Search results

The purpose of this paper is to compare GM(1,1) model, rolling GM(1,1) model and metabolism GM(1,1) model included in the GM(1,1) model cluster and use these models to forecast global oil consumption.

Simulated sequences will be generated randomly, and used to test the models included in the GM(1,1) model cluster; and these grey forecasting models are applied to forecast global oil consumption.

Effectiveness of these grey forecasting models is proved by random experiments, which explains the model adaptability. Global oil consumption is predicted, and it shows that global oil consumption will increase at a rather big growth rate in the next years.

The effectiveness of medium-term prediction of these grey forecasting models is analyzed by random experiments. These models are compared, and some basis for model selection is obtained.

The purpose of this paper is to clarify several commonly used quality cost models based on Juran’s characteristic curve. Through mathematical deduction, the lowest point of quality cost and the lowest level of quality level (often depicted by qualification rate) can be obtained. This paper also aims to introduce a new prediction model, namely discrete grey model (DGM), to forecast the changing trend of quality cost.

This paper comes to the conclusion by means of mathematical deduction. To make it more clear, the authors get the lowest quality level and the lowest quality cost by taking the derivative of the equation of quality cost and quality level. By introducing the weakening buffer operator, the authors can significantly improve the prediction accuracy of DGM.

This paper demonstrates that DGM can be used to forecast quality cost based on Juran’s cost characteristic curve, especially when the authors do not have much information or the sample capacity is rather small. When operated by practical weakening buffer operator, the randomness of time series can be obviously weakened and the prediction accuracy can be significantly improved.

This paper uses a real case from a literature to verify the validity of discrete grey forecasting model, getting the conclusion that there is a certain degree of feasibility and rationality of DGM to forecast the variation tendency of quality cost.

This paper perfects the theory of quality cost based on Juran’s characteristic curve and expands the scope of application of grey system theory.

The purpose of this paper is to study the modelling mechanisms of several grey incidence analysis models with great influence, including Deng’s grey incidence model, absolute degree of grey incidence model, slope degree of incidence model, similitude degree of incidence model and closeness degree of incidence model; then analyse the problems to be solved in grey incidence analysis models; and clarify the applicable ranges of commonly used grey incidence models.

The paper comes to conclusions by means of comparable analysis. The authors compare several commonly used grey incidence analysis models, including Deng’s grey incidence model, absolute degree of grey incidence model, slope degree of incidence model, similitude degree of incidence model and closeness degree of incidence model and give several examples to clarify the reasons why quantitative analysis results of different models are not exactly the same.

As the intension of each kind of incidence model is clear and the extension is relatively obscure, grey incidence orders calculated by different incidence models are often different. When making actual decisions, incompatible results may appear. According to different characteristics of extraction, grey incidence analysis models can be divided into three types: incidence model based on closeness perspective, incidence model based on similarity perspective and incidence model based on comprehensive perspective.

The conclusions obtained in this paper can help people avoid some defects in the process of actual selection and choose the better incidence analysis model.

The conclusions can be used as a reference and basis for the selection of grey incidence analysis models, it can help to overcome the defects and shortcomings of models caused by themselves and screen out more excellent analytical models.

The improved classical model makes it possible that the evaluation strategy has an optimal tendency, which reveals the purpose of this paper is to facilitate the first price sealed-bid auction more in line with the actual situation. To be more specific, there are several merits in the improvement process. On the one hand, the bid-winning probability can be improved for the bidder; on the other hand, the real market value of the subject matter can be more clearly recognized for the employer.

Bayesian estimation and grey system theory are referenced in this paper, with the use of double-parameter estimation, little historical data and expert experience. Specific implementation steps are as follows: first of all, using the double-parameter Bayesian estimation to correct the actual valuation of the bid matter v, then introducing the threat factor grey number R in the auction model, giving the improving of the optimal grey quotation and grey expectation utility under the two-party game and finally taking the aerospace component procurement as an example, simulating the bidding process of the bidding parties to arrive at the optimal bid strategy.

The improved model shows that the optimal strategy will change with the threat factor rather than a fixed value. When the threat factor grey number R follows [0.4, 0.6], the optimal quotation strategy will appear, which means quotation is higher than 50% of the bid matter's valuation.

