Forecasting smog in Beijing using a novel time-lag GM(1,N) model based on interval grey number sequences

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jia Shi ◽  
Pingping Xiong ◽  
Yingjie Yang ◽  
Beichen Quan
Keyword(s):  
Time Lag ◽  
Upper And Lower Bounds ◽  
Simulation Accuracy ◽  
Content Type ◽  
Model Based ◽  
Proposed Model ◽  
Lag Effect ◽  
Number Sequences ◽  
The Government ◽  
Grey Number

PurposeSmog seriously affects the ecological environment and poses a threat to public health. Therefore, smog control has become a key task in China, which requires reliable prediction.Design/methodology/approachThis paper establishes a novel time-lag GM(1,N) model based on interval grey number sequences. Firstly, calculating kernel and degree of greyness of the interval grey number sequence respectively. Then, establishing the time-lag GM(1,N) model of kernel and degree of greyness sequences respectively to obtain their values after determining the time-lag parameters of two models. Finally, the upper and lower bounds of interval grey number sequences are obtained by restoring the values of kernel and degree of greyness.FindingsIn order to verify the validity and practicability of the model, the monthly concentrations of PM2.5, SO2 and NO2 in Beijing during August 2017 to September 2018 are selected to establish the time-lag GM(1,3) model for kernel and degree of greyness sequences respectively. Compared with three existing models, the proposed model in this paper has better simulation accuracy. Therefore, the novel model is applied to forecast monthly PM2.5 concentration for October to December 2018 in Beijing and provides a reference basis for the government to formulate smog control policies.Practical implicationsThe proposed model can simulate and forecast system characteristic data with the time-lag effect more accurately, which shows that the time-lag GM(1,N) model proposed in this paper is practical and effective.Originality/valueBased on interval grey number sequences, the traditional GM(1,N) model neglects the time-lag effect of driving terms, hence this paper introduces the time-lag parameters into driving terms of the traditional GM(1,N) model and proposes a novel time-lag GM(1,N) model.

MGM(1,m) model based on interval grey number sequence and its applications

2017 ◽  
Vol 7 (3) ◽  
pp. 310-319 ◽  
Author(s):  
Pingping Xiong ◽  
Yue Zhang ◽  
Bo Zeng ◽  
Tian-Xiang Yao
Keyword(s):  
Prediction Models ◽  
Development Trend ◽  
Upper And Lower Bounds ◽  
Number Sequence ◽  
Content Type ◽  
Model Based ◽  
Grey Forecasting ◽  
Number Sequences ◽  
Grey Number ◽  
Predicted Values

Purpose Aiming at the traditional multivariate grey forecasting model only considers the modelling of real numbers; therefore, the purpose of this paper is to construct an MGM(1, m) model based on the interval grey number sequences according to the grey modelling theory. Design/methodology/approach First, the multivariable grey number sequences are transformed into the kernel and grey radius sequences which are two feature sequences of interval grey number sequences. Then the MGM(1, m) model for kernel sequences and grey radius sequences are established, respectively. Finally, the simulation and prediction of the upper and lower bounds of the interval grey number sequences are realized by the reductive calculation of the predicted values of the kernel and grey radius. Findings The model is applied to the prediction of visibility and relative humidity, the identification factors of the haze. The results show that the model has high accuracy on the simulation and prediction of multivariable grey number sequences, which is reasonable and practical. Originality/value The main contribution of this paper is to propose a method to simulate and forecast the multivariable grey number sequence that is to establish the prediction models for the whitening sequences of multivariable grey number sequences which are kernel and grey radius sequences and extend the possibility boundary of kernel by grey radius. The model can reflect the development trend of multivariable grey number sequence accurately. When the grey information is continuously complemented, the multivariable grey number prediction model is transformed into the traditional MGM(1, m) model. Therefore, the MGM(1, m) model based on interval grey number sequence is the generalisation and expansion of the traditional MGM(1, m) model.

