Grey Systems-Theory and Application最新文献

{"title":"A novel grey forecasting model with generalised fractal derivative and its optimisation","authors":"Lina Jia, MingYong Pang","doi":"10.1108/gs-11-2023-0109","DOIUrl":"https://doi.org/10.1108/gs-11-2023-0109","url":null,"abstract":"<h3>Purpose</h3>\u0000<p>The purpose of this paper is to propose a new grey prediction model, GOFHGM (1,1), which combines generalised fractal derivative and particle swarm optimisation algorithms. The aim is to address the limitations of traditional grey prediction models in order selection and improve prediction accuracy.</p><!--/ Abstract__block -->\u0000<h3>Design/methodology/approach</h3>\u0000<p>The paper introduces the concept of generalised fractal derivative and applies it to the order optimisation of grey prediction models. The particle swarm optimisation algorithm is also adopted to find the optimal combination of orders. Three cases are empirically studied to compare the performance of GOFHGM(1,1) with traditional grey prediction models.</p><!--/ Abstract__block -->\u0000<h3>Findings</h3>\u0000<p>The study finds that the GOFHGM(1,1) model outperforms traditional grey prediction models in terms of prediction accuracy. Evaluation indexes such as mean squared error (MSE) and mean absolute error (MAE) are used to evaluate the model.</p><!--/ Abstract__block -->\u0000<h3>Research limitations/implications</h3>\u0000<p>The research study may have limitations in terms of the scope and generalisability of the findings. Further research is needed to explore the applicability of GOFHGM(1,1) in different fields and to improve the model’s performance.</p><!--/ Abstract__block -->\u0000<h3>Originality/value</h3>\u0000<p>The study contributes to the field by introducing a new grey prediction model that combines generalised fractal derivative and particle swarm optimisation algorithms. This integration enhances the accuracy and reliability of grey predictions and strengthens their applicability in various predictive applications.</p><!--/ Abstract__block -->","PeriodicalId":48597,"journal":{"name":"Grey Systems-Theory and Application","volume":"18 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140810034","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel time-varying grey Fourier model for variable amplitude seasonal fluctuation sequences","authors":"Xiaomei Liu, Bin Ma, Meina Gao, Lin Chen","doi":"10.1108/gs-10-2023-0101","DOIUrl":"https://doi.org/10.1108/gs-10-2023-0101","url":null,"abstract":"<h3>Purpose</h3>\u0000<p>A time-varying grey Fourier model (TVGFM(1,1,N)) is proposed for the simulation of variable amplitude seasonal fluctuation time series, as the performance of traditional grey models can't catch the time-varying trend well.</p><!--/ Abstract__block -->\u0000<h3>Design/methodology/approach</h3>\u0000<p>The proposed model couples Fourier series and linear time-varying terms as the grey action, to describe the characteristics of variable amplitude and seasonality. The truncated Fourier order N is preselected from the alternative order set by Nyquist-Shannon sampling theorem and the principle of simplicity, then the optimal Fourier order is determined by hold-out method to improve the robustness of the proposed model. Initial value correction and the multiple transformation are also studied to improve the precision.</p><!--/ Abstract__block -->\u0000<h3>Findings</h3>\u0000<p>The new model has a broader applicability range as a result of the new grey action, attaining higher fitting and forecasting accuracy. The numerical experiment of a generated monthly time series indicates the proposed model can accurately fit the variable amplitude seasonal sequence, in which the mean absolute percentage error (MAPE) is only 0.01%, and the complex simulations based on Monte-Carlo method testify the validity of the proposed model. The results of monthly electricity consumption in China's primary industry, demonstrate the proposed model catches the time-varying trend and has good performances, where MAPE_F and MAPE_T are below 5%. Moreover, the proposed TVGFM(1,1,N) model is superior to the benchmark models, grey polynomial model (GMP(1,1,N)), grey Fourier model (GFM(1,1,N)), seasonal grey model (SGM(1,1)), seasonal ARIMA model seasonal autoregressive integrated moving average model (SARIMA) and support vector regression (SVR).</p><!--/ Abstract__block -->\u0000<h3>Originality/value</h3>\u0000<p>The parameter estimates and forecasting of the new proposed TVGFM are studied, and the good fitting and forecasting accuracy of time-varying amplitude seasonal fluctuation series are testified by numerical simulations and a case study.