Nai-ming Xie, Song-Ming Yin and Chuan-Zhen Hu
The purpose of this paper is to study a new approach by combining a multilayer perceptron neural network (MLPNN) algorithm with a GM(1, N) model in order to estimate the…
Abstract
Purpose
The purpose of this paper is to study a new approach by combining a multilayer perceptron neural network (MLPNN) algorithm with a GM(1, N) model in order to estimate the development cost of a new type of aircraft.
Design/methodology/approach
First, data about developing costs and their influencing factors were collected for several types of Boeing and Airbus aircraft. Second, a GM(1, N) model was constructed to simulate development costs for a civil aircraft. Then, an MLPNN algorithm was added to optimize and revise the simulative and forecasting values. Finally, a combined approach, using both a GM(1, N) model and an MLPNN algorithm was adopted to forecast development costs for new civil aircraft.
Findings
The results show that the proposed approach could do the work of cost estimation for new types of aircraft. Rather than using a single model, the combined approach could improve simulative and forecasting accuracy.
Practical implications
Scientific cost estimation could improve management efficiency and promote the success of a new type of civil aircraft development. Considering that China’s civil aircraft research and development is at its very beginning stages, only very limited data could be collected. The development costs for civil aircraft are affected by a series of factors. The approach outlined by this paper could be applied to development cost estimations in China’s civil aircraft industry.
Originality/value
The paper has succeeded by constructing a cost estimation index system and proposing a novel combined cost estimation approach comprised of a GM(1, N) model and an MLPNN. It has undoubtedly contributed to improving the accuracy of cost estimations.
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This paper aims to construct a novel grey relational model based on grey number sequences and to solve the problems which exist in traditional grey relational models, in which the…
Abstract
Purpose
This paper aims to construct a novel grey relational model based on grey number sequences and to solve the problems which exist in traditional grey relational models, in which the uncertain information cannot be described.
Design/methodology/approach
Based on the definition of traditional grey relational models, considering the limited information and knowledge, the algorithm of grey numbers was combined with the grey relational model. A general formula of grey operations and grey distance is defined. A novel grey relational model based on grey number sequences, named grey geometrical relational model, is proposed according to the definition of grey distance. Finally, several properties including parallel, multiple and order‐keeping about the proposed model are discussed.
Findings
The results show that the novel grey relational model satisfies the properties properly. It is useful to calculate the relational degree of two different grey number sequences. And the process of calculating is easier than traditional grey relational models.
Practical implications
The method exposed in the paper can be used to calculate every two sequences. The method can also be used to rank sequences of more than two.
Originality/value
The paper succeeds in constructing a novel grey relational model. The properties of novel model are studied and it is a new development in grey systems theory undoubtedly.
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Si‐feng Liu, Nai‐ming Xie and Jeffrey Forrest
The purpose of this paper is to solve the problems existing in traditional grey incidence models and advance several new grey incidence models based on visual angle of similarity…
Abstract
Purpose
The purpose of this paper is to solve the problems existing in traditional grey incidence models and advance several new grey incidence models based on visual angle of similarity and nearness.
Design/methodology/approach
Based on the definition of traditional grey incidence models, two novel grey incidence models, grey similar incidence model and grey close incidence model, are studied in this paper. The interrelations and influence can be measured by the new models with different visual angle of similarity and/or nearness, respectively. The grey similar incidence model is used mainly to measure the similitude degree of the geometric patterns of sequence curves. The grey close incidence model is used mainly to measure the nearness of the sequence curves in space. The properties of the new models are discussed. It is proved that the proposed models are simplified methods to calculate the similitude degree and the close degree of grey incidence models.
Findings
The results show that the two novel grey incidence models satisfy the grey incidence axiom properly. It is useful to calculate the similitude degree and the close degree of two different sequences, and the process of calculating is easier than with traditional grey incidence models.
Practical implications
The method exposed in the paper can be used to calculate every two sequences. The similitude degree and the close degree of two different sequences can be given out. The method can also be used to rank sequences of more than two.
Originality/value
The paper succeeds in constructing two novel grey incidence models. The properties of novel model are studied and it is undoubtedly a new development in grey systems theory.
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The purpose of this paper is to redefine the concept of grey number with information background and to propose novel grey number algorithms.
Abstract
Purpose
The purpose of this paper is to redefine the concept of grey number with information background and to propose novel grey number algorithms.
Design/methodology/approach
As the basic element of a grey system, grey number is defined as a number of which the true value is unknown because of the limited information while the boundary or possible value set can be known. Grey number algorithms are key points for constructing grey system models and helping to calculate model results. The concept of grey number is redefined with information background in this paper. Novel grey number algorithms are defined considering all the different forms of grey number information background. Several illustrative examples are applied to state the process of the proposed algorithms.
