The fractional neural grey system model and its application
作者：
Xie, Wanli;Wu, Wen-Ze;Xu, Zhenguo;Liu, Caixia;Zhao, Keyun
期刊：
Applied Mathematical Modelling ,2023年121:43-58 ISSN：0307-904X
通讯作者：
Wu, WZ
作者机构：
[Zhao, Keyun; Xie, Wanli; Xu, Zhenguo] Qufu Normal Univ, Sch Commun, Rizhao 276826, Peoples R China.;[Wu, Wen-Ze; Wu, WZ] Cent China Normal Univ, Sch Econ & Business Adm, Wuhan 430079, Peoples R China.;[Xu, Zhenguo] Jiangsu Normal Univ, Coll Intelligent Educ, Xuzhou 221008, Peoples R China.
通讯机构：
[Wu, WZ ] C;Cent China Normal Univ, Sch Econ & Business Adm, Wuhan 430079, Peoples R China.
关键词：
Grey system model;Fractional -order accumulation;Grey neural network;Predictive model
摘要：
Recently, grey system, neural network, and fractional order calculus theory have become popular research areas, and an increasing number of scholars have joined these studies, conducted illuminating research, and produced a number of significant results. Numerous research studies have demonstrated that these three strategies are crucial to solving a wide range of practical problems. In this paper, we present a fractional order neural grey system model with a three-layer structure in which the input of the network is a fractional order cumulative sequence, and the output is a predicted value in order to maximize the bene-fits of each of the three elements. The purpose of this research is to present a strategy for reducing the number of conditions in order to improve the stability of parameter estima-tion by using QR decomposition. The order of the models is determined by an intelligent optimization algorithm. Finally, real-world examples are used to validate the model's va-lidity, and experimental results indicate that the newly presented model is more accurate than previous models. (c) 2023 Elsevier Inc. All rights reserved.
语种：
英文
展开
A novel discrete GM(2,1) model with a polynomial term for forecasting electricity consumption
作者：
Zeng, Liang;Liu, Chong;Wu, Wen-Ze
期刊：
Electric Power Systems Research ,2023年214:108926 ISSN：0378-7796
通讯作者：
Wu, Wen-Ze(bsstatistics@126.com)
作者机构：
[Zeng, Liang] Guangdong Technol Coll, Sch Basic Courses, Zhaoqing 526100, Peoples R China.;[Liu, Chong] Northeastern Univ, Coll Sci, Shenyang 110819, Peoples R China.;[Wu, Wen-Ze] Cent China Normal Univ, Sch Econ & Business Adm, Wuhan 430079, Peoples R China.
通讯机构：
[Wen-Ze Wu] S;School of Economics and Business Administration, Central China Normal University, Wuhan 430079, China
关键词：
Grey model;Polynomial;Tikhonov regularization;Electricity consumption
摘要：
The forecast of electrical energy demand has played an increasingly relevant role in sustainable electrical power system. This paper develops a new method for forecasting China's per capita living electricity consumption by grey modelling technique. Considering the multiple and mixed change patterns, a novel discrete grey model with polynomial term (abbreviated as DGM(2,1,kn)) is proposed in this study. Firstly, the polynomial term is introduced into the discrete DGM(2,1) model. Secondly, the Tikhonov regularization method is employed to solve the overfitting problem. Lastly, two published cases and China's per capita living electricity consumption are used to validate the generalization and adaptability of the newly-designed model. The numerical results of such experiments show that the proposed model outperforms other competitive models in terms of accuracy level. Therefore, the projections of China's per capita living electricity consumption in 2020 and 2025 have been made for providing a solid reference for the formulation of electrical power strategies. © 2022 Elsevier B.V.
语种：
英文
展开
A novel conformable fractional nonlinear grey multivariable prediction model with marine predator algorithm for time series prediction
作者：
Zhu, Hegui;Liu, Chong;Wu, Wenze;Xie, Wanli
期刊：
Computers & Industrial Engineering ,2023年180:109278 ISSN：0360-8352
通讯作者：
Liu, C
作者机构：
[Liu, Chong; Liu, C; Zhu, Hegui] Northeastern Univ, Coll Sci, Shenyang 110819, Peoples R China.;[Wu, Wenze] Cent China Normal Univ, Sch Econ & Business Adm, Wuhan 430079, Peoples R China.;[Xie, Wanli] Nanjing Normal Univ, Inst EduInfo Sci & Engn, Nanjing 210097, Peoples R China.
通讯机构：
[Liu, C ] N;Northeastern Univ, Coll Sci, Shenyang 110819, Peoples R China.
