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This paper attempts to put forward a convincing and flexible grey cluster method that can be used in confirming credibility level of trustworthy software development process.

Determination on credibility level in the software development process is dynamic, as credibility of the results may be different at different times and under different project requirements. Qualitative methods are not entirely convincing, and most quantitative methods are not flexible enough. Grey cluster based on nonlinear grey whitening weight function put forward in this paper is both convincing and flexible. Finally eight projects from the ISBSG database are used for empirical analysis, which confirm that the method put forward in this paper is available and credible.

The results are convincing: not only that grey cluster based on nonlinear grey whitening weight function put forward in this paper is both convincing and flexible, but it can be used in confirming credibility level of trustworthy software development process.

Eight projects from the ISBSG database are used for empirical analysis, which confirms that the method put forward in this paper is available and credible.

Nonlinear grey whitening weight function is derivable except endpoint. Grey cluster based on nonlinear grey whitening weight function put forward in this paper is both convincing and flexible.

The purpose of this paper is to propose a grey target decision model based on cobweb area in order to overcome the effect and influence from the extreme value of the index on the decision result. However, it does not take into account the impact of the correlation between indicators on the angle of the index, and produce a certain degree decision information distortion as a result of the equal angle between the indicators. In order to solve the above problems, a novel grey decision-making model based on cone volume is proposed.

In this paper, the model uses the whitening weight function to whiten the interval grey number, and the Delphi method and the maximal entropy method are exploited to integrate the weight of the index. On the basis of this, the center of the bull’s eye, the weight and the index value are constructed as the center circle, the radius, and the high cone, respectively. The scheme is selected by the volume of the cone, the decision is made according to the order relation, and the example is utilized to prove and analyze the validity of the proposed model.

The results show that the proposed model can well improve the traditional grey target decision-making model from the modeling object and modeling method.

The method exposed in the paper can be used to deal with the grey target decision-making problems which characteristics are multi-indexes, and the attribute values are interval grey numbers.

The paper succeeds in overcoming the disadvantages of grey target decision making based on the target center distance and the cobweb area.

This paper aims to build an improved grey panel clustering evaluation model and evaluate the comprehensive development potential of industrial economy, society and ecological environment in the Yangtze River Economic Belt of China. The purpose of this study is to provide some theoretical basis and tool support for management departments and relevant researchers engaged in industrial sustainable development.

This study uses the driving force pressure state impact response analysis framework to build a comprehensive evaluation index system. Based on the center point triangle whitening weight function, it classifies the panel grey clustering of improvement time and index weight.

The results show that there are great differences in the level of industrial ecological development in different regions of the Yangtze River Economic Belt, which further illustrates the scientificity and rationality of the evaluation method proposed in this paper.

Due to the industrial ecological development is in a constantly changing state, and the information is uncertain. Whitening weight function is introduced to represent the complete information of relevant data. The industrial ecological evaluation involves a comprehensive complex system, which belongs to the panel data analysis problem. The improved grey panel clustering evaluation model is applied to grade the industrial ecological development level of the Yangtze River Economic Belt. The results have important guiding significance for the balanced development of industrial ecology in the region.

Due to the industrial ecological development is in a constantly changing state, and the information is uncertain. Whitening weight function is introduced to represent the complete information of relevant data. The industrial ecological evaluation involves a comprehensive complex system, which belongs to the panel data analysis problem. In order to improve the effectiveness of industrial ecological evaluation, the improved grey panel clustering evaluation model is applied to grade the industrial ecological development level of the Yangtze River Economic Belt. The results have important guiding significance for the balanced development of industrial ecology in the region.

the new model proposed in this paper complements and improves the grey clustering analysis theory of panel data, that is, aiming at the subjective limitation of using time degree to determine time weight in panel grey clustering, a comprehensive theoretical method for determining time weight is creatively proposed. Combining the DPSIR (Driving force-Pressure-State-Influence-Response) model model with ecological development, a comprehensive evaluation model is constructed to make the evaluation results more authentic and comprehensive.

The purpose of this paper is to construct a dynamic information aggregation decision-making model based on variable precision rough set.

