AIRCRAFT CONCEPT EVALUATION AND EFFECTIVENESS-BASED DECISION-MAKING

Based on effectiveness analysis , a novel method is presented for combat aircraft top-hierarchy concept evaluation and decision-making. Applying multi-criterion decision-making ( MCDM ) and analytic hierarchy process , the new method can help to overcome the limitations of existing evaluation systems and decision-make methods.The proposed method includes the following process :( 1 ) Establish a multi-criterion and multi-hierarchy evaluation attribute system by introducing combat effectiveness ;( 2 ) Assign weight to the attributes and normalize them ;( 3 ) Evaluate and decision-make top-hierarchy aircraft concept based on effectiveness to reach a satisfactory design by comprehensively applying four multi-criterion decision-making methodologies , i.e.grey correlation projection method , weighted summation method , weighted quadrature method and ideal solution decision-making method , while considering the attribute hierarchy system and the logical relations among the attributes.Finally , an example is given to indicate the validity and feasibility of the proposed method.

Improved Fuzzification Method for Multi-Objective Decision-Making and Its Application in Evaluation of Highway Planning

A new fuzzification method for multi-objective decision-making and selective sorting is proposed on the basis of the fuzzy consistent relation, and the specific algorithm is presented. The method is applied to the evaluation of highway planning of Zhanjiang city. To decrease the subjectivity in the process of decision-making, the LOWA operator is introduced, and a discussion on how to select appropriate weights involved in multi-objective sorting is made. It is concluded that it is feasible to apply the fuzzy consistent relation to multi-objective decision-making analysis, and the improved fuzzication method is workable.

Assessing Criteria Weights by the Symmetry Point of Criterion (Novel SPC Method)–Application in the Efficiency Evaluation of the Mineral Deposit Multi-Criteria Partitioning Algorithm

Information about the relative importance of each criterion or theweights of criteria can have a significant influence on the ultimate rank of alternatives.Accordingly,assessing the weights of criteria is a very important task in solving multi-criteria decision-making problems.Three methods are commonly used for assessing the weights of criteria:objective,subjective,and integrated methods.In this study,an objective approach is proposed to assess the weights of criteria,called SPCmethod(Symmetry Point of Criterion).This point enriches the criterion so that it is balanced and easy to implement in the process of the evaluation of its influence on decision-making.The SPC methodology is systematically presented and supported by detailed calculations related to an artificial example.To validate the developed method,we used our numerical example and calculated the weights of criteria by CRITIC,Entropy,Standard Deviation and MEREC methods.Comparative analysis between these methods and the SPC method reveals that the developedmethod is a very reliable objective way to determine the weights of criteria.Additionally,in this study,we proposed the application of SPCmethod to evaluate the efficiency of themulti-criteria partitioning algorithm.The main idea of the evaluation is based on the following fact:the greater the uniformity of the weights of criteria,the higher the efficiency of the partitioning algorithm.The research demonstrates that the SPC method can be applied to solving different multi-criteria problems.

Selecting suitable key supplier for core components during smart complex equipment central-private enterprises collaborative development process:from two different forms of evaluation information and matching perspective

With the development of central-private enterprises integration,selecting suitable key suppliers are able to provide core components for smart complex equipment.We consider selecting suitable key suppliers from matching perspective,for it not only satisfies natural development of smart complex equipment,it is also a good implementation of equipment project in central-private enterprises integration context.In in this paper,we carry out two parts of research,one is evaluation attributes based on comprehensive analysis,and the other is matching process between key suppliers and core components based on the matching attribute.In practical analysis process,we employ comprehensive evaluated analysis methods to acquire relevant attributes for the matching process that follows.In the analysis process,we adopt entropy-maximum deviation method(MDM)-decision-making trial and evaluation laboratory(DEMATEL)-technique for order preference by similarity to an ideal solution(TOPSIS)to obtain a comprehensive analysis.The entropy-MDM is applied to get weight value,DEMATEL is utilized to obtain internal relations,and TOPSIS is adopted to get ideal evaluated solution.We consider aggregating two types of evaluation information according to similarities of smart complex equipment based on the combination between geometric mean and arithmetic mean.Moreover,based on the aforementioned attributes and generalized power Heronian mean operator,we aggregate preference information to acquire relevant satisfaction degree,then combine the constructed matching model to get suitable key supplier.Through comprehensive analysis of selecting suitable suppliers,we know that two-sided matching and information aggregation can provide more research perspectives for smart complex equipment.Through analysis for relevant factors,we find that leading role and service level are also significant for the smart complex equipment development process.