Findings
The results show that the novel grey number algorithms can do the operations well no matter what the grey number's type. It is useful to create effective grey system models and to do system analysis, forecasting, decision making and control in grey systems.
Practical implications
The method exposed in the paper can be used to calculate different grey numbers and used in constructing new grey models.
Originality/value
The paper succeeds in defining new grey number algorithm. The concept and its remarks of grey number are discussed. The novel algorithm can be used in creating new grey models and solve the modelling parameters in of grey systems theory undoubtedly.
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The purpose of this paper is to study the parameters' properties of GM(n, h) model on the basis of multiple transformation and the relationship of GM(n, h) model and other grey…
Abstract
Purpose
The purpose of this paper is to study the parameters' properties of GM(n, h) model on the basis of multiple transformation and the relationship of GM(n, h) model and other grey models.
Design/methodology/approach
Multiple transformation property of parameters is important to construct a grey model. However, there is no research on the property of GM(n, h) model, therefore it is meaningful to study the relationship between GM(n, h) model and other grey models.
Findings
The multiple transformation property of parameters of GM(n, h) model is recognized. The parameters' value is dependent on multiple transformation value. The values of simulative and predicative are only dependent to the multiple transformation of the main variable and independent to other variables.
Research limitations/implications
The properties of other grey models could be obtained by analyzing the property of GM(n, h) model.
Practical implications
It is a very useful result for constructing a grey model.
Originality/value
This paper discusses multiple transformation property of GM(n, h) model and the relationship between the GM(n, h) model and other grey models. These grey models are put into a common model and the affections that parameters' multiple transformation caused to the model are studied.
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San-dang Guo, Sifeng Liu, Zhigeng Fang and Lingling Wang
The purpose of this paper is to put forward a multi-stage information aggregation method based on grey inspiriting control lines to evaluate the objects dynamically and…
Abstract
Purpose
The purpose of this paper is to put forward a multi-stage information aggregation method based on grey inspiriting control lines to evaluate the objects dynamically and comprehensively.
Design/methodology/approach
According to the evaluation value of the objects, the positive and negative incentive lines were set up and the predicted values were solved based on the grey GM(1, 1) model, so the value with expected information could be evaluated. In the evaluation, the part above the positive incentive line should be “rewarded” and that below the negative incentive line should be “punished” appropriately. Thereby the double incentive effects of “the current development situation and future development trend” to objects could be implemented on the basis of control.
Findings
This method can primarily describe the decision maker's expectancy of the development of evaluation objects and make the evaluation results have better practical application value.
Research limitations/implications
Many comprehensive evaluations were always based on the past information. However, the future development trend of the evaluated object is also very important. This study can be used in the evaluation for future application and development.
Originality/value
The paper succeeds in providing not only a method of multi-phase information aggregation with expectancy information, but also a simple and convenient method solving nonlinear inspiring lines objectively.
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Benhai Guo, Rongrong Zhang and Chaoqing Yuan
This paper attempts to study the impact of changing incentive strategies on enterprises' energy saving effort level and to construct an effective principal‐agent mechanism to…
Abstract
Purpose
This paper attempts to study the impact of changing incentive strategies on enterprises' energy saving effort level and to construct an effective principal‐agent mechanism to achieve Pareto improvement of energy‐saving control.
Design/methodology/approach
Starting from the benefit relations between government and enterprises as well as their game strategies in energy conservation management, the impact of changing incentive strategies on enterprises' energy saving effort level and the asymmetric information situation of the players are studied taking into consideration the angle of strategies evolving in local government. Also, an effective principal‐agent mechanism to achieve Pareto improvement of energy‐saving control is constructed.
Findings
The results are convincing: interests of both the principal and agent had consistency under the principal‐agent mechanism, and the principal‐agent model was a mechanism with rich efficiency that could substantially arouse the enthusiasm of enterprises in energy saving. The comprehensive supervision of local governments over enterprises could effectually eliminate ill effects on energy‐saving management caused by information asymmetry under certain circumstances.
Practical implications
It is good for locating the balance of interest of game players by building a government energy saving mechanism based on principal‐agent theory. Through solving a game stable strategy, it is beneficial to seize a key point of regulation and control policies.
Originality/value
The paper succeeds in analyzing decision behaviours of government and enterprises through the basic idea of cooperative game theory so as to make actions of enterprises at all levels agree to government determined solving of energy issues.