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Article
Publication date: 22 October 2019

Ye Li and Juan Li

The purpose of this paper is to construct an unbiased interval grey number prediction model with new information priority for dealing with the jumping errors from difference…

Abstract

Purpose

The purpose of this paper is to construct an unbiased interval grey number prediction model with new information priority for dealing with the jumping errors from difference equation to the differential equation in the prediction model of interval grey number.

Design/methodology/approach

First, this study obtains a set of linear equations about the model parameters by taking the minimum error sum of squares between the accumulative sequence and its simulation values as criterion, and solves them on the basis of the Crammer rule. Then, according to the new information priority principle, it selects the last number of the accumulated generation sequence as the initial value and gives the expression of the time response function by the recursive iteration method to establish the interval grey number prediction model.

Findings

This paper provides an unbiased interval grey number prediction model with new information priority, and the example analysis shows that the method proposed in this paper has higher prediction precision and practicality.

Research limitations/implications

If there is a better method to whiten the interval grey number, so as to fully tap the grey information contained in it, the accuracy of the model will be higher.

Practical implications

The model proposed in this paper can avoid the error caused by jumping from difference equation to differential equation and make full use of new information. It can be better used in a problem where new information has a great influence on prediction results.

Originality/value

This paper selects the last number of the accumulated generation sequence as the initial value and gives the expression of the time response function by the recursive iteration method. Then, it constructs an unbiased interval grey number prediction model with new information priority.

Details

Grey Systems: Theory and Application, vol. 10 no. 1
Type: Research Article
ISSN: 2043-9377

Keywords

Article
Publication date: 25 December 2023

Ran Wang, Yunbao Xu and Qinwen Yang

This paper intends to construct a new adaptive grey seasonal model (AGSM) to promote the application of the grey forecasting model in quarterly GDP.

Abstract

Purpose

This paper intends to construct a new adaptive grey seasonal model (AGSM) to promote the application of the grey forecasting model in quarterly GDP.

Design/methodology/approach

Firstly, this paper constructs a new accumulation operation that embodies the new information priority by using a hyperparameter. Then, a new AGSM is constructed by using a new grey action quantity, nonlinear Bernoulli operator, discretization operation, moving average trend elimination method and the proposed new accumulation operation. Subsequently, the marine predators algorithm is used to quickly obtain the hyperparameters used to build the AGSM. Finally, comparative analysis experiments and ablation experiments based on China's quarterly GDP confirm the validity of the proposed model.

Findings

AGSM can be degraded to some classical grey prediction models by replacing its own structural parameters. The proposed accumulation operation satisfies the new information priority rule. In the comparative analysis experiments, AGSM shows better prediction performance than other competitive algorithms, and the proposed accumulation operation is also better than the existing accumulation operations. Ablation experiments show that each component in the AGSM is effective in enhancing the predictive performance of the model.

Originality/value

A new AGSM with new information priority accumulation operation is proposed.

Details

Grey Systems: Theory and Application, vol. 14 no. 2
Type: Research Article
ISSN: 2043-9377

Keywords

Article
Publication date: 14 May 2020

Dang Luo, Muffarah Ambreen, Assad Latif and Xiaolei Wang

Electricity plays an important role in the economic condition of any country. Nowadays, Pakistan is badly affected by shortage of electricity, which directly affected the economic…

Abstract

Purpose

Electricity plays an important role in the economic condition of any country. Nowadays, Pakistan is badly affected by shortage of electricity, which directly affected the economic growth of state. The purpose of this study is to propose an improved grey model DGPM(1,1,N) to forecast Pakistan's production of electricity, installed capacity and consumption.

Design/methodology/approach

To significantly simulate and predict accuracy, the discrete grey polynomial model DGPM(1,1,N) is improved with new information priority accumulation. The particle swarm optimization (PSO) algorithm is used for parameter optimization. The value of parameter is adjusted into improved grey model. By adjusting the parameter value in the model, the accuracy of prediction is enhanced.

Findings

The installed capacity of electricity needs more attention to improvement through implementation of effective polices, resolving major issues and funding scheme to fulfill the electricity demand of country. And improved DGPM(1,1,N) has better accuracy than original DGPM(1,1,N), DGM(1,1), nongrey models, linear regression and Holt–Winters methods.

Practical implications

This paper provides a practical and efficient improved grey method to predict the electricity production, consumption and installed capacity in Pakistan. This research and suggestion will help Pakistani government to formulate better policies to decrease the consumption of electricity and increase the installed capacity of electricity.

