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This paper aims to implement quality of service(QoS) dynamic optimization for the integrated satellite-terrestrial network(STN) of the fifth-generation Inmarsat system(Inmarsat-5).

The structure and operational logic of Inmarsat-5 STN are introduced to build the graphic evaluation and review technique(GERT) model. Thus, the equivalent network QoS metrics can be derived from the analytical algorithm of GERT. The center–point mixed possibility functions of average delay and delay variation are constructed considering users' experiences. Then, the grey clustering evaluation of link QoS is obtained combined with the two-stage decision model to give suitable rewards for the agent of GERT-Q-learning, which realizes the intelligent optimization mechanism under real-time monitoring data.

A case study based on five time periods of monitoring data verifies the adaptability of the proposed method. On the one hand, grey clustering based on possibility function enables a more effective measurement of link QoS from the users' perspective. On the other hand, the method comparison intuitively shows that the proposed method performs better.

With the development trend of integrated communication, STN has become an important research object in satellite communications. This paper establishes a modular and extensible optimization framework whose loose coupling structure and flexibility facilitate management and development. The grey-clustering-based GERT-Q-Learning model has the potential to maximize design and application benefits of STN throughout its life cycle.

The purpose of this paper is to present the terms of grey clustering evaluation models.

The definitions of basic terms about grey clustering evaluation models are presented one by one.

The reader could know the basic explanation about the important terms about various grey clustering evaluation models from this paper.

Many of the authors’ colleagues thought that unified definitions of key terms would be beneficial for both the readers and the authors.

It is a fundamental work to standardise all the definitions of terms for a new discipline. It is also propitious to spread and universal of grey system theory.

The purpose of this paper is to present a novel synthetic index of two counts and mathematical model for researcher evaluation.

A synthetic index L for researcher evaluation considering both the total number of other citations (C) and nonacademic impact (I) and a synthetic evaluation model are proposed in this paper. C and I are verified impact indexes. According to investigation by Delphi method, researchers are divided into five different classes of “below average,” “average,” “good,” “excellent” and “stellar.” The threshold values for counts C of grey class “stellar” are determined by deep investigation. The possibility functions of the two counts C and I on four grey classes of “below average,” “average,” “good” and “excellent” are built.

The novel synthetic index of two counts and mathematical model for researcher evaluation provide a better way to conduct researcher assessment.

The synthetic index L presented in this paper can be used to evaluate a researcher. It's more reasonable than the current research assessment indexes such as the number of publications and the numbers of so-called high-quality journal publications and the amount of granted funds and so on. The synthetic index L reflects the actual value created by a researcher. No artificial maneuver can change them significantly.

A synthetic index L for researcher evaluation considering both the total number of other citations (C) and nonacademic impact (I) and a synthetic evaluation model are proposed in this paper.

The purpose of this paper is to construct a grey clustering evaluation model based on center-point mixed possibility function and to evaluate the tourism development potential of tea intangible cultural heritage. The research results provide a certain reference for the tourism development department and related researchers who are engaged in the tourism development of intangible cultural heritage.

The study uses literature research, questionnaire investigation, expert interviews and factor analysis to determine the evaluation index system of tourism development potential of tea intangible cultural heritage and applies analytic hierarchy process (AHP) to determine the weight of each criteria. Then, according to the grey clustering evaluation theory and two-stage decision model, a grey clustering evaluation model is constructed to assess the tourism development potential of tea intangible cultural heritage. Finally, a new model is employed to evaluate the tourism development potential of tea intangible cultural heritage in Huangshan city.

The results show that there is a big difference in the tourism development potential of different tea intangible cultural heritages in Huangshan City and it further illustrates the scientificity and rationality of the method proposed in this paper.

The model constructed in the paper can be effectively applied to the evaluation of tourism development potential of tea intangible cultural heritage scientifically and reasonably.

This manuscript not only constructs the evaluation index system of tourism development potential of tea intangible cultural heritage but also creatively applies the grey clustering theory to the evaluation of tourism development potential of tea intangible cultural heritage, which provides a new research idea for the evaluation of tourism development potential of tea intangible cultural heritage.

The purpose of this paper is to solve the dilemma in the process of major selection decision-making.