关键词：
Marine predator algorithm;Multivariable grey prediction model;The modified conformable fractional-order accumulation operator;Time-delay effect
摘要：
To promote the development of multivariate prediction modelling in small sample environments, this paper constructs a new multivariate prediction model named CFDNGBM(r,N) by integrating the marine predator algorithm (MPA), the modified conformable fractional-order accumulation operation (MCFAO) and the grey prediction model. In CFDNGBM(r,N), the MCFAO and time-delay polynomial are used to enhance the model prediction performance, the backward difference operation is used to activate the unbiasedness, and the unbiased regularization algorithm is used to estimate the model parameters. In addition, the MPA is used to optimize the hyperparameters in the model. The experimental results show that the CFDNGBM(r,N) outperforms the 12 benchmark algorithms and all the optimization measures are effective, both of which confirm the effectiveness of the proposed methods. © 2023 Elsevier Ltd
语种：
英文
展开
Do institutional investors facilitate corporate environmental innovation?
作者：
Xu, Jia;Zeng, Shu;Qi, Shaozhou;Cui, Jingbo
期刊：
Energy Economics ,2023年117:106472 ISSN：0140-9883
通讯作者：
Zeng, Shu(zengshu@zuel.edu.cn)
作者机构：
[Xu, Jia] Cent China Normal Univ, Sch Econ & Business Adm, Wuhan, Peoples R China.;[Zeng, Shu] Zhongnan Univ Econ & Law, Sch Accounting, Wuhan, Peoples R China.;[Qi, Shaozhou] Wuhan Univ, Climate Change & Energy Econ Study Ctr, Econ & Management Sch, Wuhan, Peoples R China.;[Qi, Shaozhou] Hubei Univ Econ, Ctr Hubei Cooperat Innovat Emiss Trading Syst, Wuhan, Peoples R China.;[Cui, Jingbo] Duke Kunshan Univ, Environm Res Ctr, Div Social Sci, Suzhou, Peoples R China.
通讯机构：
[Shu Zeng] S;School of Accounting at Zhongnan University of Economics and Law, China
关键词：
Institutional investors;Environmental innovation;Patent;Corporate social responsibility
摘要：
This paper addresses whether institutional investors drive firms’ innovation direction toward environmentally friendly technologies. The data pertain to comprehensive environmental patents filed by Chinese publicly-listed firms in the manufacturing and public utility sectors during the 2003–2015 period. We find that institutional investors are associated with higher ratios of environmental patents in total patents for firms in the pollution-intensive sectors than those in the non-pollution-intensive sectors. Institutional investors exert the roles of financial support and corporate governance in pursuit of monitoring firms’ long-term sustainable innovation. They further facilitate the information disclosure on corporate social responsibility. © 2022 Elsevier B.V.
语种：
英文
展开
Synergy between pollution control and carbon reduction: China's evidence
作者：
Zhu, Junpeng;Wu, Shaohui;Xu, Junbing
期刊：
Energy Economics ,2023年119:106541 ISSN：0140-9883
通讯作者：
Xu, Junbing(xu940981226@163.com)
作者机构：
[Zhu, Junpeng; Wu, Shaohui] Cent China Normal Univ, Sch Econ & Business Adm, Wuhan, Peoples R China.;[Xu, Junbing] Minjiang Univ, NewHuadu Business Sch, Fuzhou 361005, Fujian, Peoples R China.
通讯机构：
[Junbing Xu] N;NewHuadu Business School, Minjiang University, Fuzhou City, Fujian Province 361005, PR China
关键词：
Environmental regulation;Carbon reduction;Synergy;China
摘要：
The proposal of dual carbon goals indicates that China's overall ecological environment protection will focus on carbon reduction in the future. Our concern is whether the existing environmental regulatory policies focusing on pollutants emission have a synergistic effect on carbon reduction. Based on China's 11th Five-Year Plan, this paper examines the synergy between pollution control and carbon reduction by using the data at China's 'province-industry-year' level and constructing a difference-in-difference-in-differences analysis framework. The results show that the implementation of the 11th Five-Year Plan has significantly reduced the CO2 emissions of polluting industries in provinces with stricter environmental regulations, which means that it has played an important role in promoting carbon neutrality. Moreover, the mechanism analysis suggests that the 11th Five-Year Plan can achieve CO2 reduction through energy substitution and technological innovation, but the effect of the energy structure transformation is not significant. The results also indicate that climate benefit was realized at the cost of declining output and employment. The findings of this paper contribute to an in-depth understanding of the synergistic system of reducing pollution and carbon emissions and provide empirical evidence for formulating development strategies and policies to achieve synergies, which has important practical guiding significance. © 2023
语种：
英文
展开
Weakened fractional-order accumulation operator for ill-conditioned discrete grey system models
作者：
Zhu, Hegui;Liu, Chong;Wu, Wen-Ze;Xie, Wanli;Lao, Tongfei
期刊：
Applied Mathematical Modelling ,2022年111:349-362 ISSN：0307-904X
通讯作者：
Liu, Chong(liuchong@stumail.neu.edu.cn)
作者机构：
[Liu, Chong; Lao, Tongfei; Zhu, Hegui] Northeastern Univ, Coll Sci, Shenyang 110819, Peoples R China.;[Wu, Wen-Ze] Cent China Normal Univ Wuhan, Sch Econ, Wuhan 430079, Peoples R China.;[Wu, Wen-Ze] Cent China Normal Univ Wuhan, Business Adm, Wuhan 430079, Peoples R China.;[Xie, Wanli] Nanjing Normal Univ, Inst EduInfo Sci & Engn, Nanjing 210097, Peoples R China.