To deal with the dynamic decision-making problems, the grey relational analysis method, grey fixed weight clustering based on the centre triangle whitening weight function and maximum entropy principle is used to establish the dynamic information aggregation decision-making model based on variable precision rough set. The method, to begin with, the grey relational analysis method is used to determine the attributes weights of each stage; taking the proximity of the attribute measurement value and positive and negative desired effect value and the uncertainty of time weight into account, a multi-objective optimisation model based on maximum entropy principle is established to solve the model with Lagrange multiplier method, so that time weights expression are acquired; what is more, the decision-making attribute is obtained by grey fixed weight clustering based on the centre triangle whitening weight function, so that multi-decision-making table with dynamic characteristics is established, and then probabilistic decision rules from multi-criteria decision table are derived by applying variable precision rough set. Finally, a decision-making model validates the feasibility and effectiveness of the model.

The results show that it the proposed model can well aggregate the multi-stage dynamic decision-making information, realise the extraction of decision-making rules.

The method exposed in the paper can be used to deal with the decision-making problems with the multi-stage dynamic characteristics, and decision-making attributes contain noise data and the attribute values are interval grey numbers.

The paper succeeds in realising both the aggregation of dynamic decision-making information and the extraction of decision-making rules.

As the world's largest developing country, China is relying on innovation to transform the pattern of economic growth; more and more attention has been paid to the construction of China's regional innovation system (RIS). This paper aims to establish a provincial evaluation index system for RIS construction level and that of construction condition and evaluate the innovation system construction level and construction condition of China's provinces by using grey fixed weight clustering.

This paper makes a comprehensive assessment of RIS by using grey fixed weight clustering.

The results show that the construction level of RIS is clearly associated with construction condition of RIS. In accordance with the results of the assessment, China's 31 provinces are classified into four typical types. Some relevant key measures to promote the RIS are suggested.

This paper establishes a new frame to evaluate RIS.

The purpose of this paper is to cluster and analyse the level of agricultural science and technology in China’s provinces by using grey clustering model, to have an overall understanding of the current situation of agricultural science and technology development in these provinces, and to offer a reference for decision-making departments to draw up agricultural science and technology development plans.

First of all, the grey clustering assessment is used to evaluate the clustering of agricultural science and technology level in China’s provinces in 2011, 2013 and 2015. Also a comparative static analysis is made. Then, based on the prediction data of GM (1,1) model, the provincial agricultural science and technology levels in 2017 and 2019 are analysed by grey clustering. Finally, some suggestions are put forward, such as adjusting the allocation of agricultural science and technology resources and providing policy preferences to backward areas, so as to promote the coordinated development of agricultural science and technology in China.

The development of agricultural science and technology in various provinces and regions of the authors’ country is unbalanced, with a big gap of agricultural and technology level between different provinces. What’s more, the level of agricultural science and technology in remote areas has been developing slowly, but it has been lagging behind. Through the grey clustering analysis of the provincial agricultural science and technology level in 2017 and 2019, it is concluded that the level of agricultural science and technology will be promoted as a whole, but the gap of agricultural science and technology level between different provinces and cities will be enlarged.

This paper comprehensively studies the current situation and future development trends of agricultural science and technology in China’s provinces in recent years, and preliminarily analyses the reasons for the transformation of agricultural science and technology level, however, with no further inspection. Related research should be made for further study.

This paper will provide overall understanding of the current situation of agricultural science and technology development in China’s provinces and cities, and put forward relevant suggestions for the future development of agricultural science and technology in China’s provinces and cities, and provide references for decision-making departments to draw up agricultural science and technology development plans.

For the first time, the grey clustering method is used to the research of agricultural science and technology level in the province. It analyses and evaluates the past and present situation and predicts the future development trend of provincial agricultural science and technology level by the grey clustering analysis method, which is a complete research.

The purpose of this paper is to construct a grey clustering model based on the nonlinear whitenization weight function and to assess the safety of civil aircraft by using a quantitative method.

According to the running stage of civil aircraft safety assessment issues, first the civil aircraft safety evaluation index system is constructed by using a qualitative method. Taking the information duplication between indicators, the grey relational analysis method is used to filter the key indicators, then the grey clustering evaluation model of nonlinear whitening right function is built to evaluate the safety of civil aircraft and the algorithm steps of the evaluation model are given. Finally, the model is validated by collecting the parameters of nine different civil aircrafts at home and abroad.

The results show that the safety level of different types of aircraft is different due to the different index parameters, and to some extent, explain the rationality and scientificity of the method proposed in this paper to solve the problem.

This paper gives a complete set of security assessment methods, which can be used to evaluate the security of civil aircraft in the operational phase quantitatively, scientifically and reasonably. Furthermore, it can be extended to other complex system security or stability assessment issues.