</p><!--/ Abstract__block -->","PeriodicalId":48597,"journal":{"name":"Grey Systems-Theory and Application","volume":"59 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140314695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel fractional order variable structure multivariable grey prediction model with optimal differential background-value coefficients and its performance comparison analysis","authors":"Chao Xia, Bo Zeng, Yingjie Yang","doi":"10.1108/gs-08-2023-0082","DOIUrl":"https://doi.org/10.1108/gs-08-2023-0082","url":null,"abstract":"<h3>Purpose</h3>\u0000<p>Traditional multivariable grey prediction models define the background-value coefficients of the dependent and independent variables uniformly, ignoring the differences between their physical properties, which in turn affects the stability and reliability of the model performance.</p><!--/ Abstract__block -->\u0000<h3>Design/methodology/approach</h3>\u0000<p>A novel multivariable grey prediction model is constructed with different background-value coefficients of the dependent and independent variables, and a one-to-one correspondence between the variables and the background-value coefficients to improve the smoothing effect of the background-value coefficients on the sequences. Furthermore, the fractional order accumulating operator is introduced to the new model weaken the randomness of the raw sequence. The particle swarm optimization (PSO) algorithm is used to optimize the background-value coefficients and the order of the model to improve model performance.</p><!--/ Abstract__block -->\u0000<h3>Findings</h3>\u0000<p>The new model structure has good variability and compatibility, which can achieve compatibility with current mainstream grey prediction models. The performance of the new model is compared and analyzed with three typical cases, and the results show that the new model outperforms the other two similar grey prediction models.</p><!--/ Abstract__block -->\u0000<h3>Originality/value</h3>\u0000<p>This study has positive implications for enriching the method system of multivariable grey prediction model.</p><!--/ Abstract__block -->","PeriodicalId":48597,"journal":{"name":"Grey Systems-Theory and Application","volume":"9 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139771380","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Damping accumulated discrete MGM(1, m) power model and its application to forecasting agricultural output value share and employment share","authors":"Liangshuai Li, Dang Luo","doi":"10.1108/gs-11-2023-0112","DOIUrl":"https://doi.org/10.1108/gs-11-2023-0112","url":null,"abstract":"<h3>Purpose</h3>\u0000<p>The damping accumulated discrete MGM(1, m) power model is proposed for the problem of forecasting the share of agricultural output value and the share of employment in China.</p><!--/ Abstract__block -->\u0000<h3>Design/methodology/approach</h3>\u0000<p>In this study, the damping accumulated discrete MGM(1, m) power model was developed based on the idea of discrete modelling by introducing a damping accumulated generating operator and power index. The new model can better identify the non-linear characteristics existing between different factors in the multivariate system and can accurately describe and forecast the trend of changes between data series and each of them.</p><!--/ Abstract__block -->\u0000<h3>Findings</h3>\u0000<p>The validity and rationality of the new model are verified through numerical experiment. It is forecasted that in 2023, the share of agricultural output value in China will be 7.14% and the share of agricultural employment will be 21.98%, with an overall decreasing trend.</p><!--/ Abstract__block -->\u0000<h3>Practical implications</h3>\u0000<p>The simultaneous decline in the share of agricultural output value and the share of employment is a common feature of countries that have achieved agricultural modernisation. Accurate forecasts of the share of agricultural output value and the share of employment can provide an important scientific basis for formulating appropriate agricultural development targets and policies in China.</p><!--/ Abstract__block -->\u0000<h3>Originality/value</h3>\u0000<p>The new model proposed in this study fully considers the importance of new information and has higher stability. The differential evolutionary algorithm was used to optimise the model parameters.</p><!