Search results

1 – 10 of 462
To view the access options for this content please click here
Article
Publication date: 7 August 2017

Ke Zhang, Qiupin Zhong and Yuan Zuo

The purpose of this paper is to overcome the shortcomings of existing multivariate grey incidence models that cannot analyze the similarity of behavior matrixes.

Abstract

Purpose

The purpose of this paper is to overcome the shortcomings of existing multivariate grey incidence models that cannot analyze the similarity of behavior matrixes.

Design/methodology/approach

First, the feasibility of using gradient to measure the similarity of continuous functions is analyzed theoretically and intuitively. Then, a grey incidence degree is constructed for multivariable continuous functions. The model employs the gradient to measure the local similarity, as incidence coefficient function, of two functions, and combines local similarity into global similarity, as grey incidence degree by double integral. Third, the gradient incidence degree model for behavior matrix is proposed by discretizing the continuous models. Furthermore, the properties and satisfaction of grey incidence atom of the proposed model are research, respectively. Finally, a financial case is studied to examine the validity of the model.

Findings

The proposed model satisfies properties of invariance under mean value transformation, multiple transformation and linear transformation, which proves it is a model constructed from similarity perspective. Meanwhile, the case study shows that proposed model performs effectively.

Practical implications

The method proposed in the paper could be used in financial multivariable time series clustering, personalized recommendation in e-commerce, etc., when the behavior matrixes need to be analyzed from trend similarity perspective.

Originality/value

It will promote the accuracy of multivariate grey incidence model.

Details

Grey Systems: Theory and Application, vol. 7 no. 2
Type: Research Article
ISSN: 2043-9377

Keywords

To view the access options for this content please click here
Article
Publication date: 8 August 2008

Mahdi Fadaee Khorasgani

Higher education has a vital role to play in shaping the way in which future generations learn to cope with the complexities of sustainable development. Universities and…

Abstract

Purpose

Higher education has a vital role to play in shaping the way in which future generations learn to cope with the complexities of sustainable development. Universities and higher education institutions educate highly qualified graduates and responsible citizens able to meet the needs of all sectors of human activity; they provide opportunities for higher learning and for learning throughout life; they advance, create and disseminate knowledge through research and provide, as part of their service to the community, relevant expertise to assist societies in cultural, social and economic development; they contribute to the development and improvement of education at all levels, including through the training of teachers. The objective of this study is to examine the relationship between higher education and economic growth in Iran.

Design/methodology/approach

First, a baseline survey analysis of Iran supported by tables and figures was conducted. Secondly, by using multivariable time series data on the variables: annual logarithmic gross domestic product, physical capital (K), human capital, research expenditures (R) and by using an autoregressive distributed lag (ARDL) model, the long‐ and short‐run relationship between the growth and higher education variable was investigated. The following steps were followed: test of a dynamic ARDL model, CUSUM and CUSUMQ test for stability, long‐run relationship and ECM test.

Findings

The results indicated that the higher education variable had a positive effect on the economic growth of Iran in both the short and long run.

Originality/value

The research in this paper has implications for government policy makers responsible for investment in higher education.

Details

Education, Business and Society: Contemporary Middle Eastern Issues, vol. 1 no. 3
Type: Research Article
ISSN: 1753-7983

Keywords

To view the access options for this content please click here
Article
Publication date: 23 January 2009

Lihui Geng, Tao Zhang, Deyun Xiao and Jingyan Song

The purpose of this paper is to propose an identification algorithm to obtain generalized attitude model (GAM) of satellites in on‐orbit environment, which includes…

Abstract

Purpose

The purpose of this paper is to propose an identification algorithm to obtain generalized attitude model (GAM) of satellites in on‐orbit environment, which includes missing attitude data and multi‐noise. The identified GAM and noise model are the basis of attitude control and state estimation on‐orbit.

Design/methodology/approach

To cope with noises contaminating both input and output of attitude model, the errors‐in‐variables model is transformed into a traditional Box‐Jenkins model according to the attitude control loop. The wavelet denoising (WD) technique is helpful to predict the missing output data using the identified GAM.

Findings

By the numerical simulation, it is verified that the proposal accompanied with WD has a faster prediction capability than that of the algorithm without WD. As a result, the proposed approach is suitable to attitude model identification of on‐orbit satellites.

Originality/value

This identification algorithm can deal with two kinds of on‐orbit conditions and has a fast parameter convergent rate. Therefore, it has a practical application value in on‐orbit environment.

Details

Aircraft Engineering and Aerospace Technology, vol. 81 no. 2
Type: Research Article
ISSN: 0002-2667

Keywords

To view the access options for this content please click here
Article
Publication date: 28 June 2021

Jue Wang and Wuyong Qian

The purpose of this study is to make a prediction of the R&D output of China from the perspective of R&D institutions and put forward a set of policy recommendations for…

Abstract

Purpose

The purpose of this study is to make a prediction of the R&D output of China from the perspective of R&D institutions and put forward a set of policy recommendations for further development of the science and technology in China.