scholarly journals A Novel Linear Time-Varying GM(1,N) Model for Forecasting Haze: A Case Study of Beijing, China

2019 ◽  
Vol 11 (14) ◽  
pp. 3832 ◽  
Author(s):  
Pingping Xiong ◽  
Jia Shi ◽  
Lingling Pei ◽  
Song Ding
Keyword(s):  
Linear Time ◽  
Dynamic Change ◽  
Time Varying ◽  
The Novel ◽  
Model Based ◽  
Number Sequences ◽  
The Government ◽  
Grey Number ◽  
Beijing China

Haze is the greatest challenge facing China’s sustainable development, and it seriously affects China’s economy, society, ecology and human health. Based on the uncertainty and suddenness of haze, this paper proposes a novel linear time-varying grey model (GM)(1,N) based on interval grey number sequences. Because the original GM(1,N) model based on interval grey number sequences has constant parameters, it neglects the dynamic change characteristics of parameters over time. Therefore, this novel linear time-varying GM(1,N) model, based on interval grey number sequences, is established on the basis of the original GM(1,N) model by introducing a linear time polynomial. To verify the validity and practicability of this model, this paper selects the data of PM10, SO2 and NO2 concentrations in Beijing, China, from 2008 to 2018, to establish a linear time-varying GM(1,3) model based on interval grey number sequences, and the prediction results are compared with the original GM(1,3) model. The result indicates that the prediction effect of the novel model is better than that of the original model. Finally, this model is applied to forecast PM10 concentration for 2019 to 2021 in Beijing, and the forecast is made to provide a reference for the government to carry out haze control.

Grey target decision-making model of interval grey number based on cone volume

2017 ◽  
Vol 7 (2) ◽  
pp. 247-258 ◽  
Author(s):  
Lizhen Wang ◽  
Wuyong Qian
Keyword(s):  
Decision Making ◽  
Entropy Method ◽  
Maximal Entropy ◽  
Information Distortion ◽  
Content Type ◽  
Model Based ◽  
Proposed Model ◽  
Grey Number ◽  
Decision Making Model ◽  
The Impact

Purpose The purpose of this paper is to propose a grey target decision model based on cobweb area in order to overcome the effect and influence from the extreme value of the index on the decision result. However, it does not take into account the impact of the correlation between indicators on the angle of the index, and produce a certain degree decision information distortion as a result of the equal angle between the indicators. In order to solve the above problems, a novel grey decision-making model based on cone volume is proposed. Design/methodology/approach In this paper, the model uses the whitening weight function to whiten the interval grey number, and the Delphi method and the maximal entropy method are exploited to integrate the weight of the index. On the basis of this, the center of the bull’s eye, the weight and the index value are constructed as the center circle, the radius, and the high cone, respectively. The scheme is selected by the volume of the cone, the decision is made according to the order relation, and the example is utilized to prove and analyze the validity of the proposed model. Findings The results show that the proposed model can well improve the traditional grey target decision-making model from the modeling object and modeling method. Practical implications The method exposed in the paper can be used to deal with the grey target decision-making problems which characteristics are multi-indexes, and the attribute values are interval grey numbers. Originality/value The paper succeeds in overcoming the disadvantages of grey target decision making based on the target center distance and the cobweb area.

Information technology investment and innovation performance: does investment paradox exist?

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Peinan Ji ◽  
Xiangbin Yan ◽  
Yan Shi
Keyword(s):  
Information Technology ◽  
Time Lag ◽  
Innovation Performance ◽  
Test Model ◽  
It Investment ◽  
Firm Innovation ◽  
Data Set ◽  
Content Type ◽  
Lag Effect ◽  
Enterprise Innovation