通讯机构：
[Chong Liu] C;College of Sciences, Northeastern University, Shenyang, 110819, China
关键词：
Discrete grey forecasting models;Ill-condition;Multiplicative transformation;Weakened fractional-order accumulation operator
摘要：
In this study, the weakened fractional-order accumulation operator for alleviating the ill-condition of discrete grey system models with the aim of improving the grey system theory is proposed. It is found that the weakened fractional-order accumulation operator composed of the improved fractional-order accumulation operator and the multiplicative transformation can not only alleviate the ill-condition of the system by decreasing the differences between the elements of the columns (rows) in the coefficient matrix but also further enhance the prediction performance of the models. Therefore, the weakened fractional-order accumulation operator is an effective improvement measure. The demonstration of the unbiasedness and affine transformation property of the discrete grey forecasting models with the weakened fractional-order accumulation operator further strengthens the theoretical basis of this new system. Two real-world time series are used as cases to demonstrate the effectiveness of the discrete grey system models with the weakened fractional-order accumulation operator compared with discrete grey forecasting models based on five other different accumulation operators(1-order accumulation operation, new information accumulation operation, fractional-order accumulation operator, damping accumulative generating operator and the conformable fractional-order accumulation operator). The results of the comparative analysis show that the proposed weakened fractional order accumulation operator can not only substantially reduce the ill-condition of the models but also have good predictive performance, both of which confirm the feasibility and validity of the method. © 2022 Elsevier Inc.
语种：
英文
展开
An optimized conformable fractional non-homogeneous gray model and its application
作者：
Xie, Wanli;Wu, Wen-Ze* ;Zhang, Tao;Li, Qi
期刊：
Communications in Statistics - Simulation and Computation ,2022年51(10):5988-6003 ISSN：0361-0918
通讯作者：
Wu, Wen-Ze
作者机构：
[Xie, Wanli] Nanjing Normal Univ, Inst EduInfo Sci & Engn, Nanjing, Peoples R China.;[Wu, Wen-Ze; Li, Qi] Cent China Normal Univ, Sch Econ & Business Adm, Wuhan, Peoples R China.;[Zhang, Tao] Guangxi Univ Sci & Technol, Sch Sci, Liuzhou, Peoples R China.
通讯机构：
[Wu, Wen-Ze] C;Cent China Normal Univ, Sch Econ & Business Adm, Wuhan, Peoples R China.
关键词：
CFONGM(1,1,k,c);Conformable fractional accumulation;Gray model;Particle swarm optimization
摘要：
Developing a robust, accurate forecasting model and improving the prediction abilities of the limited historical data that lacks statistical rules has become a top priority. To address this problem, an improved conformable fractional non-homogeneous gray model, namely CFONGM(1,1,k,c), is proposed. Combining the dynamic background-value and particle swarm optimization algorithm to further improve forecasting ability of the existing gray model. In which matrix perturbation theory is employed to prove that the novel model conforms the principle of new information priority and has a smaller perturbation bound of solution. The two empirical examples of educational funds and new students enrollment of regular institutions of higher education of China are employed to examine the prediction accuracy of the novel model. The results show that the novel model has a better prediction performance compared with other competitive models. © 2020 Taylor & Francis Group, LLC.
语种：
英文
展开
A time power-based grey model with conformable fractional derivative and its applications
作者：
Wu, Wen-Ze;Zeng, Liang;Liu, Chong;Xie, Wanli;Goh, Mark
期刊：
CHAOS SOLITONS & FRACTALS ,2022年155:111657 ISSN：0960-0779
通讯作者：
Zeng, Liang(zengliang19820809@126.com)
作者机构：
[Wu, Wen-Ze] Cent China Normal Univ, Sch Econ & Business Adm, Wuhan 430079, Peoples R China.;[Zeng, Liang] Guangdong Technol Coll, Sch Basic Courses, Zhaoqing 526100, Peoples R China.;[Liu, Chong] Northeastern Univ, Sch Sci, Shenyang 110819, Peoples R China.;[Xie, Wanli] Nanjing Normal Univ, Inst EduInfo Sci & Engn, Nanjing 210097, Peoples R China.;[Goh, Mark; Wu, Wen-Ze] Natl Univ Singapore, NUS Business Sch, Logist Inst Asia Pacific, Singapore, Singapore.
