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Deep Belief Network Based Hybrid Model for Building Energy Consumption Prediction 期刊论文
ENERGIES, 2018, 卷号: 11, 期号: 1
作者:  Li, Chengdong;  Ding, Zixiang;  Yi, Jianqiang;  Lv, Yisheng;  Zhang, Guiqing
收藏  |  浏览/下载：224/0  |  提交时间：2018/10/10
Building Energy Consumption Prediction  Deep Belief Network  Contrastive Divergence Algorithm  Least Squares Learning  Energy-consuming Pattern  
Analysis and Design of Functionally Weighted Single-Input-Rule-Modules Connected Fuzzy Inference Systems 期刊论文
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2018, 卷号: 26, 期号: 1, 页码: 56-71
作者:  Li, Chengdong;  Gao, Junlong;  Yi, Jianqiang;  Zhang, Guiqing
收藏  |  浏览/下载：176/0  |  提交时间：2018/10/10
Data-driven Method  Fuzzy Inference System (Fis)  Least-squares Method  Parameter Learning  Single-input Rule Module (Sirm)  
A fast learning method for data-driven design of interval type-2 fuzzy logic system 期刊论文
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2017, 卷号: 32, 期号: 3, 页码: 2705-2715
作者:  Li, Chengdong;  Zhang, Guiqing;  Yi, Jianqiang;  Shang, Fang;  Gao, Junlong
收藏  |  浏览/下载：223/0  |  提交时间：2017/05/05
Data-driven Method  Fast Learning  Fuzzy Logic System  Anfis  Type-2 Fuzzy  
Adaptive Inverse Control of Cable-Driven Parallel System Based on Type-2 Fuzzy Logic Systems 期刊论文
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2015, 卷号: 23, 期号: 5, 页码: 1803-1816
作者:  Wang, Tiechao;  Tong, Shaocheng;  Yi, Jianqiang;  Li, Hongyi
浏览  |  Adobe PDF(1877Kb)  |  收藏  |  浏览/下载：364/86  |  提交时间：2015/11/12
Adaptive Inverse Control  Cable-driven Parallel System  Fuzzy Nonlinear Autoregressive Exogenous (Narx) Model  Type-2 Fuzzy Logic Systems  
NEW DRUG R&D OF TRADITIONAL CHINESE MEDICINE: ROLE OF DATA MINING APPROACHES 期刊论文
JOURNAL OF BIOLOGICAL SYSTEMS, 2009, 卷号: 17, 期号: 3, 页码: 329-347
作者:  Yang, Hongjun;  Chen, Jianxin;  Tang, Shihuan;  Li, Zhenkun;  Zhen, Yisong;  Huang, Luqi;  Yi, Jianqiang
浏览  |  Adobe PDF(293Kb)  |  收藏  |  浏览/下载：427/90  |  提交时间：2015/11/08
Drug Discovery  Traditional Chinese Medicine  Data Mining  Unsupervised Cluster  Supervised Regression  Formulae  Association  Mutual Information  
ENCODING PRIOR KNOWLEDGE INTO DATA DRIVEN DESIGN OF INTERVAL TYPE-2 FUZZY LOGIC SYSTEMS 期刊论文
INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL, 2011, 卷号: 7, 期号: 3, 页码: 1133-1144
作者:  Li, Chengdong;  Yi, Jianqiang;  Wang, Tiechao
浏览  |  Adobe PDF(228Kb)  |  收藏  |  浏览/下载：206/74  |  提交时间：2015/11/08
Information Fusion  Type-2 Fuzzy  Least Squares Algorithm  Prior Knowledge  
An effective solution to discover synergistic drugs for anti-cerebral ischemia from traditional Chinese medicinal formulae 期刊论文
ACTA PHARMACOLOGICA SINICA, 2013, 卷号: 34, 期号: 11, 页码: 116-117
作者:  Wu, Chuan-hong;  Chen, Jian-xin;  Lu, Pang;  Chen, Chang;  Li, Shao-jing
收藏  |  浏览/下载：241/0  |  提交时间：2015/09/23
On the Monotonicity of Interval Type-2 Fuzzy Logic Systems 期刊论文
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2014, 卷号: 22, 期号: 5, 页码: 1197-1212
作者:  Li, Chengdong;  Yi, Jianqiang;  Zhang, Guiqing
浏览  |  Adobe PDF(1881Kb)  |  收藏  |  浏览/下载：281/71  |  提交时间：2015/09/18
Data-driven Method  Fuzzy Logic System  Modeling And Control  Monotonicity  Type-2 Fuzzy  Type-reduction And Defuzzification Method  
Efficacy of a Chinese herbal formula in patients with stable angina pectoris based on doctor and patient reported outcomes 期刊论文
AFRICAN JOURNAL OF PHARMACY AND PHARMACOLOGY, 2012, 卷号: 6, 期号: 24, 页码: 1799-1804
作者:  Li, Xiao-ke;  Jing, Lu;  Lu, Peng;  He, Qing-yong;  Xiong, Xing-jiang;  Yao, Kui-wu;  Guo, Li-li;  Wang, Jie;  Chen, Jian-xin
收藏  |  浏览/下载：189/0  |  提交时间：2015/09/18
Blood Mansion Stasis-expelling Decoction  Patient Reported Outcomes  Doctor Reported Outcomes  Stable Angina Pectoris  Seattle Angina Questionnaire (Saq)  Traditional Chinese Medicine  Double-blind Randomized Controlled Trial  
Data-driven modeling and optimization of thermal comfort and energy consumption using type-2 fuzzy method 期刊论文
SOFT COMPUTING, 2013, 卷号: 17, 期号: 11, 页码: 2075-2088
作者:  Li, Chengdong;  Zhang, Guiqing;  Wang, Ming;  Yi, Jianqiang
浏览  |  Adobe PDF(1108Kb)  |  收藏  |  浏览/下载：313/87  |  提交时间：2015/08/12
Type-2 Fuzzy  Data-driven Method  Thermal Comfort  Multiobjective Optimization  Energy Saving