Purpose The purpose of this study is to deepen the understanding of the effects of information technology (IT) investment on firm innovation performance and examining the investment paradox effect in China. Design/methodology/approach Using a sample of China’ public firms IT investment data between 2010 and 2016, the authors establish a test model of IT investment and innovation performance. Findings The result indicates that IT investment in firms have no effect on innovation performance in the investment period. However, in the full sample and manufacturing sample, the IT investment has a significant positive effect on innovation performance in the post-investment years. In addition, this study finds that large companies and low-age companies may contribute more to innovation when firm investment in IT. Research limitations/implications There are several limitations in this research. First, the authors are failed to obtain a larger sample about the IT investment information data set in China, so this study was compelled to use limited sample data from China, hence, this could lead to errors of too early generalization. Second, the authors use the number of invention patent applications to represent the performance of enterprise innovation, which may not show enterprise innovation effectively. Third, the firms in the sample are all in China Listed Companies, so this may not accurately reflect the entire environment of firm innovation performance, and could possibly. Practical implications The research confirms that there is a paradox and time lag effect in IT investment, which enterprises should pay attention to. Originality/value Existing research confirms that corporate IT investments can bring new products or services. However, the authors still do not know whether IT investment has improved the company’s ability of innovation. This study will fill this gap and the industry effect and time lag effect of the influence of IT investment on innovative performance are also examined.

Development of a direct NGM(1,1) prediction model based on interval grey numbers

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ye Li ◽  
Yuanping Ding ◽  
Yaqian Jing ◽  
Sandang Guo
Keyword(s):  
Genetic Algorithm ◽  
Markov Model ◽  
Prediction Model ◽  
Real Number ◽  
Content Type ◽  
Optimal Weight ◽  
Practical Applications ◽  
Number Sequences ◽  
Integral Development ◽  
Grey Number

PurposeThe purpose of this paper is to construct an interval grey number NGM(1,1) direct prediction model (abbreviated as IGNGM(1,1)), which need not transform interval grey numbers sequences into real number sequences, and the Markov model is used to optimize residual sequences of IGNGM(1,1) model.Design/methodology/approachA definition equation of IGNGM(1,1) model is proposed in this paper, and its time response function is solved by recursive iteration method. Next, the optimal weight of development coefficients of two boundaries is obtained by genetic algorithm, which is designed by minimizing the average relative error based on time weighted. In addition to that, the Markov model is used to modify residual sequences.FindingsThe interval grey numbers’ sequences can be predicted directly by IGNGM(1,1) model and its residual sequences can be amended by Markov model. A case study shows that the proposed model has higher accuracy in prediction.Practical implicationsUncertainty and volatility information is widespread in practical applications, and the information can be characterized by interval grey numbers. In this paper, an interval grey numbers direct prediction model is proposed, which provides a method for predicting the uncertainty information in the real world.Originality/valueThe main contribution of this paper is to propose an IGNGM(1,1) model which can realize interval grey numbers prediction without transforming them into real number and solve the optimal weight of integral development coefficient by genetic algorithm so as to avoid the distortion of prediction results. Moreover, the Markov model is used to modify residual sequences to further improve the modeling accuracy.

scholarly journals An SEIR Model for Assessment of Current COVID-19 Pandemic Situation in the UK

2020 ◽  
Author(s):  
Peiliang Sun ◽  
Kang Li
Keyword(s):  
Seasonal Influenza ◽  
Time Lag ◽  
Seir Model ◽  
Infected People ◽  
Proposed Model ◽  
Lag Effect ◽  
Novel Coronavirus ◽  
The Uk ◽  
Specific Symptoms ◽  
Limited Testing

AbstractThe ongoing COVID-19 pandemic spread to the UK in early 2020 with the first few cases being identified in late January. A rapid increase in confirmed cases started in March, and the number of infected people is however unknown, largely due to the rather limited testing scale. A number of reports published so far reveal that the COVID-19 has long incubation period, high fatality ratio and non-specific symptoms, making this novel coronavirus far different from common seasonal influenza. In this note, we present a modified SEIR model which takes into account the time lag effect and probability distribution of model states. Based on the proposed model, it is estimated that the actual total number of infected people by 1 April in the UK might have already exceeded 610,000. Average fatality rates under different assumptions at the beginning of April 2020 are also estimated. Our model also reveals that the R0 value is between 7.5–9 which is much larger than most of the previously reported values. The proposed model has a potential to be used for assessing future epidemic situations under different intervention strategies.