通讯机构：
[Liang Zeng] S;School of basic courses, Guangdong Technology College, Zhaoqing 526100, China
关键词：
Conformable fractional derivative;Grey modeling technique;Time power;Particle swarm optimization
摘要：
The fractional grey model and its deformation forms have been appealed interest of research in practice due to its strong adaptability by merits of falling from the integer-order form into the fractional. This paper proposes an optimised time power-based grey model by the introduction of conformable fractional derivative into the conventional model. As a result, a newly-designed approach, namely the time power-based grey model with conformable fractional derivative (referred to as CFGM( phi, 1 , t alpha)), is proposed thereby. Specifically, the model establishment, system parameter estimation and explicit expression are comprehensively implemented. In particular, several properties for the proposed approach are emphasized to interpret the superiority of the newly-designed model from a theoretical analysis perspective. The particle swarm optimization technique is then employed to determine the emerging coefficients such as the order of the conformable fractional derivative and time-power coefficient. Finally, four real-world cases are chosen to certify the applicability of the proposed model in contrast with other benchmark models and, the empirical results show that the newly-designed model outperforms other competing models, thus obtaining some managerial insights from these numerical experiments.(c) 2021 Elsevier Ltd. All rights reserved.
语种：
英文
展开
Clustering and compatibility-based approach for large-scale group decision making with hesitant fuzzy linguistic preference relations: An application in e-waste recycling
作者：
Zheng, Chengli;Zhou, Yuanyuan;Zhou, Ligang;Chen, Huayou
期刊：
Expert Systems with Applications ,2022年197:116615 ISSN：0957-4174
通讯作者：
Zhou, Yuanyuan(zyy_xx@126.com)
作者机构：
[Zhou, Yuanyuan; Zheng, Chengli] Cent China Normal Univ, Financial Engn Res Ctr, Sch Econ & Business Adm, Wuhan 430079, Peoples R China.;[Chen, Huayou; Zhou, Ligang] Anhui Univ, Sch Math Sci, Hefei 230601, Anhui, Peoples R China.;[Zhou, Ligang] Anhui Univ, Ctr Appl Math, Hefei 230601, Peoples R China.
通讯机构：
[Yuanyuan Zhou] S;School of Economics and Business Administration, Financial Engineering Research Center, Central China Normal University, Wuhan 430079, China
关键词：
Clustering;Compatibility measure;Hesitant fuzzy linguistic preference relation;Large-scale group decision making;Similarity measure
摘要：
Considering that large-scale group decision making (LSGDM) has been widely concentrated on clustering and lower compatibility problems, this paper focuses on clustering and consensus reaching of hesitant fuzzy linguistic preference relations (HFLPRs) in LSGDM. Firstly, we define the hesitant degree and the fuzzy degree functions for hesitant fuzzy linguistic term sets (HFLTSs) according to their scale and deviation of elements. To normalize HFLTSs with different length, a minimum deviation model based on the hesitant and the fuzzy degrees is developed. After that, we propose a new similarity measure and compatibility measure via integrating the hesitant and fuzzy degrees. Then a clustering process combining similarity and compatibility is used to assign large-scale experts into several clusters. The clustering method not only strengths the cohesion of subgroups, but also guarantees that HFLPRs in subgroups are acceptable compatibility. Moreover, a compatibility adjusting process with self-selected feedback mechanism is presented to improve the compatibility level of clusters until they reach a predefined threshold in selection process. And we combine the number of members in subgroups and the compatibility level of subgroups to determine weights of subgroups. Finally, a case of e-waste recycling and comparison are analyzed to show the availability of the proposed method. © 2022 Elsevier Ltd
语种：
英文
展开
An optimized nonlinear grey Bernoulli prediction model and its application in natural gas production
作者：
Liu, Chong;Lao, Tongfei;Wu, Wen-Ze;Xie, Wanli;Zhu, Hegui
期刊：
Expert Systems with Applications ,2022年194:116448 ISSN：0957-4174
通讯作者：
Zhu, HG
作者机构：
[Liu, Chong; Lao, Tongfei; Zhu, Hegui] Northeastern Univ, Coll Sci, Shenyang 110819, Peoples R China.;[Wu, Wen-Ze] Cent China Normal Univ, Sch Econ & Business Adm, Wuhan 430079, Peoples R China.;[Xie, Wanli] Nanjing Normal Univ, Inst EduInfo Sci & Engn, Nanjing 210097, Peoples R China.
通讯机构：
[Zhu, HG ] N;Northeastern Univ, Coll Sci, Shenyang 110819, Peoples R China.