Originality/value

This paper not only improves the grey model with accumulation generation operator but also forecasts Pakistan's electricity production, installed capacity and consumption. It is a new idea to predict the installed capacity of electricity and the findings provide suggestions for the government to make policies.

Details

Grey Systems: Theory and Application, vol. 10 no. 2
Type: Research Article
ISSN: 2043-9377

Keywords

Article
Publication date: 6 June 2023

Xuemei Zhao, Xin Ma, Yubin Cai, Hong Yuan and Yanqiao Deng

Considering the small sample size and non-linear characteristics of historical energy consumption data from certain provinces in Southwest China, the authors propose a hybrid…

Abstract

Purpose

Considering the small sample size and non-linear characteristics of historical energy consumption data from certain provinces in Southwest China, the authors propose a hybrid accumulation operator and a hybrid accumulation grey univariate model as a more accurate and reliable methodology for forecasting energy consumption. This method can provide valuable decision-making support for policy makers involved in energy management and planning.

Design/methodology/approach

The hybrid accumulation operator is proposed by linearly combining the fractional-order accumulation operator and the new information priority accumulation. The new operator is then used to build a new grey system model, named the hybrid accumulation grey model (HAGM). An optimization algorithm based on the JAYA optimizer is then designed to solve the non-linear parameters θ, r, and γ of the proposed model. Four different types of curves are used to verify the prediction performance of the model for data series with completely different trends. Finally, the prediction performance of the model is applied to forecast the total energy consumption of Southwest Provinces in China using the real world data sets from 2010 to 2020.

Findings

The proposed HAGM is a general formulation of existing grey system models, including the fractional-order accumulation and new information priority accumulation. Results from the validation cases and real-world cases on forecasting the total energy consumption of Southwest Provinces in China illustrate that the proposed model outperforms the other seven models based on different modelling methods.

Research limitations/implications

The HAGM is used to forecast the total energy consumption of the Southwest Provinces of China from 2010 to 2020. The results indicate that the HAGM with HA has higher prediction accuracy and broader applicability than the seven comparative models, demonstrating its potential for use in the energy field.

Practical implications

The HAGM(1,1) is used to predict energy consumption of Southwest Provinces in China with the raw data from 2010 to 2020. The HAGM(1,1) with HA has higher prediction accuracy and wider applicability compared with some existing models, implying its high potential to be used in energy field.

Originality/value

Theoretically, this paper presents, for the first time, a hybrid accumulation grey univariate model based on a new hybrid accumulation operator. In terms of application, this work provides a new method for accurate forecasting of the total energy consumption for southwest provinces in China.

Details

Grey Systems: Theory and Application, vol. 13 no. 4
Type: Research Article
ISSN: 2043-9377

Keywords

Article
Publication date: 19 August 2011

Dang Luo and Xia Wang

According to the basic principle of grey system and third axiom buffer operator, aiming at the problem of disturbance, some new weakening buffer operators are established by…

217

Abstract

Purpose

According to the basic principle of grey system and third axiom buffer operator, aiming at the problem of disturbance, some new weakening buffer operators are established by analytical skills in the process of prediction. The problem of some contradictions between quantitative analysis and qualitative analysis existing in pretreatment for vibration data sequences is resolved effectively. An example shows that the kind of new weakening buffer operators increase the forecast precision of data forecast model remarkably. The aim of this paper is to attempt to resolve the problem of some contradictions between quantitative analysis and qualitative analysis existing in pretreatment for vibration data sequences.

Design/methodology/approach

In view of the problem of some contradictions between quantitative analysis and qualitative analysis existing in pretreatment for vibration data sequences, according to the basic principle of grey system and third axiom buffer operator, some new weakening buffer operators are established by analytical skills. As an example, the kind of new weakening buffer operators can increase the forecast precision of data forecast model remarkably.

Findings

The results show that the new weakening buffer operators can increase the forecast precision of data forecast model remarkably.

Practical implications

The new weakening buffer operators exposed in the paper can be used to resolve the problem of some contradictions between quantitative analysis and qualitative analysis existing in pretreatment for vibration data sequences and increase the forecast precision of data forecast model remarkably.

Originality/value

The paper succeeds in increasing the forecast precision of data forecast model remarkably.

