Pin Lim

8 papers receiving 1.2k citations

Pin Lim's Hit Papers

Multiobjective Deep Belief Networks Ensemble for Remaining Useful Life Estimation in Prognostics 2016 · 702 citations
7020+3+6Years since publication200400600

Peers

Pin Lim
Comparison fields: 5 of 67
  • Medical Laboratory Technology 73
  • Safety, Risk, Reliability and Quality 339
  • Control and Systems Engineering 810
  • Statistics, Probability and Uncertainty 63
  • Artificial Intelligence 272
Replace Mei Yuan with:
Mei Yuan China
Brigitte Chebel‐Morello France
Zheng Zhou China
Carl S. Byington United States
Gang Niu China
Sankalita Saha United States
Shuai Zheng United States
Joo-Ho Choi South Korea
Edward Balaban United States
Pierre Dersin France
Pin Lim relative to Mei Yuan China Mei Yuan's profile →
Citations per field
00.5×1.7×
Mei Yuan · 1×
Citations per year

Countries citing papers authored by Pin Lim

Since Specialization
Citations

This map shows the geographic impact of Pin Lim's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Pin Lim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pin Lim more than expected).

Fields of papers citing papers by Pin Lim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pin Lim. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Pin Lim. The network helps show where Pin Lim may publish in the future.

Co-authors

The 11 scholars most cited alongside Pin Lim, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Pin Lim Line = papers co-authored together Pin Lim links everyone, so they are left out of the graph.

All Works

8 of 8 papers shown

About Pin Lim

Pin Lim is a scholar working on Control and Systems Engineering, Safety, Risk, Reliability and Quality, Artificial Intelligence, Information Systems and Mechanics of Materials, having authored 8 papers that have together received 1.2k indexed citations. Recurring topics across this work include Machine Fault Diagnosis Techniques (6 papers), Fault Detection and Control Systems (5 papers), Reliability and Maintenance Optimization (4 papers), Imbalanced Data Classification Techniques (1 paper), Electricity Theft Detection Techniques (1 paper), Fuzzy Logic and Control Systems (1 paper), Financial Distress and Bankruptcy Prediction (1 paper) and Engineering Diagnostics and Reliability (1 paper). The work is most often cited by research in Medical Laboratory Technology (73 citations), Safety, Risk, Reliability and Quality (339 citations), Control and Systems Engineering (810 citations), Statistics, Probability and Uncertainty (63 citations) and Artificial Intelligence (272 citations). Pin Lim has collaborated with scholars based in Singapore, Hong Kong and China. Frequent co-authors include Kay Chen Tan, Chong Zhang, A. K. Qin, Chi-Keong Goh, Zhao Xu, Feng Yang, Sivakumar Nadarajan, Mohamed Habibullah, P.S. Dutta and Ming Luo. Their work appears in journals such as IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Industrial Electronics, IEEE Transactions on Emerging Topics in Computational Intelligence, IEEE Transactions on Cybernetics and Annual Conference of the PHM Society.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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