Application of grey prediction model to the prediction of medical consumables consumption

Shen, Xin; Yue, Minghui; Duan, Pengfei; Wu, Guihai; Tan, Xuerui

doi:10.1108/gs-11-2018-0059

Cited by 4 publications

(3 citation statements)

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“…We used this model to obtain the forecast values for the years 2022 and 2023. [9] Gradient boosting regression tree has the strong applicability and fault tolerance. We established a training model for historical data.…”

Section: Resultsmentioning

confidence: 99%

Birth Rate Prediction System Based on Grey Prediction and Gradient Boosting Regression Tree Ensemble Model

Huang,

Lin,

Qin

et al. 2023

Fuzzy Systems and Data Mining IX

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We selected several factors affecting the Birth Rate in Guangdong Province. Then we saw the contribution of each characteristic to the Birth Rate by the gradient boosting regression tree model. The grey prediction algorithm used each characteristic to predict its value in a certain year. Using variance ratio and small residual probability, we evaluated the prediction accuracy. We used the gradient boosting regression tree for predicting the Birth Rate in the next two years. This was done under the premise of knowing the data of each characteristic. The thinking of the factors affecting the Birth Rate and the prediction of the Birth Rate prompt us to think about the relevant realistic factors. They also assist the government in focusing on the adjustment of fertility policy. The aim is to promote population development and social progress to the greatest extent possible.

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Section: Resultsmentioning

confidence: 99%

Birth Rate Prediction System Based on Grey Prediction and Gradient Boosting Regression Tree Ensemble Model

Huang,

Lin,

Qin

et al. 2023

Fuzzy Systems and Data Mining IX

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show abstract

“…Grey Models e grey prediction model is established based on the accumulation sequence, which can effectively reduce the randomness of the system and show the development law of the system. For example, for an original data sequence X (0) � (1, 4, 2, 5, 2, 3), its first-order accumulation sequence is X (1) � (1,5,7,12,14,17), as shown in Figure 1.…”

Section: Construction Of Fractional Discretementioning

confidence: 99%

“…In recent years, many scholars have carried out extensive research studies on the grey prediction model [4][5][6][7][8][9][10][11][12][13][14][15][16][17], whose achievements have played a positive role in improving the grey prediction theory. e GM (1, 1) model requires the transformation of differential equation and difference equation, which will lead to systematic errors.…”

Section: Introductionmentioning

confidence: 99%

Energy Consumption Predication in China Based on the Modified Fractional Grey Prediction Model

Liu

Gao²

2021

Journal of Mathematics

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China’s increasing energy consumption poses challenges to economy and environment. How to predict the energy consumption accurately and regulate the future energy consumption production is a problem worth studying. In this paper, the fractional order cumulative linear time-varying parameter discrete grey prediction model (FTDGM (1, 1) model) is introduced. Firstly, the data are preprocessed by buffer operators, and then, the FTDGM (1, 1) model is established. In this paper, the parameter estimation method and the specific process of model establishment are presented. Finally, the models of energy consumption in China are built. The advantages and prediction accuracy of the model established in this paper are analyzed, and the data in the following years are effectively predicted, so as to provide theoretical support for the government to formulate reasonable energy policies.

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Benchmarking quality characteristics for road-mapping sustainability of higher educational institutes and capping Indian portfolio

Sahu,

Raut

2023

BIJ

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PurposeEducational policies, integrated practices, obliged strategies and notable benchmarks are always required by the higher educational institutions (HEIs) for operating business ventures into competent boundaries and to preside toward the overall new business density. The same are needed to be evaluated based on student's concerns for road-mapping sustainability. Accordingly, authors conducted present study to identify crucial quality characteristics (measures) under the origins of HEIs based on student's concerns using qualitative medium under Indian economy. The study is presenting critical dimensions and quality characteristics, which are seeking by the students for selecting HEIs for their studies.Design/methodology/approachKano integrated-Grey-VIKOR approach is utilized in present study for road-mapping sustainability based on the determination of priority index and ranking. The study utilized three segments of methodology, where in the first segment, Kano technique is implicated to define priority index of quality characteristics. In the second segment, grey sets theory is implicated to capture the perceptions of the respondents. In the third segment, VIKOR technique is implicate to rank the HEIs.FindingsThe findings of the study will assist administrators in planning the prominent strategies that can embrace performance traits under HEI, which in turn will participate in growth and development of an economy. The findings have revealed “PPCS, ICMC, TSTR, PICM, AFEP, IMIS as Attractive performance characteristics,” “IEAF, OIAR, INET as One dimensional performance characteristics,” “QTCS, PORE, SIRD as Must-be performance characteristics” and “PQPE, PCTM as Indifferent performance characteristics.” Additionally, “Professional and placement characteristics of institute” is found as the most significant measure inspiring students for admiring engineering institutes. It is found that “Observance of institutional affiliation and recognition” and “Infrastructure, classroom management and control methods” are found as the second significant measures. “Patterns of question papers and evaluation medium” and “Personal characteristics of teacher and management” are found as the least competent characteristics admiring stakeholders for selecting HEI.Originality/valueThe present study can assist administrators in drafting refined policies and strategies for practising quality outputs by HEI. The study suggested critical quality characteristics, which in respond will aid in attracting more number of students toward educational institutes. A study under Indian context is demonstrated for presenting critical facts and attaining higher student's enrolment rates.

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Application of grey prediction model to the prediction of medical consumables consumption

Cited by 4 publications

References 1 publication

Birth Rate Prediction System Based on Grey Prediction and Gradient Boosting Regression Tree Ensemble Model

Birth Rate Prediction System Based on Grey Prediction and Gradient Boosting Regression Tree Ensemble Model

Energy Consumption Predication in China Based on the Modified Fractional Grey Prediction Model

Benchmarking quality characteristics for road-mapping sustainability of higher educational institutes and capping Indian portfolio

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