Details

Grey Systems: Theory and Application, vol. 1 no. 2
Type: Research Article
ISSN: 2043-9377

Keywords

Book part
Publication date: 3 February 2015

Robert Gannon, Karen M. Hogan and Gerard T. Olson

New Technology Business Firms are known to be volatile dynamic organizations whose innovations are subject to short life cycles and product imitability. Venture capitalist firms…

Abstract

New Technology Business Firms are known to be volatile dynamic organizations whose innovations are subject to short life cycles and product imitability. Venture capitalist firms who allocate funds to these start-ups need to evaluate multiple facets associated with the individual firm’s internal and external characteristics, as well as, its own unique objectives and goals. This study applies a multicriteria decision making model to the identification for venture capital firms of potential New Technology Business Firms who are requesting capital infusions.

Details

Applications of Management Science
Type: Book
ISBN: 978-1-78441-211-1

Keywords

Article
Publication date: 7 November 2016

Sifeng Liu, Yingjie Yang, Jeffrey Forrest and Handan Rui

The purpose of this paper is to present the terms of concepts and fundamental principles of grey systems.

Abstract

Purpose

The purpose of this paper is to present the terms of concepts and fundamental principles of grey systems.

Design/methodology/approach

The definitions of basic terms about concepts and fundamental principles of grey systems are presented one by one.

Findings

The reader could know the basic explanation about the important terms about concepts and fundamental principles of grey systems from this paper.

Practical implications

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

Originality/value

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

Details

Grey Systems: Theory and Application, vol. 6 no. 3
Type: Research Article
ISSN: 2043-9377

Keywords

Article
Publication date: 1 February 2016

Sifeng Liu, Yingjie Yang, Naiming Xie and Jeffrey Forrest

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…

1802

Abstract

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Practical implications

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.

Originality/value

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.

Details

Grey Systems: Theory and Application, vol. 6 no. 1
Type: Research Article
ISSN: 2043-9377

Keywords

Article
Publication date: 9 December 2020

Wei Meng, Qian Li, Bo Zeng and Yingjie Yang

The purpose of this paper is to unify the expression of fractional grey accumulating generation operator and the reducing generation operator, and build the FDGM(1,1) model with…

Abstract

Purpose

The purpose of this paper is to unify the expression of fractional grey accumulating generation operator and the reducing generation operator, and build the FDGM(1,1) model with the unified fractional grey generation operator.

Design/methodology/approach

By systematically studying the properties of the fractional accumulating operator and the reducing operator, and analyzing the sensitivity of the order value, a unified expression of the fractional operators is given. The FDGM(1,1) model with the unified fractional grey generation operator is established. The relationship between the order value and the modeling error distribution is studied.

Findings

The expression of the fractional accumulating generation operator and the reducing generation operator can be unified to a simple expression. For −1<r < 1, the fractional grey generation operator satisfies the principle of new information priority. The DGM(1,1) model is a special case of the FDGM(1,1) model with r = 1.

Research limitations/implications

The sensitivity of the unified operator is verified through random numerical simulation method, and the theoretical proof was not yet possible.

Practical implications

The FDGM(1,1) model has a higher modeling accuracy and modeling adaptability than the DGM(1,1) by optimizing the order.

Originality/value

The expression of the fractional accumulating generation operator and the reducing generation operator is firstly unified. The FDGM(1,1) model with the unified fractional grey generation operator is firstly established. The unification of the fractional accumulating operator and the reducing operator improved the theoretical basis of grey generation operator.

Details

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

Keywords

Article
Publication date: 29 July 2014

Yunchol Jong and Sifeng Liu

– The purpose of this paper is to propose a novel approach to improve prediction accuracy of grey power models including GM(1, 1) and grey Verhulst model.

Abstract

Purpose

The purpose of this paper is to propose a novel approach to improve prediction accuracy of grey power models including GM(1, 1) and grey Verhulst model.

Design/methodology/approach

The modified new models are proposed by optimizing the initial condition and model parameters. The new initial condition consists of the first item and the last item of a sequence generated by applying the first-order accumulative generation operator on the sequence of raw data.

Findings

It is shown that the newly modified grey power model is an extension of the previous optimized GM(1, 1) and grey Verhulst model. And the optimized initial condition reflected the principle of new information priority.

Practical implications

The result of a numerical example indicates that the modified grey model presented in this paper with better prediction performance.

Originality/value

The new initial condition are derived by weighted combination of the first item and the last item. The coefficients of weight obtained by the least square method.

Details

Grey Systems: Theory and Application, vol. 4 no. 2
Type: Research Article
ISSN: 2043-9377

Keywords

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