蔡振闹

姓名:蔡振闹
性别:男
职称:高级工程师
职务:温州大学校友与发展联络办公室副主任
最后学历、学位:博研,工学博士学位
工作单位:温州大学校友与发展联络办公室、温州大学计算机与人工智能学院
学术兼职:温州市计算机学会理事、中国计算机学会会员、中国人工智能学会会员、
温州市网络安全应急处置专家小组成员
通讯地址:浙江省温州市茶山高教园区温州大学计算机与人工智能学院 5 号楼
联系电话:0577- 86598951
Emailerikcai@qq.com
实验室主页:https://mdm.wzu.edu.cn
欢迎踏实勤奋的同学报考温州大学计算机科学与技术学术硕士或电子信息专业硕士!
二、主要研究方向及研究团队
专业领域:计算机科学与技术、人工智能、教育数字化
主要研究方向:数据挖掘、机器学习方法及应用、进化计算
主要研究团队:陈慧灵教授课题组成员、温州市智能影像处理与分析重点实验室团队
成员、温州大学智能信息系统研究所成员
三、主要教育及工作经历
2003 6 月,浙江师范大学计算机科学与技术专业本科毕业,获工学学士学位
2003 7 月至 2022 6 , 温州大学现代教育技术中心参加工作,任助理工程师、
工程师、高级工程师
2022 7 月至今,温州大学校友与发展联络办公室副主任
期中,2021 7 月至今,温州大学计算机与人工智能学院硕士生导师
2008 9 月,华中科技大学软件工程硕士在职毕业,获工程硕士学位
2021 3 月,西北工业大学计算机学科与技术专业博士研究生毕业,获工学博士学位
四、近年来主持或主要参与的科研项目
1、浙江省自然科学基金探索公益项目,基于群体进化计算的光伏系统智能监控方法
研究(LTGS23E070001),2023/01-2025/12,在研,主持
2、浙江省自然科学基金一般项目,多源模态医学数据挖掘及其在阿尔茨海默病诊断
中的应用(LY14F020035),2014/1-2017/12,已结题,主持3. 国家自然基金面上项目,大数据驱动的肺部感染性疾病预测模型的构建与应用
62076185),2021/01-2024/12,在研,参与
4. 浙江省自然科学基金重大项目,基于多中心多模态的阿尔茨海默病早期诊断方法研
究(LD21F020001),2021/01-2023/12,在研,参与
5、国家自然科学基金青年科学基金项目,服务生态网络中服务协同的可信性机制与关
键技术研究服务网络中服务的可信机制与算法研究(61402337),2015/01-2017/12,结题,
参与
6、浙江省自然科学基金一般项目,基于大规模医学数据的智能疾病诊断方法研究
Y17F020061),2017/01-2019/12,结题,参与
7、温州市科技重大项目,大数据驱动的肺部感染性疾病预测预警关键技术研究
ZG2017019),2017/07-2019/12, 已结题,参与
五、主要科研成果
主要论文
[1] Chen J, Cai Z, Heidari A A, Chen H, He Q, Gutierrez J E, Mansour R F. Multi-threshold
image segmentation based on an improved differential evolution: Case study of thyroid papillary
carcinoma. Biomedical Signal Processing and Control, 2023.
[2] Zhang M, Chen H, Heidari A A, Cai Z, Aljehane N O, Mansour R F. OCRUN: An
oppositional RungeKutta optimizer with cuckoo search for global optimization and feature
selection. Applied Soft Computing, 2023.
[3] Chen Z, Kuang F, Yu S, Cai Z, Chen H. Static photovoltaic modelsparameter
extraction using reinforcement learning strategy adapted local gradient Nelder-Mead Runge
Kutta method. Applied Intelligence, 2023.
[4] Chen J, Cai Z, Chen H, Chen X, Gutierrez J E, Mansour R F, Ragab M. Renal Pathology
Images Segmentation Based on Improved Cuckoo Search with Diffusion Mechanism and
Adaptive Beta-Hill Climbing. Journal of Bionic Engineering, 2023.
[5] Xu B, Heidari A A, Cai Z, Chen H. Dimensional decision covariance colony predation
algorithm: global optimization and high−dimensional feature selection. Artificial Intelligence
Review, 2023.
[6] Xu, B.Y., Heidari, A.A., Kuang, F.J., Zhang, S.Y., Chen, H.L., and Cai, Z.N. *:
‘Performance optimization of photovoltaic systems: Reassessment of political optimization with
a quantum Nelder-mead functionality’, Solar Energy, 2022, 234, pp. 39-63
[7] Xu, B.Y., Heidari, A.A., Kuang, F.J., Zhang, S.Y., Chen, H.L., and Cai, Z.N.*: ‘Quantum
Nelder-Mead Hunger Games Search for optimizing photovoltaic solar cells’, International
Journal of Energy Research, 2022, 46, (9), pp. 12417-12466
[8] Xia J, Cai Z, Heidari A A, Ye Y, Chen H, Pan Z. Enhanced Moth-Flame Optimizer with Quasi-Reflection and Refraction Learning with Application to Image Segmentation and Medical
Diagnosis. Current Bioinformatics, 2022.
[9] Chen H, Li C, Mafarja M, Heidari A A, Chen Y, Cai Z. Slime mould algorithm: a
comprehensive review of recent variants and applications. International Journal of Systems
Science, 2022.
[10] Yang X, Wang R, Zhao D, Yu F, Huang C, Heidari A A, Cai Z, Bourouis S, Algarni A D,
Chen H. An Adaptive Quadratic Interpolation and Rounding Mechanism Sine Cosine Algorithm
with Application to Constrained Engineering Optimization Problems. Expert Systems with
Applications, 2022, 213: 119041.
[11] Yu S, Heidari A A, He C, Cai Z, Althobaiti M M, Mansour R F, Liang G, Chen H.
Parameter estimation of static solar photovoltaic models using Laplacian Nelder-Mead hunger