--/ Abstract__block -->","PeriodicalId":48597,"journal":{"name":"Grey Systems-Theory and Application","volume":"3 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139677511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Seasonal electricity consumption forecasting: an approach with novel weakening buffer operator and fractional order accumulation grey model","authors":"Chuanmin Mi, Xiaoyi Gou, Yating Ren, Bo Zeng, Jamshed Khalid, Yuhuan Ma","doi":"10.1108/gs-08-2023-0074","DOIUrl":"https://doi.org/10.1108/gs-08-2023-0074","url":null,"abstract":"<h3>Purpose</h3>\u0000<p>Accurate prediction of seasonal power consumption trends with impact disturbances provides a scientific basis for the flexible balance of the long timescale power system. Consequently, it fosters reasonable scheduling plans, ensuring the safety of the system and improving the economic dispatching efficiency of the power system.</p><!--/ Abstract__block -->\u0000<h3>Design/methodology/approach</h3>\u0000<p>First, a new seasonal grey buffer operator in the longitudinal and transverse dimensional perspectives is designed. Then, a new seasonal grey modeling approach that integrates the new operator, full real domain fractional order accumulation generation technique, grey prediction modeling tool and fruit fly optimization algorithm is proposed. Moreover, the rationality, scientificity and superiority of the new approach are verified by designing 24 seasonal electricity consumption forecasting approaches, incorporating case study and amalgamating qualitative and quantitative research.</p><!--/ Abstract__block -->\u0000<h3>Findings</h3>\u0000<p>Compared with other comparative models, the new approach has superior mean absolute percentage error and mean absolute error. Furthermore, the research results show that the new method provides a scientific and effective mathematical method for solving the seasonal trend power consumption forecasting modeling with impact disturbance.</p><!--/ Abstract__block -->\u0000<h3>Originality/value</h3>\u0000<p>Considering the development trend of longitudinal and transverse dimensions of seasonal data with impact disturbance and the differences in each stage, a new grey buffer operator is constructed, and a new seasonal grey modeling approach with multi-method fusion is proposed to solve the seasonal power consumption forecasting problem.</p><!--/ Abstract__block -->\u0000<h3>Highlights</h3>\u0000<p>The highlights of the paper are as follows:<ol list-type=\"order\"><li><p>A new seasonal grey buffer operator is constructed.</p></li><li><p>The impact of shock perturbations on seasonal data trends is effectively mitigated.</p></li><li><p>A novel seasonal grey forecasting approach with multi-method fusion is proposed.</p></li><li><p>Seasonal electricity consumption is successfully predicted by the novel approach.</p></li><li><p>The way to adjust China's power system flexibility in the future is analyzed.</p></li></ol></p><!--/ Abstract__block -->","PeriodicalId":48597,"journal":{"name":"Grey Systems-Theory and Application","volume":"103 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139422622","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A new grey relational analysis model of cross-sequences","authors":"Sifeng Liu, Ningning Lu, Zhongju Shang, R.M. Kapila Tharanga Rathnayaka","doi":"10.1108/gs-10-2023-0098","DOIUrl":"https://doi.org/10.1108/gs-10-2023-0098","url":null,"abstract":"<h3>Purpose</h3>\u0000<p>The purpose of this paper is to explore a new approach to solve the problem of positive and negative offset in the calculation process of integral elements, then propose a series of new grey relational degree model for cross sequences.</p><!--/ Abstract__block -->\u0000<h3>Design/methodology/approach</h3>\u0000<p>The definitions of cross sequences and area elements have been proposed at first. Then the concept of difference degree between sequences has been put forward. Based on the definition of difference degree between sequences, various modified grey relational degree models for cross sequences have been proposed to solve the measurement problem of cross sequence correlation relationships.</p><!--/ Abstract__block -->\u0000<h3>Findings</h3>\u0000<p>(1) The new definition of cross sequences; (2) The area element; (3) Various modified grey relational degree models for cross sequences based on the definition of difference degree between sequences.</p><!--/ Abstract__block -->\u0000<h3>Practical implications</h3>\u0000<p>The grey relational analysis model of cross sequences is a difficult problem in grey relational analysis. The new model proposed in this article can effectively avoid the calculation deviation of grey relational analysis model for cross sequences, and reasonably measure the correlation between cross sequences. The new model was used to analyse the food consumer price index in Shaanxi Province, clarifying the relationship between different types of food consumer price indices, some interesting results that are not completely consistent with general economic theory were obtained.