What is he best known for?
The fields of study he is best known for:
- Statistics
- Normal distribution
- Artificial intelligence
Min Xie spends much of his time researching Reliability engineering, Reliability, Statistics, Software quality and Artificial intelligence.
His studies deal with areas such as Markov model, Software reliability testing and Degradation as well as Reliability engineering.
His biological study spans a wide range of topics, including Distributed algorithm, Distributed computing and Failure mode and effects analysis.
His work in Statistics covers topics such as Control chart which are related to areas like Statistical process control and Sample size determination.
His Software quality study integrates concerns from other disciplines, such as Fault tolerance, Poisson process and Fault detection and isolation.
His Artificial intelligence research integrates issues from Machine learning and Data mining.
His most cited work include:
- Stochastic Ageing and Dependence for Reliability (373 citations)
- A modified Weibull distribution (319 citations)
- Reliability analysis using an additive Weibull model with bathtub-shaped failure rate function (308 citations)
What are the main themes of his work throughout his whole career to date?
Min Xie mostly deals with Reliability engineering, Statistics, Reliability, Control chart and Weibull distribution.
His Reliability engineering study combines topics from a wide range of disciplines, such as Software quality, Software metric, Software reliability testing, Software construction and Degradation.
Bayesian network is closely connected to Data mining in his research, which is encompassed under the umbrella topic of Software quality.
His work on Statistics is being expanded to include thematically relevant topics such as Algorithm.
Min Xie combines subjects such as Statistical process control and Chart with his study of Control chart.
His Weibull distribution study combines topics in areas such as Failure rate and Applied mathematics.
He most often published in these fields:
- Reliability engineering (33.27%)
- Statistics (21.29%)
- Reliability (20.21%)
What were the highlights of his more recent work (between 2015-2021)?
- Reliability engineering (33.27%)
- Reliability (20.21%)
- Control chart (15.21%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Reliability engineering, Reliability, Control chart, Control theory and Statistics.
The concepts of his Reliability engineering study are interwoven with issues in Weibull distribution and Degradation.
His Reliability research focuses on Quality and how it connects with Process.
His research in Control chart intersects with topics in Nonparametric statistics and Chart.
His work in the fields of Control theory, such as Control theory and Control system, overlaps with other areas such as Scheme.
He studies Statistics, namely Event.
Between 2015 and 2021, his most popular works were:
- A Data-Driven Fault Diagnosis Methodology in Three-Phase Inverters for PMSM Drive Systems (169 citations)
- Bayesian Networks in Fault Diagnosis (168 citations)
- A real-time fault diagnosis methodology of complex systems using object-oriented Bayesian networks (150 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Normal distribution
- Artificial intelligence
Min Xie spends much of his time researching Reliability engineering, Control limits, Control chart, Data mining and Condition-based maintenance.
His Reliability engineering research includes elements of Reliability, Experimental data and Degradation.
Min Xie interconnects Algorithm, Estimation theory, Sample size determination and Nonlinear system in the investigation of issues within Control limits.
In his research, Estimator is intimately related to CUSUM, which falls under the overarching field of Control chart.
His work carried out in the field of Data mining brings together such families of science as Nonparametric statistics, Ensemble learning, Support vector machine, Artificial intelligence and Statistic.
His work is dedicated to discovering how Shewhart individuals control chart, Statistics are connected with X-bar chart and other disciplines.
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