Design/methodology/approach

In this paper, an improved discrete grey multivariable model is proposed, which takes both the interaction effects and the accumulative effects into account. As the current research on China's R&D activities is generally based on the perspective of universities or industrial enterprises above designated size while few studies put their focus on R&D institutions, this paper applies the proposed model to carry out an empirical analysis based on the data of China's R&D institutions from 2009 to 2019. The prediction results from the new model are then compared with three existing approaches and the comparison results indicate that the proposed model generally outperforms existing methods. A further prediction of the R&D output in China's R&D institutions is conducted into a future horizon from 2020 to 2023 by using the model.

Findings

The results indicate that China's R&D institutions have a good development trend and broad prospects, which is closely related to China's long-term investment in science and technology. Additionally, the R&D inputs of China possess obvious interaction effects and accumulative effects.

Originality/value

The paper considers the interaction effects and the accumulative effects of R&D inputs simultaneously and proposes an improved discrete grey multivariable model, which fills the gap in previous studies.

Details

Kybernetes, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0368-492X

Keywords

To view the access options for this content please click here
Article
Publication date: 21 June 2019

Hang Jiang, Yi-Chung Hu, Jan-Yan Lin and Peng Jiang

With the development of economy, China’s OFDI constantly increase in recent year. Meanwhile, OFDI has spillover effect on economic development and technological…

Abstract

Purpose

With the development of economy, China’s OFDI constantly increase in recent year. Meanwhile, OFDI has spillover effect on economic development and technological development of home country. Thus, accurate OFDI prediction is a prerequisite for the effective development of international investment strategies. The purpose of this paper is to predict China’s OFDI accurately using a novel multivariable grey prediction model with Fourier series.

Design/methodology/approach

This paper applied a multivariable grey prediction model, GM(1,N), to forecast China’s OFDI. In order to improve the prediction accuracy and without changing local characteristics of grey model prediction, this paper proposed a novel grey prediction model to improve the performance of the traditional GM(1,N) model by combining with residual modification model using GM(1,1) model and Fourier series.

Findings

The coefficients indicate that the export and GDP have positive influence on China’s OFDI, and, according to the prediction result, China’s OFDI shows a growing trend in next five years.

Originality/value

This paper proposed an effective multivariable grey prediction model that combined the traditional GM(1,N) model with a residual modification model in order to predict China’s OFDI. Accurate forecasting of OFDI provides reference for the Chinese Government to implement international investment strategies.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 12 no. 3
Type: Research Article
ISSN: 1756-378X

Keywords

To view the access options for this content please click here
Article
Publication date: 4 May 2021

Sandang Guo, Yaqian Jing and Bingjun Li

The purpose of this paper is to make multivariable gray model to be available for the application on interval gray number sequences directly, the matrix form of interval…

Abstract

Purpose

The purpose of this paper is to make multivariable gray model to be available for the application on interval gray number sequences directly, the matrix form of interval multivariable gray model (IMGM(1,m,k) model) is constructed to simulate and forecast original interval gray number sequences in this paper.

Design/methodology/approach

Firstly, the interval gray number is regarded as a three-dimensional column vector, and the parameters of multivariable gray model are expressed in matrix form. Based on the dynamic gray action and optimized background value, the interval multivariable gray model is constructed. Finally, two examples and comparisons are carried out to verify the effectiveness of IMGM(1,m,k) model.

Findings

The model is applied to simulate and predict expert value, foreign direct investment, automobile sales and steel output, respectively. The results show that the proposed model has better simulation and prediction performance than another two models.

Practical implications

Due to the uncertainty information and continuous changing of reality, the interval gray numbers are used to characterize full information of original data. And the IMGM(1,m,k) model not only considers the characteristics of parameters changing with time but also takes into account information on lower, middle and upper bounds of interval gray numbers simultaneously to make better suitable for practical application.

Originality/value

The main contribution of this paper is to propose a new interval multivariable gray model, which considers the interaction between the lower, middle and upper bounds of interval numbers and need not to transform interval gray number sequences into real sequences. According to combining different characteristics of each bound of interval gray numbers, the matrix form of interval multivariable gray model is established to simulate and forecast interval gray numbers. In addition, the model introduces dynamic gray action to reflect the changes of parameters over time. Instead of white equation of classic MGM(1,m), the difference equation is directly used to solve the simulated and predicted values.

Details

Grey Systems: Theory and Application, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2043-9377

Keywords

To view the access options for this content please click here
Article
Publication date: 2 October 2018

Liang Zeng

High-tech industries play an important role in promoting economic and social development. The purpose of this paper is to accurately predict and analyze the output value…

Abstract

Purpose

High-tech industries play an important role in promoting economic and social development. The purpose of this paper is to accurately predict and analyze the output value of high-tech products in Guangdong Province, China, by using a multivariable grey model.