</p><!--/ Abstract__block -->\u0000<h3>Originality/value</h3>\u0000<p>The new definition of cross sequences, the area element and various modified grey relational degree models for cross sequences were proposed.</p><!--/ Abstract__block -->","PeriodicalId":48597,"journal":{"name":"Grey Systems-Theory and Application","volume":"29 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139423882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Grey angle cosine relational degree model based on generalized greyness of interval grey number","authors":"Li Zhang, Xican Li","doi":"10.1108/gs-08-2023-0081","DOIUrl":"https://doi.org/10.1108/gs-08-2023-0081","url":null,"abstract":"<h3>Purpose</h3>\u0000<p>Aim to the limitations of grey relational analysis of interval grey number, based on the generalized greyness of interval grey number, this paper tries to construct a grey angle cosine relational degree model from the perspective of proximity and similarity.</p><!--/ Abstract__block -->\u0000<h3>Design/methodology/approach</h3>\u0000<p>Firstly, the algorithms of the generalized greyness of interval grey number and interval grey number vector are given, and its properties are analyzed. Then, based on the grey relational theory, the grey angle cosine relational model is proposed based on the generalized greyness of interval grey number, and the relationship between the classical cosine similarity model and the grey angle cosine relational model is analyzed. Finally, the validity of the model in this paper is illustrated by the calculation examples and an application example of related factor analysis of maize yield.</p><!--/ Abstract__block -->\u0000<h3>Findings</h3>\u0000<p>The results show that the grey angle cosine relational degree model has strict theoretical basis, convenient calculation and is easy to program, which can not only fully utilize the information of interval grey numbers but also overcome the shortcomings of greyness relational degree model. The grey angle cosine relational degree is an extended form of cosine similarity degree of real numbers. The calculation examples and the related factor analysis of maize yield show that the model proposed in this paper is feasible and valid.</p><!--/ Abstract__block -->\u0000<h3>Practical implications</h3>\u0000<p>The research results not only further enrich the grey system theory and method but also provide a basis for the grey relational analysis of the sequences in which the interval grey numbers coexist with the real numbers.</p><!--/ Abstract__block -->\u0000<h3>Originality/value</h3>\u0000<p>The paper succeeds in realizing the algorithms of the generalized greyness of interval grey number and interval grey number vector, and the grey angle cosine relational degree, which provide a new method for grey relational analysis.</p><!--/ Abstract__block -->","PeriodicalId":48597,"journal":{"name":"Grey Systems-Theory and Application","volume":"54 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139020380","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assembly line balancing and capacity evaluation based on interval grey processing time","authors":"Zihan Dang, Naiming Xie","doi":"10.1108/gs-09-2023-0084","DOIUrl":"https://doi.org/10.1108/gs-09-2023-0084","url":null,"abstract":"<h3>Purpose</h3>\u0000<p>Assembly line is a common production form and has been effectively used in many industries, but the imprecise processing time of each process makes production line balancing and capacity forecasting the most troublesome problems for production managers. In this paper, uncertain man-hours are represented as interval grey numbers, and the optimization problem of production line balance in the case of interval grey man-hours is studied to better evaluate the production line capacity.</p><!--/ Abstract__block -->\u0000<h3>Design/methodology/approach</h3>\u0000<p>First, this paper constructs the basic model of assembly line balance optimization for the single-product scenario, and on this basis constructs an assembly line balance optimization model under the multi-product scenario with the objective function of maximizing the weighted greyscale production line balance rate, second, this paper designs a simulated annealing algorithm to solve problem. A neighborhood search strategy is proposed, based on assembly line balance optimization, an assembly line capacity evaluation method with interval grey man-hour characteristics is designed.