1) identify and describe exhaustively the local criteria used by farmers to measure the agronomic performance of cowpea;2) assess the variability and statistical structure of these farmer criteria across local contexts;3) and analyze the association between these farmer criteria and the classical agronomic measurement. To achieve these objectives, an augmented block design was implemented across fifteen locations in the regions of Maradi, Dosso and Tillabéri, representing a diversity of local contexts. From a set of 36 cowpea varieties, fifteen varieties were sown per location, including five varieties (controls) common to all locations. In each location, two replicates were sown in randomized Fisher’s blocks. After agronomic measurement and participatory evaluation (scoring of varieties by farmers), a group survey (focus group) was conducted in each location to identify the criteria considered by farmers to found their discretional scoring of varieties during the participatory evaluation. The analysis of the data identified, across locations, thirteen criteria defined by farmers to characterize the agronomic performance of cowpea. Some of these criteria were different according to location. Farmers ranked the three varieties with the best performance for each agronomical trait (Top 3 varieties). A comparison of the farmer ranking with the ranking based on agronomic measurements revealed similarity and complementary between both methods. This study highlighted the importance of considering both local and scientific knowledge in local varietal evaluations.

Coal-rock gas:Concept,connotation and classification criteria

In recent years,great breakthroughs have been made in the exploration and development of natural gas in deep coal-rock reservoirs in Junggar,Ordos and other basins in China.In view of the inconsistency between the industrial and academic circles on this new type of unconventional natural gas,this paper defines the concept of"coal-rock gas"on the basis of previous studies,and systematically analyzes its characteristics of occurrence state,transport and storage form,differential accumulation,and development law.Coal-rock gas,geologically unlike coalbed methane in the traditional sense,occurs in both free and adsorbed states,with free state in abundance.It is generated and stored in the same set of rocks through short distance migration,occasionally with the accumulation from other sources.Moreover,coal rock develops cleat fractures,and the free gas accumulates differentially.The coal-rock gas reservoirs deeper than 2000 m are high in pressure,temperature,gas content,gas saturation,and free-gas content.In terms of development,similar to shale gas and tight gas,coal-rock gas can be exploited by natural formation energy after the reservoirs connectivity is improved artificially,that is,the adsorbed gas is desorbed due to pressure drop after the high-potential free gas is recovered,so that the free gas and adsorbed gas are produced in succession for a long term without water drainage for pressure drop.According to buried depth,coal rank,pressure coefficient,reserves scale,reserves abundance and gas well production,the classification criteria and reserves/resources estimation method of coal-rock gas are presented.It is preliminarily estimated that the coal-rock gas in place deeper than 2000 m in China exceeds 30×10^(12)m^(3),indicating an important strategic resource for the country.The Ordos,Sichuan,Junggar and Bohai Bay basins are favorable areas for large-scale enrichment of coal-rock gas.The paper summarizes the technical and management challenges and points out the research directions,laying a foundation for the management,exploration,and development of coal-rock gas in China.

Evaluation of AVNRT & AVRT by Different Criteria: Old & New

The two most frequent causes of paroxysmal SVT are atrioventricular tachycardia (AVRT) and atrioventricular nodal re-entrant tachycardia (AVNRT). The purpose of this study was to assess the diagnostic efficacy of traditional and newly proposed ECG criteria in the identification of Avnrt and Avrt. Aim of the Study: The aim of this study was to evaluate Atrioventricular Nodal Reentrant Tachycardia (AVNRT) and Atrioventricular Re-entrant Tachycardia (AVRT) using both traditional and novel criteria. Methods: This prospective observational study was conducted at the Electrophysiology Unit, Department of Cardiology, National Institute of Cardiovascular Diseases (NICVD) in Dhaka, from February 2019 to January 2020. A total of 62 patients with Supraventricular Tachycardia (SVT) undergoing electrophysiology study (EPS) were included. Standard ECG criteria were applied for the differential diagnosis, and electrophysiological diagnoses were made using established criteria. Statistical analysis, including descriptive statistics and appropriate tests, was performed using SPSS 23.0. Result: In our study of 62 patients with Supraventricular Tachycardia (SVT), we found that 66.1% had AVNRT and 33.9% had AVRT. The mean age in AVNRT was higher than AVRT (41.3 ± 9.7 vs. 38.5 ± 14.3, p = 0.36) with statistically no significant difference, with similar gender distribution between AVNRT and AVRT groups. Classical AVNRT criteria were present in 30.6% of patients, and 45.2% showed a Pseudo R' wave in aVR. Additionally, 30.6% had an RP interval ≥100ms, more prevalent in AVRT patients (66.7%). Conclusion: Integrating traditional and novel criteria, including lead aVR analysis, enhances the electrocardiographic diagnosis of AVNRT and AVRT, offering a pathway to refined patient care.

