scholarly journals Forecasting the Cumulative Confirmed Cases with the FGM and Fractional-Order Buffer Operator in Different Stages of COVID-19

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Yanhui Chen ◽  
Minglei Zhang ◽  
Kai Lisa Lo ◽  
Jackson Jinhong Mi
Keyword(s):  
Growth Rate ◽  
Empirical Analysis ◽  
Fractional Order ◽  
Prediction Accuracy ◽  
Historical Data ◽  
Grey Model ◽  
Prevention Measures ◽  
Early Stages ◽  
The Empirical Analysis ◽  
Epidemic Diseases

This study proposes to use the fractional-order accumulation grey model (FGM) combined with the fractional-order buffer operator to predict the cumulative confirmed cases in different stages of COVID-19. In the early stages of COVID-19 outbreak, when the cumulative confirmed cases increased rapidly, we used the strengthening buffer operator in the prediction process. After the government’s prevention measures started to take effect, the growth rate of cumulative confirmed cases slows down. Therefore, the weakening buffer operator is applied in the prediction process. The fractional order of the buffer operator is derived from the historical data, which are more relevant. The empirical analysis of seven countries’ data shows that the FGM with the fractional-order buffer operator achieves the best results for most cases. The fractional-order buffer operator improves the prediction accuracy of the FGM in this study. Our study also suggests a practical way for predicting the trend of epidemic diseases.

scholarly journals A Novel Discrete Grey Model and Its Application

2019 ◽  
Vol 2019 ◽  
pp. 1-6 ◽  
Author(s):  
Wen-Ze Wu ◽  
Jianming Jiang ◽  
Qi Li
Keyword(s):  
Tensile Strength ◽  
Arbitrary Number ◽  
Prediction Accuracy ◽  
Historical Data ◽  
Prediction Performance ◽  
Grey Model ◽  
Original Series ◽  
Proposed Model ◽  
Grey Models ◽  
Future Data

This paper aims to further increase the prediction accuracy of the grey model based on the existing discrete grey model, DGM(1,1). Herein, we begin by studying the connection between forecasts and the first entry of the original series. The results comprehensively show that the forecasts are independent of the first entry in the original series. On this basis, an effective method of inserting an arbitrary number in front of the first item of the original series to extract messages is applied to produce a novel grey model, which is abbreviated as FDGM(1,1) for simplicity. Incidentally, the proposed model can even forecast future data using only three historical data. To demonstrate the effectiveness of the proposed model, two classical examples of the tensile strength and life of the product are employed in this paper. The numerical results indicate that FDGM(1,1) has a better prediction performance than most commonly used grey models.

scholarly journals Prediction of Agricultural Water Consumption in 2 Regions of China Based on Fractional-Order Cumulative Discrete Grey Model

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Yunhong Xu ◽  
Huadong Wang ◽  
Nga Lay Hui
Keyword(s):  
Fractional Order ◽  
Water Consumption ◽  
Optimization Model ◽  
Historical Data ◽  
Grey Model ◽  
Optimal Order ◽  
Agricultural Water ◽  
Forecasting Method ◽  
Best Fitting ◽  
Matlab Programming

In this paper, a new forecasting method of agricultural water demand, fractional-order cumulative discrete grey model, is proposed. Firstly, the best fitting of historical data is used to construct the optimization model. MATLAB programming is applied to solve the optimization model and obtain the optimal order. Secondly, the fractional-order cumulative discrete grey model in this paper is compared with GM (1, 1) model to verify the performance of the model. Finally, Handan region of Hebei Province and Jingzhou region of Hubei Province were selected as the study areas to predict their agricultural water consumptions. The results show that the fractional-order cumulative discrete grey model has better prediction performance than the GM (1, 1) model. It can be used as an effective method for forecasting agricultural water consumption.

Application of Improved Grey Prediction Model in Jilin Province of the Software Industry

2014 ◽  
Vol 998-999 ◽  
pp. 1079-1082 ◽  
Author(s):  
Wei Shi Yin ◽  
Pin Chao Meng ◽  
Yan Zhong Li
Keyword(s):  
Prediction Model ◽  
Prediction Accuracy ◽  
Historical Data ◽  
Software Industry ◽  
Experimental Results ◽  
Jilin Province ◽  
Grey Model ◽  
Grey Prediction ◽  
Grey Prediction Model ◽  
Better Than

Based on the modified grey prediction model, the outputs of software industry in Jilin Province were predicted. First the historical data and updated the data were pre-treated by iteration. Then it was found that the results from the modified grey prediction model were better than that from traditional grey prediction model by residual analysis. Finally, the prediction about the outputs of software industry in Jilin Province was given for the next five years. According to the experimental results, our proposed new method obviously can improve the prediction accuracy of the original grey model.