关键词：
Algorithms;Grey Bernoulli model;Natural gas production;The weighted fractional accumulation generation operation
摘要：
Natural gas, an efficient, eco-friendly and clean green energy, has become one of the important energy structures of various countries in the world, accurately predicting the production of natural gas can help the national energy agency solve “gas shortage” problem. To accurately predict natural gas production in China, this paper establishes an optimized grey system model with weighted fractional accumulation generation operation (abbreviated as WFNGBM(1,1,N)). The proposed model has all the advantages of the GMP(1,1,N) model, NGBM(1,1) model and weighted fractional accumulation generation operation, which makes it have excellent prediction performance. Moreover, five outstanding intelligent optimization algorithms (whale optimization algorithm, marine predators algorithm, grasshopper optimization algorithm, equilibrium optimization algorithm and arithmetic optimization algorithm) are used to solve the hyperparameters of the WFNGBM(1,1,N) model. It is found that the WFNGBM(1,1,N) model has the characteristics of convertibility and small sample modeling, which indicates that it is a small sample prediction model with strong compatibility. After confirming the feasibility of the proposed model compared with its competing models by using natural gas production in Germany, Italy and Canada as examples, the proposed model is used to study China's natural gas production. The results show that this model is very suitable for predicting and analyzing natural gas production in China. Based on this, the WFNGBM(1,1,N) model is used to estimate China's natural gas production in the next three years, and some reasonable suggestions are given according to the development trend of natural gas production. © 2022 Elsevier Ltd
语种：
英文
展开
A MFO-based conformable fractional nonhomogeneous grey Bernoulli model for natural gas production and consumption forecasting
作者：
Zheng, Chengli;Wu, Wen-Ze* ;Xie, Wanli;Li, Qi
期刊：
Applied Soft Computing ,2021年99:106891 ISSN：1568-4946
通讯作者：
Wu, Wen-Ze
作者机构：
[Zheng, Chengli; Wu, Wen-Ze; Li, Qi] Cent China Normal Univ, Sch Econ & Business Adm, Wuhan 430079, Peoples R China.;[Xie, Wanli] Nanjing Normal Univ, Inst EduInfo Sci & Engn, Nanjing 210097, Peoples R China.
通讯机构：
[Wu, Wen-Ze] C;Cent China Normal Univ, Sch Econ & Business Adm, Wuhan 430079, Peoples R China.
关键词：
CFNHGBM(1, 1, k);Conformable fractional accumulation;Moth flame optimization (MFO);Natural gas
摘要：
The demand for natural gas is expected to continuously increase due to its significant role in the transition towards a low-carbon energy structure. Based on the nonhomogeneous grey model, a new method for estimating natural gas production and consumption is developed, namely, the conformable fractional nonhomogeneous grey Bernoulli model (denoted as CFNHGBM(1,1,k) for short). In the new method, the Bernoulli equation is first introduced into the existing differential equation. The traditional accumulation is then replaced with conformable fractional accumulation. Finally, the moth flame optimization (MFO) algorithm is applied to determine the structural parameters for the novel model. Moreover, when taking different values, the novel model will be changed into the existing grey serial models. Based on natural gas production and consumption from 2008 to 2018, we use the proposed model to predict future data from 2019 to 2021 in North America, and the forecasts show that the novel model performs better than other competitors. Furthermore, natural gas production and consumption maintain steady increasing trends with average annual growth rates of 3.29% and 2.02%, respectively. © 2020 Elsevier B.V.
语种：
英文
展开
Impact of China's new-type urbanization on energy intensity: A city-level analysis
作者：
Lin, Boqiang;Zhu, Junpeng
期刊：
Energy Economics ,2021年99:105292 ISSN：0140-9883
通讯作者：
Zhu, Junpeng(junpzhu@sina.com)
作者机构：
[Lin, Boqiang] School of Management, China Institute for Studies in Energy Policy, Collaborative Innovation Center for Energy Economics and Energy Policy, Xiamen University, Fujian;361005, China;[Zhu, Junpeng] School of Economics and Business Administration, Central China Normal University, Wuhan, China;[Lin, Boqiang] 361005, China
通讯机构：
[Junpeng Zhu] S;School of Economics and Business Administration, Central China Normal University, Wuhan, PR China
关键词：
China;Conditional β-convergence;Energy intensity;The new-type urbanization
摘要：
The new-type urbanization strategy proposed by the Chinese government is human-centered urbanization, which emphasizes the coordination of population, economy, society, and ecological environment. Despite extensive research on the impact of traditional urbanization, the impact of the new-type urbanization on energy efficiency is largely unknown. Based on the sample of 193 Chinese cities, this paper investigates the conditional convergence characteristics of energy intensity and explores the role of new-type urbanization on energy saving as well as its transmission channels. The results confirm the existence of condition β-convergence for energy intensity, and the new-type urbanization has a significant energy-saving effect with the effect being greater in resource-rich areas. Moreover, the mechanism analysis shows that the economic agglomeration effect, industrial structure effect, and technological progress effect are important transmission channels through which the new-type urbanization affects energy intensity. This paper adds new insights to understand the new-type urbanization process. © 2021 Elsevier B.V.