Firstly, the group of weight vector with kernel has been defined. Then, the weighted comprehensive clustering coefficient vector was calculated based on the group of weight vector with kernel. Under the action of weighted comprehensive clustering coefficient vector, the information including in other components around component k and supporting object i to be classified into the k-th category has been gathered to component k. At last, a novel two-stage decision model based on the group of weight vector with kernel and the weighted comprehensive clustering coefficient vector is put forward to solve the dilemma in grey clustering evaluation. Then the overall evaluation conclusion can be consistent with the clustering result according to the rule of maximum value.

A new way to solve the dilemma in the process of major selection decision-making has been found. People can obtain a consistent result with two-stage decision model at the case of dilemma. That is, the conclusion of the overall evaluation is consistent with the clustering result according to the rule of maximum value.

Several functional groups of weight vector with kernel have been put forward. The proposed model can solve the clustering dilemma effectively and produce consistent results. A practical application of decision problem to solve the dilemma in supplier evaluation and selection of a key component of large commercial aircraft C919 have been completed by the novel two-stage decision model.

The two-stage decision model, the group of weight vector with kernel and the weighted comprehensive clustering coefficient vector were presented in this paper firstly. People can solve the dilemma in grey clustering evaluation effectively by the novel two-stage decision model based on the group of weight vector with kernel and the weighted comprehensive clustering coefficient vector.

The technical level of aircraft failure analysis plays a special role in ensuring the safety of civil aviation flight. Using appropriate methods for functional failures analysis can provide a reliable reference for aircraft safety. The purpose of this paper is to provide a new and comprehensive measure based on conventional functional hazard analysis (FHA) and grey system theory to analysis and evaluate the class that each failure belongs to.

This paper integrates multiple methods including the FHA, the fixed weight cluster, the Delphi method and the analytic hierarchy process (AHP). To begin with, use FHA method to sort out the corresponding failure states of a certain system from the perspective of function and determine the evaluation index. And then using group decision and AHP, determine the expert weight and index weight in the fixed weight cluster. The fixed weight cluster function is used to determine the grey class to which a certain functional failure belongs in the complex system.

In the past, the risk assessment of aircraft was mostly dominated by the subjective judgment of the experts, but it was not possible to give an objective observation score for each failure state. This paper addresses the problem efficiently as well as the feature of “little data, poor information.” The risk degree of each failure state can ultimately be replaced by a quantitative value.

This paper uses the idea of clustering in grey system theory to evaluate the risk of landing gear system. In the expert evaluation stage, different experts evaluated the impact degree of the aircraft's failure caused by its functions, so the final risk classification is subjective to some extent.

This study analyzed the different conditions of the landing gear, including the front wheel steering, front wheel damping, front wheel steering system, brake system fault information and so on. It can effectively divide the different failure states and their effects, which is helpful to improve the safety of aircraft landing gear system and provide some useful methods and ideas for studying the safety of aircraft systems.

Based on the FHA analysis process and the grey system theory, this paper determines various potential risks and their consequences of various functions according to the hierarchy, so as to carry out further detailed analysis on the risks that may occur under various functional conditions and take certain measures to prevent them. It is helpful to improve the risk management and control ability of aircraft in the actual flight process and to guarantee the safety of people's lives and property.

This paper is a pioneer in integrating the FHA method and the grey system theory, which exactly can be used to address the problem with the character of “little data, poor information.” The model established in this paper for the defects of FHA can effectively improve the accuracy of FHA, which is of great significance for the study of safety. In this paper, a case about landing gear system is given to illustrate the effectiveness of the model.

The purpose of this paper is to establish the index system of leading industries in Kashgar urban agglomeration, and use the multi-attribute weighted intelligent grey target decision-making evaluation model to measure the comprehensive effect, so as to select the leading industries of Kashgar urban agglomeration.

First, 18 industries in Kashgar urban agglomerations are taken as objectives, and four indexes, namely, demand income elasticity index, growth rate index, labor productivity growth rate index and contribution rate of output value, are selected to construct an evaluation system for leading industry selection in Kashgar urban agglomerations. Then, grey incidence degree method is used to determine the decision-making power of each decision-making objective. Finally, multi-attribute weighted intelligent grey target decision-making evaluation model is used to measure the comprehensive effect of the objective system of leading industries in Kashgar urban agglomerations.