A novel GM(1,N) model based on interval gray number and its application to research on smog pollution

Kybernetes ◽  
2019 ◽  
Vol 49 (3) ◽  
pp. 753-778
Author(s):  
Pingping Xiong ◽  
Zhiqing He ◽  
Shiting Chen ◽  
Mao Peng
Keyword(s):  
Prediction Model ◽  
Practical Significance ◽  
Upper And Lower Bounds ◽  
Gray Model ◽  
Number Sequence ◽  
Mathematical Methods ◽  
Public Attention ◽  
Content Type ◽  
Model Based ◽  
Definition Of

Purpose In recent years, domestic smog has become increasingly frequent and the adverse effects of smog have increasingly become the focus of public attention. It is a way to analyze such problems and provide solutions by mathematical methods. Design/methodology/approach This paper establishes a new gray model (GM) (1,N) prediction model based on the new kernel and degree of grayness sequences under the case that the interval gray number distribution information is known. First, the new kernel and degree of grayness sequences of the interval gray number sequence are calculated using the reconstruction definition of the kernel and degree of grayness. Then, the GM(1,N) model is formed based on the above new sequences to simulate and predict the kernel and degree of the grayness of the interval gray number sequence. Finally, the upper and lower bounds of the interval gray number are deduced based on the calculation formulas of the kernel and degree of grayness. Findings To verify further the practical significance of the model proposed in this paper, the authors apply the model to the simulation and prediction of smog. Compared with the traditional GM(1,N) model, the new GM(1,N) prediction model established in this paper has better prediction effect and accuracy. Originality/value This paper improves the traditional GM(1,N) prediction model and establishes a new GM(1,N) prediction model in the case of the known distribution information of the interval gray number of the smog pollutants concentrations data.

scholarly journals A multi-objective evolutionary algorithm-based soft computing model for educational data mining

2017 ◽  
Vol 12 (1) ◽  
pp. 106-123
Author(s):  
Choo Jun Tan ◽  
Ting Yee Lim ◽  
Chin Wei Bong ◽  
Teik Kooi Liew
Keyword(s):  
Student Achievement ◽  
Evolutionary Algorithm ◽  
Soft Computing ◽  
Real World ◽  
Classification Accuracy ◽  
Content Type ◽  
Computing Model ◽  
Model Based ◽  
Proposed Model

Purpose The purpose of this paper is to propose a soft computing model based on multi-objective evolutionary algorithm (MOEA), namely, modified micro genetic algorithm (MmGA) coupled with a decision tree (DT)-based classifier, in classifying and optimising the students’ online interaction activities as classifier of student achievement. Subsequently, the results are transformed into useful information that may help educator in designing better learning instructions geared towards higher student achievement. Design/methodology/approach A soft computing model based on MOEA is proposed. It is tested on benchmark data pertaining to student activities and achievement obtained from the University of California at Irvine machine learning repository. Additional, a real-world case study in a distance learning institution, namely, Wawasan Open University in Malaysia has been conducted. The case study involves a total of 46 courses collected over 24 consecutive weeks with students across the entire regions in Malaysia and worldwide. Findings The proposed model obtains high classification accuracy rates at reduced number of features used. These results are transformed into useful information for the educational institution in our case study in an effort to improve student achievement. Whether benchmark or real-world case study, the proposed model successfully reduced the number features used by at least 48 per cent while achieving higher classification accuracy. Originality/value A soft computing model based on MOEA, namely, MmGA coupled with a DT-based classifier, in handling educational data is proposed.

scholarly journals Developing Islamic crowdfunding website platform for startup companies in Indonesia