基于Beers Criteria 2023 评估我院门诊老年患者潜在不适当用药现状

目的评估我院门诊老年患者潜在不适当用药(PIM)的发生情况,分析影响因素,探讨如何促进老年合理用药。方法收集常州市第一人民医院2023年5月~2023年7月,年龄65~99岁门诊患者处方,按照Beers Criteria 2023对患者的用药进行分析,采用二元logistic回归模型分析发生PIM的影响因素。结果最终筛选出24217例患者,男11823例,占比48.8%,女12394例,占比51.2%。疾病数量、用药种类、年龄为PIM发生的危险因素,就诊科室数为保护因素(P<0.05)。结论Beers Criteria 2023检出PIM率为20.37%,临床药师应结合临床,减少用药种类以减少老年患者PIM的发生率,对必需使用导致PIM药物治疗的老年患者应加强监测并个体化用药,保证老年患者用药安全。

GIS-Based Multi-Criteria Decision Analysis (MCDA) and Analytical Hierarchy Process (AHP) Techniques to Derive Flood Risks Management on Rice Productivity in Gishari Marshland

Floods are phenomenon with significant socio-economic implications mainly for human loss, agriculture, livestock, soil loss and land degradation, for which many researchers try to identify the most appropriate methodologies by analyzing their temporal and spatial development. This study therefore attempts to employ the GIS-based multi-criteria decision analysis and analytical hierarchy process techniques to derive the flood risks management on rice productivity in the Gishari Agricultural Marshland in Rwamagana district, Rwanda. Here, six influencing potential factors to flooding, including river slope, soil texture, Land Use Land Cover through Land Sat 8, rainfall, river distance and Digital Elevation Model are considered for the delineation of flood risk zones. Data acquisition like Landsat 8 images, DEM, land use land cover, slope, and soil class in the study area were considered. Results showed that if the DEM is outdated or inaccurate due to changes in the terrain, such as construction, excavation, or erosion, the predicted flood patterns might not reflect the actual water flow. This could result unexpected flood extents and depths, potentially inundating rice fields that were not previously at risk and this, expectedly explained that the increase 1 m in elevation would reduce the rice productivity by 0.17% due to unplanned flood risks in marshland. It was found that the change in rainfall distribution in Gishari agricultural marshland would also decrease the rice productivity by 0.0018%, which is a sign that rainfall is a major factor of flooding in rice scheme. Rainfall distribution plays a crucial role in flooding analysis and can directly impact rice productivity. Oppositely, another causal factor was Land Use Land Cover (LULC), where the Multivariate Logistic Regression Model Analysis findings showed that the increase of one unit in Land Use Land Cover would increase rice productivity by 0.17% of the total rice productivity from the Gishari Agricultural Marshland. Based on findings from these techniques, the Gishari Agricultural Marshlands having steeped land with grassland is classified into five classes of flooding namely very low, low, moderate, high, and very high which include 430%, 361%, 292%, 223%, and 154%. Government of Rwanda and other implementing agencies and major key actors have to contribute on soil and water conservation strategies to reduce the runoff and soil erosion as major contributors of flooding.

Prognostic value of cachexia defined by the Asian Working Group for Cachexia criteria in patients with gastric cancer