</p><!--/ Abstract__block -->\u0000<h3>Findings</h3>\u0000<p>This paper provides a production line balance optimization scheme with uncertain processing time for multi-product scenarios and designs a capacity evaluation method to provide managers with scientific management strategies so that decision-makers can scientifically solve the problems that the company's design production line is quite different from the actual production situation.</p><!--/ Abstract__block -->\u0000<h3>Originality/value</h3>\u0000<p>There are few literary studies on combining interval grey number with assembly line balance optimization. Therefore, this paper makes an important contribution in this regard.</p><!--/ Abstract__block -->","PeriodicalId":48597,"journal":{"name":"Grey Systems-Theory and Application","volume":"32 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138825896","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A new adaptive grey seasonal model for time series forecasting tasks","authors":"Ran Wang, Yunbao Xu, Qinwen Yang","doi":"10.1108/gs-07-2023-0055","DOIUrl":"https://doi.org/10.1108/gs-07-2023-0055","url":null,"abstract":"<h3>Purpose</h3>\u0000<p>This paper intends to construct a new adaptive grey seasonal model (AGSM) to promote the application of the grey forecasting model in quarterly GDP.</p><!--/ Abstract__block -->\u0000<h3>Design/methodology/approach</h3>\u0000<p>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.</p><!--/ Abstract__block -->\u0000<h3>Findings</h3>\u0000<p>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.</p><!--/ Abstract__block -->\u0000<h3>Originality/value</h3>\u0000<p>A new AGSM with new information priority accumulation operation is proposed.</p><!--/ Abstract__block -->","PeriodicalId":48597,"journal":{"name":"Grey Systems-Theory and Application","volume":"12 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138825847","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The evaluation of grey relative incidence","authors":"Marcin Nowak, Marta Pawłowska-Nowak, Małgorzata Kokocińska, Piotr Kułyk","doi":"10.1108/gs-06-2023-0049","DOIUrl":"https://doi.org/10.1108/gs-06-2023-0049","url":null,"abstract":"<h3>Purpose</h3>\u0000<p>With the use of the grey incidence analysis (GIA), indicators such as the absolute degree of grey incidence (<em>ε_ij</em>), relative degree of grey incidence (<em>r_ij</em>) or synthetic degree of grey incidence (<em>ρ_ij</em>) are calculated. However, it seems that some assumptions made to calculate them are arguable, which may also have a material impact on the reliability of test results. In this paper, the authors analyse one of the indicators of the GIA, namely the relative degree of grey incidence. The aim of the article was to verify the hypothesis: in determining the relative degree of grey incidence, the method of standardisation of elements in a series significantly affects the test results.</p><!--/ Abstract__block -->\u0000<h3>Design/methodology/approach</h3>\u0000<p>To achieve the purpose of the article, the authors used the numerical simulation method and the logical analysis method (in order to draw conclusions from our tests).</p><!--/ Abstract__block -->\u0000<h3>Findings</h3>\u0000<p>It turned out that the applied method of standardising elements in series when calculating the relative degree of grey incidence significantly affects the test results. Moreover, the manner of standardisation used in the original method (which involves dividing all elements by the first element) is not the best. Much more reliable results are obtained by a standardisation that involves dividing all elements by their arithmetic mean.</p><!--/ Abstract__block -->\u0000<h3>Research limitations/implications</h3>\u0000<p>Limitations of the conducted evaluation involve in particular the limited scope of inference. This is since the obtained results referred to only one of the indicators classified into the GIA.</p><!--/ Abstract__block -->\u0000<h3>Originality/value</h3>\u0000<p>In this article, the authors have evaluated the model of GIA in which the relative degree of grey incidence is determined. As a result of the research, the authors have proposed a recommendation regarding a change in the method of standardising variables, which will contribute to obtaining more reliable results in relational tests using the grey system theory.</p><!--/ Abstract__block -->","PeriodicalId":48597,"journal":{"name":"Grey Systems-Theory and Application","volume":"36 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138686066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}