2019 ◽  
Vol 11 (5) ◽  
pp. 1041-1053 ◽  
Author(s):  
Achsania Hendratmi ◽  
Muhamad Nafik Hadi Ryandono ◽  
Puji Sucia Sukmaningrum
Keyword(s):  
Group Discussion ◽  
Effective Means ◽  
Sustainable Business ◽  
Content Type ◽  
Model Based ◽  
Alternative Funding ◽  
Depth Interview ◽  
Startup Company ◽  
The Government ◽  
Effective Development

Purpose This study aims to develop an Islamic crowdfunding model based on a website platform for startup companies. Design/methodology/approach Apart from reviewing related literature, specifically focus group discussion with 16 CEO of startup companies, in-depth interview with two crowdfunding provider, Fiqh expert and technology platform expert for the development of an Islamic crowdfunding website platform for startup companies. Findings The concept of Islamic crowdfunding is recommended as a funding solution for small and medium-sized enterprises and startup companies. Therefore, it was deemed crucial for this study to develop an Islamic crowdfunding model based on a website platform as a form of innovative acceleration to provide alternative funding for a startup company, which subsequently expands to a growing and sustainable business. Furthermore, the use of a website platform for the operation of a crowdfunding mechanism is deemed as an effective means to link cross-geographical investors with the startup company owners in Indonesia, specifically East Java. Practical implications Islamic crowdfunding website platform can be the solution for startup companies to obtain capital funds while startup companies are not able to provide collateral to attain financial assistance and experience problems. Expectedly, the government should provide legality, regulation, licensing and socialization matters pertaining to crowdfunding to obtain legal legality from the country. Originality/value There is still no research to develop the Islamic crowdfunding model using a website platform. This study was expected to provide essential insights on the effective development of an Islamic crowdfunding website platform integrated with startup companies, investors and Sharia committee.

An equivalent stress method to account for local buckling in beam finite elements subjected to fire

2019 ◽  
Vol 10 (3) ◽  
pp. 340-353 ◽  
Author(s):  
Chrysanthos Maraveas ◽  
Thomas Gernay ◽  
Jean-Marc Franssen
Keyword(s):  
Finite Elements ◽  
Constitutive Model ◽  
Yield Stress ◽  
Equivalent Stress ◽  
Local Buckling ◽  
Bernoulli Beam ◽  
Content Type ◽  
Model Based ◽  
Proposed Model ◽  
Practical Implications

Purpose The purpose of this paper is to present an improved temperature-dependent constitutive model for steel that accounts for local instabilities of slender plates using an effective stress-based method. This model can be easily implemented for use with Bernoulli beam finite elements (FEs) in the fire situation. Design/methodology/approach The constitutive model is derived by calibration on parametric numerical analysis on isolated plates subject to buckling at different elevated temperatures. The model is implemented in the FE software SAFIR and validation is performed against experimental and shell element analysis results. Findings A constitutive model based on an equivalent stress method is proposed as an efficient way to consider local buckling in steel members exposed to fire. The proposed stress–strain–temperature relationship is asymmetric and is modified in compression only, by reducing the proportional limit, the yield stress and the strain at yield stress. The reduction of these parameters depends on the plate’s boundary conditions, slenderness and temperature. The validation of the proposed model shows good agreement over a range of profile dimensions, temperatures and steel grades. Research limitations/implications The model is still giving conservative results for large compressive load eccentricities. An enhanced model is under development to improve the predictive capability under large eccentricities. Practical implications The proposed model, easily implemented into any finite element software, allows using fibre type (Bernoulli) beam FEs for modelling structures made of slender sections. This has major practical implications as beam elements are the workhorse used for simulating the behaviour of structures in fire. This model, thus makes it possible to simulate large structures with slender steel sections at a limited computational cost. Originality/value The paper presents a novel steel constitutive model based on an innovative approach to capture local buckling at the material level using an equivalent stress approach. The theoretical development, validation and perspectives for future improvements are presented.

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