Background:The Asian Working Group for Cachexia(AWGC)criteria are newly proposed diagnostic standards specifically designed for Asian populations.This research focused on validating the predictive value of the AWGC criteria for assessing the prognosis and medical burden of patients with gastric cancer.Methods:Cox proportional hazards analysis was conducted to evaluate the association between cachexia and overall survival.Logistic regression analysis was used to assess whether there was an independent association between cachexia and the 90-day mortality,the length of stay and the quality of life.Harrell’s concordance index was utilized to demonstrate the discriminative ability of different diagnostic criteria for cachexia.Results:AWGC-defined cachexia was an independent risk factor for a reduced overall survival in patients(HR=1.397,95%CI=1.209–1.615,P<0.001).The predictive accuracy of the AWGC criteria was markedly superior to that of the Fearon criteria(χ2=39.025 vs 13.877).Compared with Fearon standards,the AWGC criteria offered a 2.9%enhancement in clinical benefit(0.029,95%CI=0.048–0.008,P=0.005).Logistic regression analysis showed that only AWGC-defined cachexia was an independent risk factor for 90-day mortality(OR=2.142,95%CI=1.397–3.282,P<0.001)and prolonged hospitalization(OR=1.958,95%CI=1.587–2.416,P<0.001)in patients with gastric cancer,whereas cachexia defined by the Fearon criteria was not.Patients with AWGC-defined cachexia exhibited significant reductions in physical function,role function,emotional function,cognitive function,social functioning,and overall quality-of-life scores.Conversely,cachectic patients showed higher levels of fatigue,nausea and vomiting,pain,dyspnea,sleep disturbance,appetite loss,constipation,and financial difficulties.A multivariate logistic regression showed that patients with AWGC-defined cachexia had a 126.1%increased risk of impaired quality of life(OR=2.261,95%CI=1.859–2.749,P<0.001).Conclusions:The AWGC criteria are an effective tool for predicting adverse survival outcomes,90-day mortality,a prolonged hospital stay,and poorer quality of life in patients with gastric cancer.

Evaluating the Association between Human Papillomavirus and Vulvar Cancer:A Comprehensive Analysis Using Bradford Hill Criteria

Background:The role of human papillomavirus(HPV)in the development of vulvar cancer(VC)has been widely studied,but findings have been inconsistent.Despite numerous meta-analyses exploring the potential link between HPV and VC,the association remains controversial due to inherent limitations in meta-analytic methods.Objectives:To address this controversy,the study aims to investigate the potential link between HPV and VC using the Bradford Hill criteria,which offer a more comprehensive framework for establishing causation.Methodology:The study began by extracting all relevant studies on the association between HPV and VC from the PubMed database.The potential links were then assessed by examining the data using the major postulates of the Bradford Hill criteria.To ensure the reliability of the findings,the methodologies of the identified studies were critically evaluated to account for possible false-negative and false-positive results.Results:The assessment of previous studies against the Bradford Hill criteria revealed that the major postulates were not fulfilled.Conclusion:Based on the findings,it can concluded that there is no causal association between HPV and VC.

Contribution of GIS to Soil Landscape Mapping by Multi-Criteria Analysis Using Weighting: The Case of the Square Degrees of M’Bahiakro (Centre) and Daloa (Centre-West) in Ivory Coast

As part of the drive to improve coffee and cocoa production in Ivory Coast, studies are carried out to identify soils that are favourable for these crops. It is therefore necessary to orientate soil investigations based on reliable criteria that best discriminate soil cover. With this in mind, this study is being carried out to help improve survey methods by mapping soil landscapes. It uses GIS and weighted multicriteria analysis. To do this, satellite images were processed and the geological map of the square degrees of M’Bahiakro and Daloa was reclassified. The results show that relief is the main factor in soil landscape differentiation, with respective weights of 0.58 and 0.67 for the forest and pre-forest zones. In contrast, the weight of geological formation in soil landscape differentiation remains low (0.05 for the forest zone and 0.07 for the pre-forest zone). The criteria used on the base of aggregation sum methods have made it possible to formulate soil landscape mapping prediction functions according to agro-ecological environments in the humid intertropical zone. This is essential for the orientation of soil survey work. Nevertheless, other comparative methods, such as the coding mapping method, could provide elements for discussion to validate the models.

Multi-Criteria Wildfire Risk Hazard Assessment in GIS Environment: Projection for the Future and Impact on RES Projects Installation Planning

It is alarming for the fact that Wildfires number, severity and consequently impact have significantly increased during the last years, an aftermath of the Climate Change. One of the most affected areas worldwide is Mediterranean, due to the unique combination of its type of vegetation and demanding climatic conditions. This research is focused on the Region of Epirus in Greece, an area with significant natural vegetation and a range of geomorphological aspects. In order to estimate the Wildfire Risk Hazard, several factors have been used: geomorphological (slope, aspect, elevation, TWI, Hydrographic network), social (Settlements and landfils, roads, overhead lines and substations), environmental (land cover) and climatic (Fire Weather Index). Through a multi-criteria decision analysis (MCDA) and an analytic hierarchy process (AHP) in a GIS environment, the Wildfire Risk Hazard has been estimated not only for current conditions but also for future projections for the near future (2031-2060) and the far future (2071-2100). The selected case study includes the potential impact of the Wildfires to the installed (or targeted to be installed) RES projects in the studied region.

