T.L. Paez

25 papers receiving 119 citations

Peers

T.L. Paez
Comparison fields: 5 of 32
  • Statistics, Probability and Uncertainty 61
  • Civil and Structural Engineering 55
  • Automotive Engineering 22
  • Control and Systems Engineering 36
  • Management Science and Operations Research 16
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Countries citing papers authored by T.L. Paez

Since Specialization
Citations

This map shows the geographic impact of T.L. Paez'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 T.L. Paez with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites T.L. Paez more than expected).

Fields of papers citing papers by T.L. Paez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by T.L. Paez. 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 T.L. Paez. The network helps show where T.L. Paez may publish in the future.

Co-authors

The 14 scholars most cited alongside T.L. Paez, 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 T.L. Paez Line = papers co-authored together T.L. Paez links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200839
2 200219
3
Statistical analysis of modal parameters using the bootstrap
199610
4 200210
5
Application of the bootstrap to the analysis of vibration test data
19959
6 19985
7 20025
8 20024
9
Analysis of wind turbines on offshore support structures excited by random wind and random waves
19883
10 19993
11 20023
12
Simulation of nonlinear random vibrations using artificial neural networks
19973
13 19972
14
Uncertainty evaluation in dynamic system response
19982
15
Random control at n/sup 2/ points using n shakers
19872
16
Statistical validation of physical system models
19962
17 20022
18
Statistical tests of system linearity based on the method of surrogate data
19991
19
Simulation of large systems with neural networks
19941
20
Conservatism in least favorable response analysis and testing
19801

About T.L. Paez

T.L. Paez is a scholar working on Civil and Structural Engineering, Statistics, Probability and Uncertainty, Control and Systems Engineering, Artificial Intelligence and Statistical and Nonlinear Physics, having authored 29 papers that have together received 133 indexed citations. Recurring topics across this work include Structural Health Monitoring Techniques (12 papers), Probabilistic and Robust Engineering Design (10 papers), Control Systems and Identification (5 papers), Neural Networks and Applications (5 papers), Fault Detection and Control Systems (3 papers), Advanced Statistical Methods and Models (2 papers), Diverse Scientific and Engineering Research (2 papers) and Energy Load and Power Forecasting (2 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (61 citations), Civil and Structural Engineering (55 citations), Automotive Engineering (22 citations), Control and Systems Engineering (36 citations) and Management Science and Operations Research (16 citations). T.L. Paez has collaborated with scholars based in United States. Frequent co-authors include John Red-Horse, Norman Hunter, Rudolph G. Jungst, David Ingersoll, Suleiman K. Kassicieh, Gautam Vora, Angel Urbina, D.O. Smallwood, Søren M. Bentzen and Richard Field. Their work appears in journals such as SAE technical papers on CD-ROM/SAE technical paper series, Computer Methods in Applied Mechanics and Engineering, Mechanical Systems and Signal Processing, Experimental Techniques and STIN.

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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