语种：
英文
展开
Predicting Chinese total retail sales of consumer goods by employing an extended discrete grey polynomial model
作者：
Liu, Chong;Xie, Wanli;Wu, Wen-Ze;Zhu, Hegui
期刊：
Engineering Applications of Artificial Intelligence ,2021年102:104261 ISSN：0952-1976
通讯作者：
Wu, Wen-Ze(wenzew@mails.ccnu.edu.cn)
作者机构：
[Liu, Chong; Zhu, Hegui] Northeastern Univ, Sch Sci, Shenyang 110819, Peoples R China.;[Xie, Wanli] Nanjing Normal Univ, Inst EduInfo Sci & Engn, Nanjing 210097, Peoples R China.;[Wu, Wen-Ze] Cent China Normal Univ, Sch Econ & Business Adm, Wuhan 430079, Peoples R China.
通讯机构：
[Wen-Ze Wu] S;School of Economics and Business Administration, Central China Normal University, Wuhan 430079, China
关键词：
Discretization technique;Retail sales of consumer goods;Weighted fractional accumulation;Whale optimization algorithm
摘要：
The total retail sales of consumer goods is not only an important indicator to measure the consumption level of the Chinese people, but also an important indicator of the national economy. Therefore, it is of great significance to analyze the development trend of Chinese total retail sales of consumer goods for the healthy development of Chinese economy. To explore the future development trend of Chinese total retail sales of consumer goods, this paper develops an extensive discrete grey model by the introduction of weighted fractional accumulation and discretization error, which is abbreviated as WFDPGM(1,1,tα) model. To further enhance the prediction performance of the proposed model, the whale optimization algorithm (WOA) is employed to determine the emerging coefficients. Three real cases are used to verify the effectiveness of the proposed model by comparing with other competing models. Lastly, based on Chinese retail sales of consumer goods from 2005 to 2019, the numerical results show that the proposed model outperforms other benchmarks, and the future development of Chinese retail sales of consumer goods will maintain an increasing trend, reaching 533033.15×109 yuan in 2025. And some managerial insights are obtained from numerical examples. © 2021 Elsevier Ltd
语种：
英文
展开
Equity concentration and investment efficiency of energy companies in China: Evidence based on the shock of deregulation of QFIIs
作者：
Wang, Jiangyuan;Wang, Hua* ;Wang, Di
期刊：
Energy Economics ,2021年93:105032 ISSN：0140-9883
通讯作者：
Wang, Hua
作者机构：
[Wang, Jiangyuan] Cent China Normal Univ, Sch Econ & Business Adm, 152 Luoyu Rd, Wuhan 430079, Hubei, Peoples R China.;[Wang, Di; Wang, Hua] Zhongnan Univ Econ & Law, Sch Accounting, 182 Nanhu Ave, Wuhan 430073, Hubei, Peoples R China.
通讯机构：
[Wang, Hua] Z;Zhongnan Univ Econ & Law, Sch Accounting, 182 Nanhu Ave, Wuhan 430073, Hubei, Peoples R China.
关键词：
Agency cost;Equity concentration;Information environment;Investment efficiency
摘要：
This paper empirically tests the impact of equity concentration on the investment efficiency of Chinese energy companies based on the shock that the shareholding ratio restriction of qualified foreign institutional investors (QFIIs) is relaxed. We find that equity concentration significantly improves energy companies' investment efficiency in China. Equity concentration affects the investment efficiency by influencing the first type of agency cost and the information environment. Equity concentration plays a significant role in improving the investment efficiency when the decision-making power is decentralized while the external environment is complex. © 2020 Elsevier B.V.
语种：
英文
展开
Forecasting natural gas consumption of China by using a novel fractional grey model with time power term
作者：
Liu, Chong;Wu, Wen-Ze;Xie, Wanli;Zhang, Tao;Zhang, Jun
期刊：
Energy Reports ,2021年7:788-797 ISSN：2352-4847
通讯作者：
Wu, Wen-Ze(wenzew@mails.ccnu.edu.cn)
作者机构：
[Liu, Chong; Zhang, Jun] Inner Mongolia Agr Univ, Sch Sci, Hohhot 010018, Peoples R China.;[Wu, Wen-Ze] Cent China Normal Univ, Sch Econ & Business Adm, Wuhan 430079, Peoples R China.;[Xie, Wanli] Nanjing Normal Univ, Inst EduInfo Sci & Engn, Nanjing 210097, Peoples R China.;[Zhang, Tao] Guangxi Univ Sci & Technol, Sch Sci, Liuzhou 545006, Peoples R China.