Traffic Volume Prediction Using Improved Kalman Filter

2014 ◽  
Vol 602-605 ◽  
pp. 3881-3885 ◽  
Author(s):  
Xin Jie Chen ◽  
Ji Hui Ma ◽  
Wei Guan ◽  
Wen Yuan Tu
Keyword(s):  
Kalman Filter ◽  
Empirical Analysis ◽  
Kalman Filtering ◽  
Prediction Accuracy ◽  
Prediction Models ◽  
Historical Data ◽  
Traffic Volume ◽  
The State ◽  
State Variable ◽  
Interesting Topic

Traffic volume prediction has been an interesting topic for decades during which various prediction models have been proposed. In this paper, Kalman filtering (KF) model is applied to predict traffic volume because of its significance in continuously updating the state variable as new observations. In order to enhance the prediction accuracy, an improved KF model is developed based on the current and historical data. To validate the improved KF model, empirical analysis is conducted. The results show that the improved KF model has higher accuracy than the traditional one and is more reliable and powerful in traffic volume prediction.

The Word Class Adjective in English Business Magazines Online

2018 ◽  
Vol 6 (2) ◽  
pp. 99-115
Author(s):  
Borislav Marušić ◽  
Sanda Katavić-Čaušić
Keyword(s):  
Empirical Study ◽  
Empirical Analysis ◽  
Word Formation ◽  
Word Class ◽  
Business English ◽  
Starting Point ◽  
Comprehensive Picture ◽  
English Syntax ◽  
The Empirical Analysis ◽  
Insight Into

Abstract The aim of this paper is to research the word class adjective in one sequence of the ESP: Business English, more precisely English business magazines online. It is an empirical study on the corpus taken from a variety of business magazines online. The empirical analysis allows a comprehensive insight into the word class adjective in this variety of Business English and makes its contribution to English syntax, semantics and word formation. The syntactic part analyses the adjective position in the sentence. The semantic part of the study identifies the most common adjectives that appear in English business magazines online. Most of the analysis is devoted to the word formation of the adjectives found in the corpus. The corpus is analysed in such a way that it enables its division into compounds, derivatives and conversions. The results obtained in this way will give a comprehensive picture of the word class adjective in this type of Business English and can act as a starting point for further research of the word class adjective.

ICT SMEs, Performance, Absorptive Capacity and Transformative Capacity

2019 ◽  
Vol 118 (3) ◽  
pp. 178-188
Author(s):  
Yeon-Sung Cho ◽  
Kyung-Il Khoe
Keyword(s):  
Firm Performance ◽  
Market Orientation ◽  
Empirical Analysis ◽  
Absorptive Capacity ◽  
Latent Variables ◽  
Equation Modeling ◽  
Transformative Capacity ◽  
The Impact ◽  
The Empirical Analysis ◽  
Innovative Capacity

This study intends to integrate the relationship of market orientation, innovative capacity and firm performance to Information and Communication Technology(ICT) SMEs. The purpose of this study is to identify the role of absorptive capacity and transformative capacity that affect the performance of ICT SMEs. Hypotheses were established between five latent variables. A total of six hypotheses were established including the moderated effects of absorptive capacity and transformative capacity. Of the data collected after the survey, 112 valid surveys were selected as the final sample, except for 17 questionnaires with high non - response and insincere response. The empirical analysis of this study used smartpls3.0, Partial Least Squares (PLS), a variance-based structural equation modeling. The empirical analysis of this study revealed that the impact of market orientation on innovative capacity was significant. Moreover, the innovative capacity had a positive effect on the performance of ICT SMEs. In addition, the absorptive activity had a positive moderated effect between the market orientation and the innovative capacity. On the other hand, the transformative capacity showed a positive moderated effect in relation to innovative capacity and firm performance. Our empirical results have demonstrated the importance of knowledge based capacity in the ICT SMEs.

Capital Structure and Earnings per Share: An Empirical Analysis of Indian Corporate Sector

2015 ◽  
Vol 5 (3) ◽  
Author(s):  
Harvinder Singh Mand ◽  
Manjit Singh
Keyword(s):  
Capital Structure ◽  
Empirical Analysis ◽  
Corporate Sector ◽  
Independent Variables ◽  
Earnings Per Share ◽  
Panel Data Regression ◽  
Data Regression ◽  
The Impact ◽  
The Relationship ◽  
The Empirical Analysis

This paper intends to measure the impact of capital structure on EPS (earnings per share) in Indian corporate sector. Fifteen control variables along with capital structure have been selected to know their impact on EPS. Panel data regression has been applied to establish the relationship among dependent and independent variables. It is found from the empirical analysis that the relation of capital structure with EPS has been statistically insignificant in Indian corporate sector among all specific industries except telecommunication industry. The results are consistent with Modigliani-Miller approach.

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