Study on effectiveness evaluation of weapon systems based on grey relational analysis and TOPSIS

To evaluate the effectiveness of weapon systems, the advantages and disadvantages of grey relational analysis and TOPSIS for multiattribute decision-making is pointed out, and an effectiveness evaluation model of weapon systems by combining grey relational analysis and TOPSIS is proposed. The model aggregates the grey relational grade and the distance to a new integrated closeness and reflects not only the trend but also the situation of the alternative. The example illuminates that the model is effective for the effectiveness evaluation of weapon systems.

A new framework for evaluation of rock fragmentation in open pit mines

The main purpose of blasting in open pit mines is to produce the feed for crushing stage with the optimum dimensions from in situ rocks. The size distribution of muck pile indicates the efficiency of blasting pattern to reach the required optimum sizes. Nevertheless, there is no mature model to predict fragmentation distribution to date that can be used in various open pit mines. Therefore, a new framework to evaluate and predict fragmentation distribution is presented based on the image analysis approach. For this purpose, the data collected from Jajarm bauxite mine in Iran were used as the sources in this study. The image analysis process was performed by Split-Desktop software to find out fragmentation distribution, uniformity index and average size of the fragmented rocks. Then, two different approaches including the multivariate regression method and the decision-making trial and evaluation laboratory(DEMATEL) technique were incorporated to develop new models of the uniformity index and the average size to improve the Rosin-Rammler function. The performances of the proposed models were evaluated in four blasting operation sites. The results obtained indicate that the regression model possesses a better performance in prediction of the uniformity index and the average size and subsequently the fragmentation distribution in comparison with DEMATEL and conventional Rosin-Rammler models.

Dynamic probability evaluation of safety levels of earth-rockfill dams using Bayesian approach

In order to accurately predict and control the aging process of dams, new information should be collected continuously to renew the quantitative evaluation of dam safety levels. Owing to the complex structural characteristics of dams, it is quite difficult to predict the time-varying factors affecting their safety levels. It is not feasible to employ dynamic reliability indices to evaluate the actual safety levels of dams. Based on the relevant regulations for dam safety classification in China, a dynamic probability description of dam safety levels was developed. Using the Bayesian approach and effective information mining, as well as real-time information, this study achieved more rational evaluation and prediction of dam safety levels. With the Bayesian expression of discrete stochastic variables, the a priori probabilities of the dam safety levels determined by experts were combined wfth the likelihood probability of the real-time check information, and the probability information for the evaluation of dam safety levels was renewed. The probability index was then applied to dam rehabilitation decision-making. This method helps reduce the difficulty and uncertainty of the evaluation of dam safety levels and complies with the current safe decision-making regulations for dams in China. It also enhances the application of current risk analysis methods for dam safety levels.