It not only provides the supplement and perfection of the safety assessment method in the theoretical system to a certain extent, but also provides a theoretical guidance to solve the problem of civil aircraft system safety assessment of civil aircraft manufacturing enterprise all over the world. At the same time, the nonlinear grey clustering evaluation model constructed in this paper is an improvement of the traditional model, which is, to some extent, the improvement of the grey clustering evaluation theory.

The purpose of this paper is to explore the method of clinical department classification in comprehensive hospital to provide a scientific management reference in performance evaluation.

In order to perform the classification of clinical departments, a grey cluster model was constructed. In this model, the benefit index of each clinical department was analyzed using grey associative analysis, and a superior index was chosen to incorporate in this model. Through the relevancy degree of superior index, the authors confirmed the weight of index, and the quintile threshold was calculated by a quintile method and whitening weight functions were constructed.

This model, based on grey entropy weight cluster, can reasonably distinguish the merits of clinical departments. From the case we study, neurology?/Cardiovasology?/Integrated disease and Emergency were the optimum assessing department.

The results demonstrated that the index selection, weight determination, whitening weight functions and model construction in this study could provide technique’s reference and application for hospital administrators. It avoids the subjective discrimination and reduces the influence of sample noise, and it is easy to perform while conducting performance evaluation in a comprehensive hospital.

The purpose of this paper is to propose a new casualty scheduling optimisation problem and to effectively treat casualties in the early stage of post-earthquake relief.

Different from previous studies, some new characteristics of this stage are considered, such as the grey uncertainty information of casualty numbers, the injury deterioration and the facility disruption scenarios. Considering these new characteristics, we propose a novel casualty scheduling optimisation model based on grey chance-constrained programming (GCCP). The model is formulated as a 0–1 mixed-integer nonlinear programming (MINP) model. An improved particle swarm optimisation (PSO) algorithm embedded in a grey simulation technique is proposed to solve the model.

A case study of the Lushan earthquake in China is given to verify the effectiveness of the model and algorithm. The results show that (1) considering the facility disruption in advance can improve the system reliability, (2) the grey simulation technology is more suitable for dealing with the grey uncertain information with a wider fluctuation than the equal-weight whitening method and (3) the authors' proposed PSO is superior to the genetic algorithm and immune algorithm.

The casualty scheduling problem in the emergency recovery stage of post-earthquake relief could be integrated with our study to further enhance the research value of this paper.

Considering the facility disruption in advance is beneficial to treat more patients. Considering the facility disruption in the design stage of the emergency logistics network can improve the reliability of the system.

(1) The authors propose a new casualty scheduling optimisation problem based on GCCP in the early stage of post-earthquake relief. The proposed problem considers many new characteristics in this stage. To the best of the authors' knowledge, the authors are the first to use the GCCP to study the casualty scheduling problem under the grey information. (2) A MINP model is established to formulate the proposed problem. (3) An improved integer-encoded particle swarm optimisation (PSO) algorithm embedded grey simulation technique is designed in this paper.

The purpose of this paper is to establish a maturity evaluation model for the application of construction steel structure welding robotics suitable for the actual situation and specific characteristics of engineering projects in China and then to assess the maturity level of the technology in the application of domestic engineering projects more scientifically.

The research follows a qualitative and quantitative analysis method. In the first stage, the structure of the maturity model is constructed and the evaluation index system is designed by using the ideas of the capability maturity model and WSR methodology for reference. In the second stage, the design of the evaluation process and the selection of evaluation methods (analytic hierarchy process method, multi-level gray comprehensive evaluation method). In the third stage, the data are collected and organized (preparation of questionnaires, distribution of questionnaires, questionnaire collection). In the fourth stage, the established maturity evaluation model is used to analyze the data.

The evaluation model established by using multi-level gray theory can effectively transform various complex indicators into an intuitive maturity level or score status. The conclusion shows that the application maturity of building steel structure welding robot technology in this project is at the development level as a whole. The maturity levels of “WuLi – ShiLi – RenLi” are respectively: development level, development level, between starting level and development level. Comparison of maturity evaluation values of five important factors (from high to low): environmental factors, technical factors, management factors, benefit factors, personnel and group factors.

In this paper, based on the existing research related to construction steel structure welding robot technology, a quantitative and holistic evaluation of the application of construction steel structure welding robot technology in domestic engineering projects is conducted for the first time from a project perspective by designing a maturity evaluation index system and establishing a maturity evaluation model. This research will help the project team to evaluate the application level (maturity) of the welding robot in the actual project, identify the shortcomings and defects of the application of this technology, then improve the weak links pertinently, and finally realize the gradual improvement of the overall application level of welding robot technology for building steel structure.