Design/methodology/approach

Based on the principle of fractional order accumulation, this study proposes a multivariable grey prediction model. To further enhance the prediction ability and accuracy of the model, an optimized model is established by reconstructing the background value. The optimal parameters are solved by minimizing the average relative error of the system characteristic sequence with the constraint of parameter relationships.

Findings

The results from the study show that the two proposed models exhibit better simulation and prediction performance than the traditional models, while the optimized model can significantly improve the modelling precision. In addition, it is predicted that the output value of high-tech products is 12,269.443bn yuan in 2021, which will approximately double from 2016 to 2021.

Research limitations/implications

The two proposed models can be used to forecast the trend of the system and are grown as an effective extension and supplement of the traditional multivariable grey forecasting models.

Practical implications

The forecast and analysis of the development prospects of high-tech industries would be useful for the government departments of Guangdong Province and professional forecasters to grasp the future of high-tech industries and formulate decision planning.

Originality/value

A new multivariable grey prediction model based on fractional order accumulation and its optimized model obtained by reconstructing the background value, which can improve the modelling accuracy of the traditional model, is proposed in this paper.

Details

Kybernetes, vol. 48 no. 6
Type: Research Article
ISSN: 0368-492X

Keywords

Content available
Article
Publication date: 3 September 2020

Zhaosu Meng, Xiaotong Liu, Kedong Yin, Xuemei Li and Xinchang Guo

The purpose of this paper is to examine the effectiveness of an improved dummy variables control grey model (DVCGM) considering the hysteresis effect of government…

Abstract

Purpose

The purpose of this paper is to examine the effectiveness of an improved dummy variables control grey model (DVCGM) considering the hysteresis effect of government policies in China's energy intensity (EI) forecasting.

Design/methodology/approach

Energy consumption is considered as an important driver of economic development. China has introduced policies those aim at the optimization of energy structure and EI. In this study, EI is forecasted by an improved DVCGM, considering the hysteresis effect of energy-saving policies of the government. A nonlinear optimization method based on particle swarm optimization (PSO) algorithm is constructed to calculate the hysteresis parameter. A one-step rolling mechanism is applied to provide input data of the prediction model. Grey model (GM) (1, N), DVCGM (1, N) and ARIMA model are applied to test the accuracy of the improved DVCGM (1, N) model prediction.

Findings

The results show that the improved DVCGM provides reliable results and works well in simulation and predictions using multivariable data in small sample size and time-lag virtual variable. Accordingly, the improved DVCGM notes the hysteresis effect of government policies and significantly improves the prediction accuracy of China's EI than the other three models.

Originality/value

This study estimates the EI considering the hysteresis effect of energy-saving policies in China by using an improved DVCGM. The main contribution of this paper is to propose a model to estimate EI, considering the hysteresis effect of energy-saving policies and improve forecasting accuracy.

Details

Grey Systems: Theory and Application, vol. 11 no. 3
Type: Research Article
ISSN: 2043-9377

Keywords

Content available
Article
Publication date: 8 May 2018

Grace Wang, Qingcheng Zeng and Lawrence Cliff Ghoram

In the USA, the cruise industry has generated more than $42bn in total economic activities, involving over 356,000 jobs. The largest and most aggressive operator is…

Abstract

Purpose

In the USA, the cruise industry has generated more than $42bn in total economic activities, involving over 356,000 jobs. The largest and most aggressive operator is acknowledged as Carnival Cruise Line (CCL), with a 48.3 per cent market share including all subsidiary companies in 2013. CCL has had a strong track record of reliability and high quality; however, within the past decade, there have been several deviations from standard daily procedure that have altered the way CCL does business. When trying to interpret changes in company performance, it is important to include other factors that may have contributed to changes at the time of any given deviation.

Design/methodology/approach

The authors use time series empirical mode decomposition to visualize whether there are short- or long-term shocks to company performance in the wake of deviating events. Besides, a thorough analysis is carried out with multivariable linear regression to identify the factors that really impact CCL’s performance.

Findings

This case study shows the seasonal patterns of weather issues with the largest number of hurricanes and tropical storms taking place during the third quarter of each year.

Originality/value

Empirical results will enhance understanding of the industry with regard to such events. It will provide shareholders information and opinions to enhance their decision-making processes.

Details

Maritime Business Review, vol. 3 no. 1
Type: Research Article
ISSN: 2397-3757

Keywords

To view the access options for this content please click here
Article
Publication date: 1 October 1971

THROUGHOUT history certain decades emerge which are of cardinal import to mankind, like the one beginning in 1781, when the inventions of fifty years reached their apogee…

Abstract

THROUGHOUT history certain decades emerge which are of cardinal import to mankind, like the one beginning in 1781, when the inventions of fifty years reached their apogee and through general application transformed the prevailing cottage industry into what we now call the factory system. That vast accretion of resources changed the human environment.

Details

Work Study, vol. 20 no. 10
Type: Research Article
ISSN: 0043-8022

1 – 10 of 462