Multi-attribute decision-making based on subjective and objective integrated eigenvector method

An integrated approach is proposed to investigate the fuzzy multi-attribute decision-making （MADM） problems, where subjective preferences are expressed by a pairwise comparison matrix on the relative weights of attributes and objective information is expressed by a decision matrix. An eigenvector method integrated the subjective fuzzy preference matrix and objective information is proposed. Two linear programming models based on subjective and objective information are introduced to assess the relative importance weights of attributes in an MADM problem. The simple additive weighting method is utilized to aggregate the decision information, and then all the alternatives are ranked. Finally, a numerical example is given to show the feasibility and effectiveness of the method. The result shows that it is easier than other methods of integrating subjective and objective information.

APPROACH FOR FUZZY MULTI-ATTRIBUTE DECISION-MAKING WITH FUZZY COMPLEMENTARY PREFERENCE RELATION ON ALTERNATIVES

In presented fuzzy multi-attribute decision-making （FMADM） problems, the information about attribute weights is interval numbers and the decision maker （DM） has fuzzy complementary preference relation on alternatives. Firstly, the decision-making information based on the subjective preference information in the form of the fuzzy complementary judgment matrix is uniform by using a translation function. Then an objective programming model is established. Attribute weights are obtained by solving the model, thus the fuzzy overall values of alternatives are derived by using the additive weighting method. Secondly, the ranking approach of alternatives is proposed based on the degree of similarity between the fuzzy positive ideal solution of alternatives （FPISA） and the fuzzy overall values. The method can sufficiently utilize the objective information of alternatives and meet the subjective requirements of the DM as much as possible. It is easy to be operated and implemented on a computer. Finally, the proposed method is applied to the project evaluation in the venture investment.

Multi-attribute Decision Making Method Based on the Attribute Difference Degree and Its Application in Rice Breeding

[Objective]The aim was to establish a multi-attribute decision making method and introduce its application in rice breeding.[Method]Based on the defined closeness degree among attributes,the difference degrees among attributes were discussed.Furthermore,the weights of attributes were determined based on the difference degrees among the attributes.[Result]A multi-attribute decision making method based on difference degrees among attributes was established,the feasibility of applying it in rice breeding was also analyzed.[Conclusion]This study enriched the methods to determine attribute weights in multi-attribute decision making and provided the necessary theoretical support for selecting rice varieties scientifically and rationally.

Two-phase TOPSIS of uncertain multi-attribute group decision-making

To solve the uncertain multi-attribute group decision-making of unknown attribute weights,three optimal models are built to decide the corresponding ideal solution weights,standard deviation weights and mean deviation weights.The comprehensive attribute weights are gotten through the product of the above three kinds of weights.And each decision maker＇s weighted decision matrices are also received by using the integrated attribute weights.The closeness degrees are also gotten by use of technique for order preference by similarity to ideal solution（TOPSIS） through dealing with the weighted decision matrices.At the same time the group decision matrix and weighted group decision matrix are gotten by using each decision-maker＇s closeness degree to every project.Then the vertical TOPSIS method is used to calculate the closeness degree of each project.So these projects can be ranked according to their values of the closeness degree.The process of the method is also given step by step.Finally,a numerical example demonstrates the feasibility and effectiveness of the approach.

An Improved Method Based on TODIM and TOPSIS for Multi-Attribute Decision-Making with Multi-Valued Neutrosophic Sets

Due to the complexity of decision-making problems and the subjectivity of decision-makers in practical application,it is necessary to adopt different forms of information expression according to the actual situation of specific decision-making problems and choose the best method to solve them.Multi-valued neutrosophic set,as an extension of neutrosophic set,can more effectively and accurately describe incomplete,uncertain or inconsistent information.TODIM and TOPSIS methods are two commonly used multi-attribute decision-making methods,each of which has its advantages and disadvantages.This paper proposes a new method based on TODIM and TOPSIS to solve multi-attribute decision-making problems under multi-valued neutrosophic environment.After introducing the related theory of multi-valued neutrosophic set and the traditional TODIM and TOPSIS methods,the new method based on a combination of TODIM and TOPSIS methods is described.And then,two illustrative examples proved the feasibility and validity of the proposed method.Finally,the result has been compared with some existing methods under the same examples and the proposed method’s superiority has been proved.This paper studies this kind of decision-making problem from algorithm idea,algorithm steps and decision-making influencing factors.