games search. Solar Energy, 2022, 242: 79-104.
[12] Liu Y, Heidari A A, Cai Z, Liang G, Chen H, Pan Z, Alsufyani A, Bourouis S.
Simulated annealing-based dynamic step shuffled frog leaping algorithm: Optimal performance
design and feature selection. Neurocomputing, 2022, 503: 325-362.
[13] Hu J, Gui W, Heidari A A, Cai Z, Liang G, Chen H, Pan Z. Dispersed foraging slime
mould algorithm: Continuous and binary variants for global optimization and wrapper-based
feature selection. Knowledge-Based Systems, 2021, 237: 107761.
[14] Wu S, Mao P, Li R, Cai Z, Heidari A A, Xia J, Chen H, Mafarja M, Turabieh H, Chen
X. Evolving Fuzzy k-Nearest Neighbors Using an Enhanced Sine Cosine Algorithm: Case Study
of Lupus Nephritis. Computers in Biology and Medicine, 2021, 135: 104582.
[15] Liu Y, Chong G, Heidari A A, Chen H, Liang G, Ye X, Cai Z, Wang M. Horizontal and
vertical crossover of Harris hawk optimizer with Nelder-Mead simplex for parameter estimation
of photovoltaic models. Energy Conversion and Management, 2020, 223: 113211.
[16] LIANG X, CAI Z N, WANG M J, et al. Chaotic oppositional sine-cosine method for
solving global optimization problems [J]. Engineering with Computers, 2020, 17.
[17] Zhang H, Li R, Cai Z, Gu Z, Asghar Heidari A, Wang M, Chen H, Chen M. Advanced
Orthogonal Moth Flame Optimization with BroydenFletcherGoldfarbShanno Algorithm:
Framework and Real-world Problems. Expert Systems with Applications, 2020, 159: 113617.
[18] Wang M, Heidari A A, Chen M, Chen H, Zhao X, Cai X. Exploratory Differential Ant
Lion-based Optimization. Expert Systems with Applications, 2020, 159: 113548.
[19] Xu Z, Hu Z, Heidari A A, Wang M, Zhao X, Chen H, Cai X. Orthogonally-designed
adapted grasshopper optimization: A comprehensive analysis. Expert Systems with Applications,
2020, 150: 113282.
[20] Zhennao Cai, Jianhua Gu, Jie Luo, Qian Zhang, Huiling Chen, Zhifang Pan, Yuping Li,
Chengye Li. Evolving an optimal kernel extreme learning machine by using an enhanced grey wolf optimization strategy. Expert Systems with Applications, 2019, 138: 112814.
[21] Zhennao Cai, Jianhua Gu, Caiyun Wen, Dong Zhao, Chunyu Huang, Hui Huang ,
Changfei Tong, Jun Li, Huiling Chen. An Intelligent Parkinson’s Disease Diagnostic System
Based on a Chaotic Bacterial Foraging Optimization Enhanced Fuzzy KNN Approach.
Computational and Mathematical Methods in Medicine, 2018: 1-24.
[22] Zhennao Cai, Jianhua Gu, Huiling Chen. A New Hybrid Intelligent Framework for
Predicting Parkinson’s Disease. IEEE Access, 2017, 5: 17188-17200.
[23] WANG M J, CHEN H L, LI H Z, et al. Grey wolf optimization evolving kernel
extreme learning machine: Application to bankruptcy prediction [J]. Engineering Applications of
Artificial Intelligence, 2017, 63(54-68.
[24] Hui-Ling Chen, Gang Wang, Chao Ma, Zhen-Nao Cai, Wen-Bin Liu, Su-Jing Wang.
An efficient hybrid kernel extreme learning machine approach for early diagnosis of Parkinson׳s
disease. Neurocomputing, 2016, 184: 131-144.
专利与软著
[1] 陈慧灵、罗杰、赵学华、蔡振闹等,一种基于改进灰狼优化算法的数据分类预测
方法及系统,2018-12-28,中国,授权专利号:ZL201711048597.7
[2] 黄兴利、蔡振闹、白延虎,一种可移动式大数据智能终端,2022-09-16,中国,授
权专利号:ZL202110693853.8
[3] 陈慧灵、彭乐民、何才透、蔡振闹, 基于信息共享搜索策略和 NM 单纯型的鲸鱼优
化光伏模型参数方法,2023-01-17,公开号:CN115618721A
[4] 陈慧灵、杨陈君、蔡振闹,一种基于改进灰鲸优化算法来构建预测模型的方法,
2019-07-30,公开号:CN110069817A
[5] 基于血液样本的胸腔积液智能诊断系统 V1.0,软著,登记号:2018SR227743
杨陈君、陈慧灵、李成业、蔡振闹
[6] 基于机器学习的信用风险评估系统 V1.0,软著,登记号:2017SR619787,陈慧灵,
朱彬磊,蔡振闹
获奖及荣誉
2023 年温州大学办学 90 周年校庆工作先进个人
2022 年浙江省数字化改革“最佳应用”——温州大学“人才第一要事”数字化应用
(作为骨干成员参与数字化应用开发)
2021 年度“温州大学校长特别奖”团队——数字化改革工作推进团队
2021 年温州大学申博工作先进个人
2018 年度温州大学优秀(教育)工作者;
2017 年度“温州大学校长特别奖”团队——智慧校园建设团队

 

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