It can be seen that the multi-attribute weighted intelligent grey target decision-making evaluation model is more convenient to be used in selecting regional leading industries, and the results are accurate and feasible. Based on the calculation results and the actual economic development requirements of Kashgar urban agglomeration, the leading industries of Kashgar urban agglomeration can be determined as: wood processing, furniture, paper making and printing; wholesale and retail; construction; equipment manufacturing; transportation, storage and postal services.

First, it is a new method in selecting regional leading industry by using the multi-attribute weighted intelligent grey target decision-making evaluation model. Second, since there is relatively little research on Kashgar urban agglomeration, especially on leading industries in Kashgar urban agglomeration. The research in this paper can not only enrich the research on selecting leading industries in urban agglomeration but also provide scientific reference for relevant government agencies to formulate economic development plans.

Response surface methodology (RSM) is used for optimality analysis of the cost coefficients in mixed integer linear programming. This optimality analysis goes beyond traditional sensitivity and parametric analysis in allowing investigation of the optimal objective function value response over pre‐specified ranges on multiple problem parameters. Design of experiments and least squares regression are used to indicate which cost coefficients have the greatest impact on the optimal total cost surface over the specified coefficient ranges. The mixed integer linear programming problems of interest are the large‐scale facility location and allocation problems in supply chain optimization. A system that automates this process for supply chain optimization at PFS Logistics Consulting is discussed and an example is presented.

The purpose of this paper is to summarize the progress in grey system research during 2000-2015, so as to present some important new concepts, models, methods and a new framework of grey system theory.

The new thinking, new models and new methods of grey system theory and their applications are presented in this paper. It includes algorithm rules of grey numbers based on the “kernel” and the degree of greyness of grey numbers, the concept of general grey numbers, the synthesis axiom of degree of greyness of grey numbers and their operations; the general form of buffer operators of grey sequence operators; the four basic models of grey model GM(1,1), such as even GM, original difference GM, even difference GM, discrete GM and the suitable sequence type of each basic model, and suitable range of most used grey forecasting models; the similarity degree of grey incidences, the closeness degree of grey incidences and the three-dimensional absolute degree of grey incidence of grey incidence analysis models; the grey cluster model based on center-point and end-point mixed triangular whitenization functions; the multi-attribute intelligent grey target decision model, the two stages decision model with grey synthetic measure of grey decision models; grey game models, grey input-output models of grey combined models; and the problems of robust stability for grey stochastic time-delay systems of neutral type, distributed-delay type and neutral distributed-delay type of grey control, etc. And the new framework of grey system theory is given as well.

The problems which remain for further studying are discussed at the end of each section. The reader could know the general picture of research and developing trend of grey system theory from this paper.

A lot of successful practical applications of the new models to solve various problems have been found in many different areas of natural science, social science and engineering, including spaceflight, civil aviation, information, metallurgy, machinery, petroleum, chemical industry, electrical power, electronics, light industries, energy resources, transportation, medicine, health, agriculture, forestry, geography, hydrology, seismology, meteorology, environment protection, architecture, behavioral science, management science, law, education, military science, etc. These practical applications have brought forward definite and noticeable social and economic benefits. It demonstrates a wide range of applicability of grey system theory, especially in the situation where the available information is incomplete and the collected data are inaccurate.

The reader is given a general picture of grey systems theory as a new model system and a new framework for studying problems where partial information is known; especially for uncertain systems with few data points and poor information. The problems remaining for further studying are identified at the end of each section.

In a volatile marketplace, warehouse management is fundamentally contingent of changes in its supply network environment. Flexibility is therefore a key logistics issue in distribution centre management. This study probes into the nature of warehouse flexibility in a supply network through simulation.

By using the FlexSim simulation tool the dynamic behaviour of the warehouse system are conceptualised, documented, simulated, analysed and evaluated.

Simulation revealed that external changes affect daily processes and the reorganisation of warehouse processes. Given the extensity of resource use, simulation also revealed that process reorganisation should not be a daily undertaking. This is because warehouse processes react in unpredictable and different manners to even the smallest disturbance from the environment. This reaction is not necessarily negative impending more long-term change of warehouse processes.

The warehouse is a complex system that self-adapts with limited need to calculate new optimised warehouse processes to counter changes in its environment. Rather than following deterministic optimisation procedures, the development of flexible resources is a key issue in warehouse management. The applied simulation model is generic and therefore applicable in other distribution centres pointing to how to monitor warehouse processes to in a pre-emptively develop warehouse flexibility through change of process context.