Image Processing Tool Promoting Decision-Making in Liver Surgery of Patients with Chronic Kidney Disease

Preoperative assessment of the liver volume and function of the remnant liver is a mandatory prerequisite before performing major hepatectomy. The aim of this work is to develop and test a software application for evaluation of the residual function of the liver prior to the intervention of the surgeons. For this purpose, a complete software platform consisting of three basic modules: liver volume segmentation, visualization, and virtual cutting, was developed and tested. Liver volume segmentation is based on a patient examination with non-contrast abdominal Computed Tomography (CT). The basis of the segmentation is a multiple seeded region growing algorithm adapted for use with CT images without contrast-enhancement. Virtual tumor resection is performed interactively by outlining the liver region on the CT images. The software application then processes the results to produce a three-dimensional (3D) image of the “resected” region. Finally, 3D rendering module provides possibility for easy and fast interpretation of the segmentation results. The visual outputs are accompanied with quantitative measures that further provide estimation of the residual liver function and based on them the surgeons could make a better decision. The developed system was tested and verified with twenty abdominal CT patient sets consisting of different numbers of tomographic images. Volumes, obtained by manual tracing of two surgeon experts, showed a mean relative difference of 4.5%. The application was used in a study that demonstrates the need and the added value of such a tool in practice and in education.

Extension of Paraconsistent Many-Valued Similarity Method to Group Decision

The Paraconsistent Many-Valued Similarity (PMVS) method for multi-attribute decision making will be incomplete as a decision model if it is not extended to the realm of group decision-making. Therefore, in this article, our primary objective is to show how the paraconsistent many-valued similarity method can be used to solve group decision-making problems involving choice making or ranking of a finite set of decision alternatives. Moreover, since weights are very important parameters in multi-attribute decision-making, we have introduced the Borda rule to calculate the weights of experts and that of every criterion under consideration. To demonstrate how the proposed method works, a numerical example on energy sources of an economy from the points of view of a group of experts is investigated. Further, we compare the results of this new approach with that of fuzzy TOPSIS group decision-making method to illustrate the robustness and effectiveness of the former.

A new method for performance evaluation of decision-making units with application to service industry

The decision-making units(DMUs)in the modern service industries may produce desirable outputs and undesirable outputs.For the decision makers,some outputs may be more desired than others although all of them are desirable.Considering these characteristics,this work combines the data envelopment analysis(DEA)and the multiple attributes decision-making(MADM)method,to make a reasonable and comprehensive performance evaluation for DMUs.Specifically,three DEA-based models are modified to obtain more reasonable efficiency scores for DMUs.The MADM method is used to determine the weights of outputs based on the preference ratings within the outputs.The efficiency scores are then multiplied by the aggregated outputs quantities to obtain the comprehensive performance scores for evaluation.The effectiveness of the proposed models is demonstrated by extensive numerical experiments.

Scoring system for prediction of metastatic spine tumor prognosis

Assessing the prognosis before treatment for metastatic spine tumor is extremely important in therapy selection.Therefore,we review some prognostic scoring systems and their outcomes.Articles with combinations of two keywords among"metastatic spine tumor"and"prognosis","score","scoring system","predicting",or"life expectancy"were searched for in Pub Med.As a result,236 articles were extracted.Those referring to representative scoring systems about predicting the survival of patients with metastatic spine tumors were used.The significance and limits of these scoring systems,and the future perspectives were described.Tokuhashi score,Tomita score,Baur score,Linden score,Rades score,and Katagiri score were introduced.They are all scoring systems prepared by combining factors that affect prognosis.The primary site of cancer and visceral metastasis were common factors in all of these scoring systems.Other factors selected to influence the prognosis varied.They were useful to roughly predict thesurvival period,such as,"more than one year or not"or"more than six months or not".In particular,they were utilized for decision-making about operative indications and avoidance of excessive medical treatment.Because the function depended on the survival period in the patients with metastatic spine tumor,it was also utilized in assessing functional prognosis.However,no scoring system had more than 90%consistency between the predicted and actual survival periods.Future perspectives should adopt more oncological viewpoints with adjustment of the process of treatment for metastatic spine tumor.