The improved model proposed in this paper can strengthen the cost control in the Chinese commercial space process and optimize the pricing strategy for the final launch.

The modified model changes the habit that the bidder's valuation of the bid subject to mainly come from experience and to prompt the model for making full use of little historical data on the foundation of the former. It can reduce the subjective judgment error in the game results; finally, the practical cases are simulated in MATLAB at the same time, and the simulation effect is good, so we can get some more realistic conclusions on this basis.

The purpose of this paper is to present the terms of grey numbers and its operations.

The definitions of elementary terms about grey numbers and its operations are presented one by one.

The reader could know the basic explanation about the important terms about grey numbers and its operations from this paper.

Many of the 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 the universal principles of grey system theory.

The purpose of this paper is to establish the algorithm rules of the interval grey numbers and propose a new ranking method of the interval grey numbers.

The definitions of “kernels” based on lower measure, upper measure or moderate measure are given according to the properties of the interval grey number problems. By means of the measurement error, the concept of the absolute degree of greyness and the relative degree of greyness corresponding to different “kernel” are given, and different simplified forms of the interval grey numbers are put forward.

The definitions of “kernel” and the degree of greyness in this paper not only take the upper limit, lower limit and the coverage of the interval grey numbers into account, but also avoid the inconsistency of the degree of greyness caused by the different universe of discourse.

Though the method proposed in this paper has some deficiencies, such as the definition of relative degree of greyness is meaningless when the kernel of the interval grey number is 0, it provides a new idea for calculating and sorting the interval grey numbers and is conducive to the further development of the grey system theory.

The method proposed in this paper can not only distinguish interval grey numbers in different situations, but also avoid the inconsistency of the degree of greyness caused by the different universe of discourse. In this basis, the interval grey number algorithm is established and a new ranking method of interval grey numbers is given.

This paper aims to optimize the air pressure regulation scheme of the aeroengine pressure test bench.

Based on the requirements of pressure regulation process and the operating mechanism of aeroengine pressure test bench, a grey performance evaluation index system is constructed. The combination of principal component analysis and grey theory is employed to assign weights to grey indexes. The grey target evaluation model is introduced to evaluate the performance of historical regulation processes, and the evaluation results are analyzed to derive optimization mechanism for pressure regulating schemes.

A case study based on monitoring data from nearly 300 regulation processes verifies the feasibility of the proposed method. On the one hand, the improved principal component analysis method can achieve rational weighting for grey indexes. On the other hand, the method comparison intuitively shows that the proposed method performs better.

The pressure test bench is a fundamental technical equipment in the aviation industry, serving the development and testing of aircraft engines. Due to the complex system composition, the pressure and flow adjustment of the test bench heavily rely on manual experience, leading to issues such as slow adjustment speed and insufficient accuracy. This paper proposes a performance evaluation method for the regulation process of pressure test bench, which can draw knowledge from historical regulation processes, provide guidance for the pressure regulation of test benches, and ultimately achieve the goal of reducing equipment operating costs.

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 research is to provide a theoretical framework for complex equipment quality risk evaluation. The primary aim of the framework is to enhance the ability to identify risks and improve risk control efficiency during the development phase.

A novel framework for quality risk evaluation in complex equipment is proposed, which integrates probabilistic hesitant fuzzy set-quality function deployment (PHFS-QFD) and grey clustering. PHFS-QFD is applied to identify the quality risk factors, and grey clustering is used to evaluate quality risks in cases of poor quality information during the development stage. The unfolding function of QFD is applied to simplify complex evaluation problems.

The methodology presents an innovative approach to quality risk evaluation for complex equipment development. The case analysis demonstrates that this method can efficiently evaluate the quality risks for aircraft development and systematically trace back the risk factors through hierarchical relationships. In comparison to traditional failure mode and effects analysis methods for quality risk assessment, this approach exhibits superior effectiveness and reliability in managing quality risks for complex equipment development.

This study contributes to the field by introducing a novel theoretical framework that combines PHFS-QFD and grey clustering. The integration of these approaches significantly improves the quality risk evaluation process for complex equipment development, overcoming challenges related to data scarcity and simplifying the assessment of intricate systems.