D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Engineering and Technology D-index 35 Citations 5,128 130 World Ranking 3397 National Ranking 351

Overview

What is he best known for?

The fields of study he is best known for:

  • Statistics
  • Artificial intelligence
  • Electrical engineering

Yang Zhao mainly investigates Artificial intelligence, Fault detection and isolation, Efficient energy use, Building energy and Unsupervised learning. His study in Artificial intelligence is interdisciplinary in nature, drawing from both Machine learning and Data mining, Big data. His Big data research integrates issues from Cooling load, Building science, Feature extraction, Data analysis and Flexibility.

Yang Zhao interconnects Support vector machine and Feature vector in the investigation of issues within Fault detection and isolation. His Efficient energy use study combines topics in areas such as Control, Indoor air quality and Architectural engineering. Yang Zhao usually deals with Building energy and limits it to topics linked to Renewable energy system and Zero-energy building.

His most cited work include:

  • A short-term building cooling load prediction method using deep learning algorithms (242 citations)
  • Occupancy measurement in commercial office buildings for demand-driven control applications : a survey and detection system evaluation (176 citations)
  • Pattern recognition-based chillers fault detection method using Support Vector Data Description (SVDD) (122 citations)

What are the main themes of his work throughout his whole career to date?

Yang Zhao mostly deals with Artificial intelligence, Fault detection and isolation, Data mining, Machine learning and Support vector machine. His work in the fields of Deep learning, Data-driven and Robustness overlaps with other areas such as Image quality. His Deep learning research incorporates elements of Cooling load and Flexibility.

His Fault detection and isolation study is concerned with Fault in general. His work carried out in the field of Data mining brings together such families of science as Building energy and Cluster analysis. The various areas that Yang Zhao examines in his Support vector machine study include Stepwise regression, Moving average and Linear regression.

He most often published in these fields:

  • Artificial intelligence (19.30%)
  • Fault detection and isolation (16.67%)
  • Data mining (14.04%)

What were the highlights of his more recent work (between 2019-2021)?

  • Thermal energy storage (7.02%)
  • Data mining (14.04%)
  • Artificial intelligence (19.30%)

In recent papers he was focusing on the following fields of study:

Yang Zhao spends much of his time researching Thermal energy storage, Data mining, Artificial intelligence, Building energy and Heat transfer. The Thermal energy storage study combines topics in areas such as Phase-change material, Air source heat pumps, Heat pipe, Efficient energy use and Process engineering. His biological study spans a wide range of topics, including Cluster analysis and Water chiller.

The study incorporates disciplines such as Machine learning and Autoregressive model in addition to Artificial intelligence. His Machine learning study combines topics from a wide range of disciplines, such as Fault and Experimental data. His studies deal with areas such as Decision tree, Association rule learning and Raw data as well as Building energy.

Between 2019 and 2021, his most popular works were:

  • A review of data mining technologies in building energy systems: Load prediction, pattern identification, fault detection and diagnosis (36 citations)
  • Numerical study on heat transfer enhancement of PCM using three combined methods based on heat pipe (12 citations)
  • Performance evaluation and analysis of a vertical heat pipe latent thermal energy storage system with fins-copper foam combination (12 citations)

In his most recent research, the most cited papers focused on:

  • Statistics
  • Artificial intelligence
  • Electrical engineering

His scientific interests lie mostly in Thermal energy storage, Building energy, Data mining, Phase-change material and Air source heat pumps. His Thermal energy storage study incorporates themes from Natural convection, Thermal conductivity, Electric heating and Heat pipe. His Building energy study typically links adjacent topics like Association rule learning.

His Data mining research is multidisciplinary, incorporating perspectives in Fault detection and isolation and Pattern identification. His Phase-change material research incorporates themes from Nuclear engineering, Steady state, Fin and Thermal energy. His Air source heat pumps study integrates concerns from other disciplines, such as Mathematical model, Boiler and Process engineering.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Atomically Thin Mesoporous Nanomesh of Graphitic C3N4 for High-Efficiency Photocatalytic Hydrogen Evolution

Qing Han;Bing Wang;Jian Gao;Zhihua Cheng.
ACS Nano (2016)

530 Citations

Vertically Aligned Graphene Sheets Membrane for Highly Efficient Solar Thermal Generation of Clean Water

Panpan Zhang;Jing Li;Lingxiao Lv;Yang Zhao.
ACS Nano (2017)

433 Citations

Occupancy measurement in commercial office buildings for demand-driven control applications : a survey and detection system evaluation

TM Timilehin Labeodan;W Wim Zeiler;G Gert Boxem;Y Yang Zhao.
Energy and Buildings (2015)

302 Citations

A short-term building cooling load prediction method using deep learning algorithms

Cheng Fan;Fu Xiao;Yang Zhao.
Applied Energy (2017)

294 Citations

Graphene-based smart materials

Xiaowen Yu;Huhu Cheng;Miao Zhang;Yang Zhao.
Nature Reviews Materials (2017)

225 Citations

MnO 2 -modified hierarchical graphene fiber electrochemical supercapacitor

Qing Chen;Yuning Meng;Chuangang Hu;Yang Zhao.
Journal of Power Sources (2014)

209 Citations

Pattern recognition-based chillers fault detection method using Support Vector Data Description (SVDD)

Yang Zhao;Shengwei Wang;Fu Xiao.
Applied Energy (2013)

156 Citations

An intelligent chiller fault detection and diagnosis methodology using Bayesian belief network

Yang Zhao;Fu Xiao;Shengwei Wang.
Energy and Buildings (2013)

153 Citations

Metal–Organic Frameworks Constructed from a New Thiophene-Functionalized Dicarboxylate: Luminescence Sensing and Pesticide Removal

Yang Zhao;Xiaoyue Xu;Ling Qiu;Xiaojing Kang.
ACS Applied Materials & Interfaces (2017)

149 Citations

Graphene Platforms for Smart Energy Generation and Storage

Minghui Ye;Zhipan Zhang;Yang Zhao;Liangti Qu;Liangti Qu.
Joule (2017)

147 Citations

If you think any of the details on this page are incorrect, let us know.

Contact us

Best Scientists Citing Yang Zhao

Liangti Qu

Liangti Qu

Tsinghua University

Publications: 112

Huhu Cheng

Huhu Cheng

Tsinghua University

Publications: 27

An Li

An Li

Lanzhou University of Technology

Publications: 20

Ghim Wei Ho

Ghim Wei Ho

National University of Singapore

Publications: 18

Lan Jiang

Lan Jiang

Beijing Institute of Technology

Publications: 17

Zhong-Shuai Wu

Zhong-Shuai Wu

Dalian Institute of Chemical Physics

Publications: 17

Nan Chen

Nan Chen

Beijing Institute of Technology

Publications: 17

Shengwei Wang

Shengwei Wang

Hong Kong Polytechnic University

Publications: 17

Hong-Bo Sun

Hong-Bo Sun

Tsinghua University

Publications: 16

Chun Li

Chun Li

Tsinghua University

Publications: 15

Nadeem Javaid

Nadeem Javaid

COMSATS University Islamabad

Publications: 15

Meifang Zhu

Meifang Zhu

Donghua University

Publications: 14

Hong Liu

Hong Liu

Shandong University

Publications: 14

Hui Xu

Hui Xu

Zhejiang Sci-Tech University

Publications: 14

Xianbao Wang

Xianbao Wang

Hubei University

Publications: 14

Fu Xiao

Fu Xiao

Hong Kong Polytechnic University

Publications: 14

Something went wrong. Please try again later.