通讯机构：
[Wen-Ze Wu; Tao Zhang] S;School of Economics and Business Administration, Central China Normal University, Wuhan 430079, China<&wdkj&>School of Science, Guangxi University of Science and Technology, Liuzhou 545006, China
关键词：
Natural gas consumption;DFGM(1,1,t(alpha));Quantum Genetic Algorithm (QGA)
摘要：
Natural gas, an important low-carbon and clean energy, is increasingly replacing high-pollution sources such as coal and gasoline. Accurate natural gas consumption forecasts are important to policy makers in making plans, saving costs, and improving efficiency. This study developed a discrete fractional grey model with a time power term (denoted as DFGM(1,1,t(alpha))) with reference to the discretization technique. The new model is simplified, generalized, and overcomes existing model drawbacks. Moreover, the quantum genetic algorithm (QGA) is used to determine the new coefficients, namely, the fractional order and time-power coefficient. Based on observations from 2001 to 2018, the novel model predicted the natural gas consumption in China from 2019 to 2025 better than other benchmarks. Specifically, natural gas consumption was predicted to maintain a steady upward trend, reaching 315.30 billion cubic metres (hereinafter referred to as Bcm) in 2020 and 439.14 Bcm in 2025. Reasonable suggestions are put forward for associated sectors based on the forecasts. (C) 2021 The Author(s). Published by Elsevier Ltd.
语种：
英文
展开
The Influence of Long-Term and Short-Term Institutional Investors on Complicated Mispricing of Stocks
作者：
Liu, Bing*
期刊：
Complexity ,2020年2020:8833180:1-8833180:14 ISSN：1076-2787
通讯作者：
Liu, Bing
作者机构：
[Liu, Bing] Cent China Normal Univ, Sch Econ & Business Adm, Wuhan 430079, Peoples R China.;[Liu, Bing] Huainan Normal Univ, Sch Econ & Management, Huainan 232038, Peoples R China.
通讯机构：
[Liu, Bing] C;[Liu, Bing] H;Cent China Normal Univ, Sch Econ & Business Adm, Wuhan 430079, Peoples R China.;Huainan Normal Univ, Sch Econ & Management, Huainan 232038, Peoples R China.
摘要：
Taking Chinese listed companies from 2009 to 2017 as the research objects, this paper aims at exploring the heterogeneous effect of short-term and long-term institutional investors on stock mispricing. The empirical study finds that long-term institutional investors have an inhibiting effect on stock mispricing, while short-term institutional investors have an opposite effect. When the company information opacity is high, long-term institutional investors have a more obvious inhibiting effect on stock mispricing while short-term institutional investors have a more obvious promoting effect on stock mispricing. When the attention of analysts is enhanced, long-term institutional investors further restrain the stock mispricing while short-term institutional investors further promote the stock mispricing. © 2020 Bing Liu.
语种：
英文
展开
Forecasting annual electricity consumption in China by employing a conformable fractional grey model in opposite direction
作者：
Xie, Wanli;Wu, Wen-Ze* ;Liu, Chong;Zhao, Jingjie
期刊：
Energy ,2020年202:117682 ISSN：0360-5442
通讯作者：
Wu, Wen-Ze
作者机构：
[Zhao, Jingjie; Xie, Wanli] Nanjing Normal Univ, Inst EduInfo Sci & Engn, Nanjing 210097, Peoples R China.;[Wu, Wen-Ze] Cent China Normal Univ, Sch Econ & Business Adm, Wuhan 430079, Peoples R China.;[Liu, Chong] Inner Mongolia Agr Univ, Sch Sci, Hohhot 010018, Peoples R China.
通讯机构：
[Wu, Wen-Ze] C;Cent China Normal Univ, Sch Econ & Business Adm, Wuhan 430079, Peoples R China.
关键词：
Conformable fractional accumulation;Electricity consumption;Grey model;Quantum inspired evolutionary algorithm
摘要：
Electric power makes a significant contribution to economic development. Predicting annual electricity consumption is becoming increasingly crucial for electric power utility planning and economic development. To address this problem, a novel conformable fractional grey model in opposite direction is presented to predict annual electricity consumption in China. Firstly, the computational formulas for the novel model are deduced by grey modelling method and the effectiveness of the novel model is proved by matrix perturbation theory. Secondly, the optimal parameters are determined by quantum inspired evolutionary algorithm. Thirdly, two empirical examples are taken to validate the prediction accuracy of the novel model. Finally, the proposed model is applied to predict electricity consumption of Beijing, Fujian and Shandong. The results show that the novel model is superior to other six competitive models. Besides, electricity consumption of these regions in next five years are predicted, which can well serve a benchmark research and provide a relatively reliable reference for economic and electric sectors. © 2020 Elsevier Ltd
语种：
英文
展开
Continuous grey model with conformable fractional derivative
作者：
Xie, Wanli;Liu, Caixia;Wu, Wen-Ze* ;Li, Weidong;Liu, Chong
期刊：
CHAOS SOLITONS & FRACTALS ,2020年139:110285 ISSN：0960-0779
通讯作者：
Wu, Wen-Ze
作者机构：
[Liu, Caixia; Xie, Wanli; Li, Weidong] Nanjing Normal Univ, Inst EduInfo Sci & Engn, Nanjing 210097, Jiangsu, Peoples R China.;[Wu, Wen-Ze] Cent China Normal Univ, Sch Econ & Business Adm, Wuhan 430079, Peoples R China.;[Liu, Chong] Inner Mongolia Agr Univ, Sch Sci, Hohhot 010018, Peoples R China.