A method for emergency response alternative decision-making under uncertainty

In this paper,an emergency decision-making method,based on case-based reasoning and cloud model,is proposed to solve the risk decision-making problem in emergency response.Casebased reasoning,by allowing the decision-maker to referring to past decisions,introduces a short-cut to formulate feasible emergency alternatives.Cloud model is used to evaluate and optimise the emergency response alternatives.To evaluate emergency response alternatives,the decision criterion must be determined according to the aim and characteristics of emergency rescue in disasters or accidents.Then,the weight cloud and evaluation cloud of the decision criterion are determined by the Delphi method combined with backward cloud generator,and the synthesised cloud of each alternative is calculated through arithmetic rules of cloud.Finally,a ranking of all response alternatives can be determined,and the best alternative is selected.Case study shows that the method makes the conversion between qualitative description and quantitative indication more effective.

基于动态综合评价模型的街区型住区开放对城市交通拥堵影响的研究（英文）

The growing use of vehicles with the development of China brings greater pressure on the existing road traffic network. Based on the domestic and international research experiences and the domestic congestion situations, this paper selected six indicators that affect the traffic conditions. As each single indicator cannot reflect the detailed traffic quality separately, the dynamic comprehensive evaluation principle is adopted.Then we used the principle of "Variation Driven" to determine the weight vector of each sub-indicator, and established a multi-indicator comprehensive evaluation system through the dynamic weight of each sub-indicator. Finally, the rationality and feasibility of the system is demonstrated by case analysis. This provides a strong theoretical foundation and basis to mitigate traffic congestion.

A method for threshold selection in load extrapolation based on multiple criteria decision-making technology

In order to establish an accurate peak over threshold(POT)model for reasonable load extrapolation,a new threshold selection method based on multiple criteria decision making(MCDM)technology is proposed.The fitting test criterion is taken into consideration in the method.For each candidate threshold,the fitting values of several fitting test criteria are integrated into a comprehensive evaluation value through entropy method and MCDM technology.The threshold corresponding to the minimum comprehensive evaluation value is assumed as the optimal threshold.A random simulation study is carried out to evaluate the performance of the method and to compare them with other literature methods.Genuine load data are applied the proposed method.Both the results shown that the proposed method could be seen as an additional method that complements existing threshold selection methods.

A bioinspired path planning approach for mobile robots based on improved sparrow search algorithm

In this paper,a bioinspired path planning approach for mobile robots is proposed.The approach is based on the sparrow search algorithm,which is an intelligent optimization algorithm inspired by the group wisdom,foraging,and anti-predation behaviors of sparrows.To obtain high-quality paths and fast convergence,an improved sparrow search algorithm is proposed with three new strategies.First,a linear path strategy is proposed,which can transform the polyline in the corner of the path into a smooth line,to enable the robot to reach the goal faster.Then,a new neighborhood search strategy is used to improve the fitness value of the global optimal individual,and a new position update function is used to speed up the convergence.Finally,a new multi-index comprehensive evaluation method is designed to evaluate these algorithms.Experimental results show that the proposed algorithm has a shorter path and faster convergence than other state-ofthe-art studies.

Risk identification and prioritization in banking projects of payment service provider companies:An empirical study

ldentifying risks and prioritizing is important for payment service provider(PSP)companies to get banking projects and gain more market share.However,studies regarding the identification of risks and causal relationships are insufficient in the lranian PSP industry and the industry is unique because of its characteristics.In this study,30 experts involved with PSP companies are employed as the research sample.Eleven key risks and 46 sub-risks are also ientified.Subsequently,the fuzzy decision-making trial and evaluation laboratory technique is applied to determine the effective and affected risks and the severity of their effects on each other.Finally,all risks are ranked.Due to the interal interrelationships of the main risks,the weight of each risk is calculated via the fuzy analytic network process.As the second-level risks have no significant interrelationships,they are ranked via the fuzzy analytical hierarchy process.Moreover,the best-worst method is used to ensure that the obtained rankings are reliable.This study identifies the risks affecting the loss of banking projects and determines the impacts of these risks on each.A sensitivity analysis is then conducted on the weights of the criteria,and the results are compared.