毛树华-亚博888

一、个人基本情况

姓名:毛树华

性别:男

学位:博士

所在系:统计学系

职称:教授

电子邮件:maosh_415@163.com

联系电话:18971654781

二、教育背景与工作经历

2002~2004  武汉理工大学理学院应用数学专业，获理学硕士学位

2008~2011  武汉理工大学理学院力学系， 获工学博士学位

2009~2010  美国宾夕法尼亚州立大学统计学系，国家青年骨干教师公派访问学者

2016~2017  加拿大university of manitoba统计学系，国家公派全额资助出国留学访问学者

2011-2016武汉理工大学船舶与海洋工程博士后流动站博士后(出站)

三、研究方向

大数据技术与数据挖掘、智能优化、深度学习、统计预测与决策等

四、教学研究

教学上共主讲各类数学与统计课程12门，其中硕士生及博士生6门，指导硕士研究生25名(含在读)。

五、科学研究

科研上主持和参加各类科研项目13项，其中国家自然科学基金5项(其中主持1项，参与4项)，省部级项目8项(其中主持5项);出版著作和教材4部，其中专著2部，发表学术论文50余篇，论文被国外著名检索系统检索50余篇。

主持及参与的主要科研项目:

[1] 教育部人文社会科学基金项目，21yjazh060, 基于多源异构数据的抑郁障碍人群自杀风险预警模型研究, 2022-01 至 2024-12, 10万元, 在研, 主持。

[2] 国家自然科学基金面上项目，51479151，通航环境耦合作用的船舶动力系统能效提升灰色建模研究，2015/01-2018/12,80万元，结题，主持。

[3] 国家自然科学基金面上项目，智慧城市动态交通流演化与行程时间短时模拟的灰信息覆盖建模研究，2016.1-2016.12，参与,结题。

[4] 中国博士后科学基金特别资助项目，2013t60755,基于灰非线性优化理论的船舶动力系统能效提升建模研究，2013/01-2015/12,15万元，结题，主持。

[5] 中国博士后科学基金面上项目，2012m521487,大型船舶推进系统可靠性分析的区间型灰色模型研究，2012/081-2014/12,5万元，结题，主持。

[6] 教育部人文社会科学基金项目，11yjc630155,基于灰理论的城市交通拥堵评价与疏导研究，2012/01-2014/12, 7万元，结题，主持。

[7] 国家自然科学基金青年基金项目，51809202，复杂环境与载况耦合作用下的混合动力船舶能效预测控制方法研究，2019/01-2021/12，25万元，结题，参与。

六、代表性论文及著作

[1]yin chen, mao shuhua. fractional multivariate grey bernoulli model combined with improved grey wolf algorithm: application in short-term power load forecasting. energy, 2023,369:126844.

[2]kang yuxiao, mao shuhua, zhang yonghong. fractional time-varying grey traffic flow model based on viscoelastic fluid and its application [j]. transportation research part b: methodol, 2022,157:149-174.

[3]he jing, mao s, ng a k y. neural computing for grey richards differential equation to forecast traffic parameters with various time granularity[j]. neurocomputing, 2023: 126394.

[4]zhang ruyue,mao shuhua, kang yuxiao. a novel traffic flow prediction model: variable order fractional grey model based on an improved grey evolution algorithm. expert system with application,2023,224: 119943.

[5]he jing, mao shuhua, kang yuxiao. augmented fractional accumulation grey model and its application: class ratio and restore error perspectives[j]. mathematics and computers in simulation, 2023, 209: 220-247.

[6]lei wen, mao shuhua, zhang yonghong. estimating china’s co2 emissions under the influence of covid19 epidemic using a novel fractional multivariate nonlinear grey model[j]. environment, development and sustainability, 2023: 1-32.

[7]kang yuxiao, mao shuhua , zhang yonghng. variable order fractional grey model and its application [j]. applied mathematical modelling, 2021, 97: 619-635

[8]mao shuhua, zhu ming, wang xianpeng , xiao xinping. grey–lotka–volterra model for the competition and cooperation between third-party online payment systems and online banking in china [j]. applied soft computing, 2020, 95: 106501.

[9]mao shuhua, kang yuxiao, zhang yonghong, xiao xinping, zhu huiming. fractional grey model based on non-singular exponential kernel and its application in the prediction of electronic waste precious metal content [j]. isa transactions, 2020, 107: 12-26.

[10] zhang yonghong, mao shuhua, kang yuxiao, wen jianghui. fractal derivative fractional grey riccati model and its application [j]. chaos, solitons and fractals, 2021, 145(2): 110778

[11] mao shuhu, gao mingyun, xiao xinping, zhu ming. a novel fractional grey system model and its application [j]. applied mathematical modelling, 2016,40(7–8): 5063-5076.

[12] mao shuhua, zhang yonghong, kang yuxiao, mao yuannong. coopetition analysis in industry upgrade and urban expansion based on fractional derivative gray lotka–volterra model [j]. soft computing, 2021, 25(17): 11485-11507.

[13] xiao xinping , yang jingwei, mao shuhua. an improved seasonal rolling grey forecasting model using a cycle truncation accumulated generating operation for traffic flow [j]. applied mathematical modeling,‏ 2017，(51):386-404

[14]  xiao xinping, guo huan, mao shuhua. the modeling mechanism，extension and optimization of grey gm(1,1) model [j]. applied mathematical modeling，2014，38(5-6):1896-1910

[15] kang yuxiao, mao shuhua, zhang yonghong, zhu huiming. fractional derivative multivariable grey model for nonstationary sequence and its application [j]. journal of systems engineering and electronics, 2020, 31(5):1009-1018.

[16] zhang yonghong, mao shuhua, kang yuxiao. a clean energy forecasting model based on artificial intelligence and fractional derivative grey bernoulli models [j]. grey systems: theory and application, 2020.

[17] mao shuhua, xiao xinping, gao mingyun, et al. nonlinear fractional order grey model of urban traffic flow short-term prediction [j]. journal of grey system, 2018, 30(4).1-17

[18]  mao s h, he q, xiao x p, et al. study of the correlation between oil price and exchange rate under the new state of the economy [j]. scientia iranica, 2019, 26(4): 2472-2483.

[19] mao s h, zhu m, yan x p, gao m y. modeling mechanism of a novel fractional grey model based on matrix analysis [j]. journal of systems engineering and electronics, 2016,27(5): 1040-1053

[20]  mao s h, wang x p, zhu m. a new coupled arma-fgm model and its application in the internet third-party payment forecasting in china [j]. grey systems: theory and application, 2018.8(2):181~198.

[21] 毛树华，高明运，肖新平.分数阶累加时滞gm(1,n,τ)模型及其应用[j].系统工程理论与实践,2015,35(2): 430-436

[22] 毛树华,王先朋,文江辉,吴超仲，肖新平.基于自回归条件持续期模型的疲劳驾驶研究, 交通运输系统工程与信息, 2018, 18(3): 81~87

[23] 肖新平，毛树华. 灰预测与决策方法.北京:科学出版社， 2013.03

[24] 毛树华，高明运，肖新平.分数阶灰色模型理论与应用.北京:科学出版社，2022.10

[25] 唐湘晋，毛树华，陈家清.应用数理统计.武汉:武汉理工大学出版社，2013