通讯机构：
[Wu, Wen-Ze] C;Cent China Normal Univ, Sch Econ & Business Adm, Wuhan 430079, Peoples R China.
关键词：
Conformable fractional derivative;Grey-based model;CCFGM(1,1);Prediction performance
摘要：
Fractional-order grey models have received more attention owing to superiority to integer-order ones in terms of the prediction performance. In this paper, to further improve the performance of grey-based model, a new method based on conformable fractional derivative, the continuous conformable fractional grey model (denoted as CCFGM(1,1) for short), is proposed. In comparison with the traditional fractional-order grey models, the novel model possesses the simpler computation procedure. The numerical results of two real cases show that the prediction performance of the novel model is superior to other competitive models and therefore, it is proved that this model effectively brings forth the improvement of the existing fractional-order grey models. (C) 2020 Elsevier Ltd. All rights reserved.
语种：
英文
展开
Forecasting Natural Gas Consumption of China Using a Novel Grey Model
作者：
Zheng, Chengli;Wu, Wen-Ze* ;Jiang, Jianming;Li, Qi
期刊：
Complexity ,2020年2020:3257328:1-3257328:9 ISSN：1076-2787
通讯作者：
Wu, Wen-Ze
作者机构：
[Zheng, Chengli; Wu, Wen-Ze; Li, Qi] Cent China Normal Univ, Sch Econ & Business Adm, Wuhan 430079, Peoples R China.;[Jiang, Jianming] Baise Univ, Sch Math & Stat, Baise 533000, Peoples R China.
通讯机构：
[Wu, Wen-Ze] C;Cent China Normal Univ, Sch Econ & Business Adm, Wuhan 430079, Peoples R China.
摘要：
As is known, natural gas consumption has been acted as an extremely important role in energy market of China, and this paper is to present a novel grey model which is based on the optimized nonhomogeneous grey model (ONGM (1,1)) in order to accurately predict natural gas consumption. This study begins with proving that prediction results are independent of the first entry of original series using the product theory of determinant; on this basis, it is a reliable approach by inserting an arbitrary number in front of the first entry of original series to extract messages, which has been proved that it is an appreciable approach to increase prediction accuracy of the traditional grey model in the earlier literature. An empirical example often appeared in testing for prediction accuracy of the grey model is utilized to demonstrate the effectiveness of the proposed model; the numerical results indicate that the proposed model has a better prediction performance than other commonly used grey models. Finally, the proposed model is applied to predict China's natural gas consumption from 2019 to 2023 in order to provide some valuable information for energy sectors and related enterprises. © 2020 Chengli Zheng et al.
语种：
英文
展开
Application of a novel fractional grey prediction model with time power term to predict the electricity consumption of India and China
作者：
Liu, Chong;Wu, Wen-Ze* ;Xie, Wanli;Zhang, Jun
期刊：
CHAOS SOLITONS & FRACTALS ,2020年141:110429 ISSN：0960-0779
通讯作者：
Wu, Wen-Ze
作者机构：
[Liu, Chong; Zhang, Jun] Inner Mongolia Agr Univ, Sch Sci, Hohhot 010018, Peoples R China.;[Wu, Wen-Ze] Cent China Normal Univ, Sch Econ & Business Adm, Wuhan 430079, Peoples R China.;[Xie, Wanli] Nanjing Normal Univ, Inst EduInfo Sci & Engn, Nanjing 210097, Peoples R China.
通讯机构：
[Wu, Wen-Ze] C;Cent China Normal Univ, Sch Econ & Business Adm, Wuhan 430079, Peoples R China.
关键词：
Electricity consumption;FPGM(1,1,t(alpha));Metabolic mechanism;Quantum genetic algorithm (QGA)
摘要：
As one of the most important energy sources, electricity plays an important role in power system and is the main driving force for the development of the country and society. Accurately forecasting electricity consumption is of significance of the power system and market. For this, a novel fractional grey polynomial model with time power term (denoted as FPGM(1,1,tα)) is developed for forecasting electricity consumption of India and China, in which the grey polynomial model is optimized by combining time power term and fractional accumulation, the quantum genetic algorithm (QGA) is then applied to determine the model parameters. Particularly, the proposed model can be changed to other existing models by adjusting systematic coefficient. The numerical results shows that the proposed model outperforms other competitive models. Given the efficacy of the proposed model, it is applied to predict electricity consumption in the coming years, which could provide with a reference in preparing energy policies and strategies. © 2020 Elsevier Ltd
语种：
英文
展开
