Open Access. Powered by Scholars. Published by Universities.®
Operations Research, Systems Engineering and Industrial Engineering Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Artificial Intelligence and Robotics (3)
- Computer Sciences (3)
- Physical Sciences and Mathematics (3)
- Business (2)
- Computer Engineering (2)
-
- Numerical Analysis and Scientific Computing (2)
- Other Operations Research, Systems Engineering and Industrial Engineering (2)
- Risk Analysis (2)
- Systems Science (2)
- Aerospace Engineering (1)
- Business Administration, Management, and Operations (1)
- Energy Policy (1)
- Information Security (1)
- Medicine and Health Sciences (1)
- Occupational Health and Industrial Hygiene (1)
- Public Affairs, Public Policy and Public Administration (1)
- Public Health (1)
- Social and Behavioral Sciences (1)
- Strategic Management Policy (1)
- Systems Engineering (1)
- Systems Engineering and Multidisciplinary Design Optimization (1)
- Institution
- Publication
- Publication Type
Articles 1 - 5 of 5
Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering
Research On Stick-Slip Vibration Level Estimation Of Near-Bit Based On Optimized Xgboost, Hanwen Tang, Zhang Tao, Yumei Li, Li Lei, Jinghua Zhang, Dongliang Hu
Research On Stick-Slip Vibration Level Estimation Of Near-Bit Based On Optimized Xgboost, Hanwen Tang, Zhang Tao, Yumei Li, Li Lei, Jinghua Zhang, Dongliang Hu
Journal of System Simulation
Abstract: Stick-slip vibration is an important limiting factor affecting drilling speed, safety and cost. The establishment of a reliable stick-slip vibration classification model is very important for oil drilling decision-making. A new method based on Bayesian optimization and eXtreme Gradient Boosting (XGBoost) is proposed to evaluate the severity of stick-slip vibration near the bit. The classification processing of the near-bit stick-slip vibration data is carried out. The main feature vectors of the original data is extracted through time domain and frequency domain analysis. A stick-slip vibration level identification and prediction model based on XGBoost is established, and Bayesian algorithm is …
Prioritizing Facilities Linked To Corporate Strategic Objectives Using A Fuzzy Model, Devin Depalmer, Steven J. Schuldt, Justin D. Delorit
Prioritizing Facilities Linked To Corporate Strategic Objectives Using A Fuzzy Model, Devin Depalmer, Steven J. Schuldt, Justin D. Delorit
Faculty Publications
Excerpt: Limited facilities operating and modernization budgets require organizations to carefully identify, prioritize and authorize projects to ensure allocated resources align with strategic objectives. Traditional facility prioritization methods using risk matrices can be improved to increase granularity in categorization and avoid mathematical error or human cognitive biases. These limitations restrict the utility of prioritizations and if erroneously used to select projects for funding, they can lead to wasted resources. This paper aims to propose a novel facility prioritization methodology that corrects these assessment design and implementation issues.
Cybersecurity Risk Assessment Using Graph Theoretical Anomaly Detection And Machine Learning, Goksel Kucukkaya
Cybersecurity Risk Assessment Using Graph Theoretical Anomaly Detection And Machine Learning, Goksel Kucukkaya
Engineering Management & Systems Engineering Theses & Dissertations
The cyber domain is a great business enabler providing many types of enterprises new opportunities such as scaling up services, obtaining customer insights, identifying end-user profiles, sharing data, and expanding to new communities. However, the cyber domain also comes with its own set of risks. Cybersecurity risk assessment helps enterprises explore these new opportunities and, at the same time, proportionately manage the risks by establishing cyber situational awareness and identifying potential consequences. Anomaly detection is a mechanism to enable situational awareness in the cyber domain. However, anomaly detection also requires one of the most extensive sets of data and features …
Uncertainty Quantitative Analysis In Risk Assessment Of Returning To School In The Post-Covid-19 Era, Haibin Li, Jialiang Wang, Haiyan Li
Uncertainty Quantitative Analysis In Risk Assessment Of Returning To School In The Post-Covid-19 Era, Haibin Li, Jialiang Wang, Haiyan Li
Journal of System Simulation
Abstract: After the epidemic, taking the spread of the epidemic in returning to school as an example, a quantitative risk assessment study is conducted. Taking the activity trajectory description of the whole process of susceptible individuals from infection to isolation as a clue, an epidemiological model for risk assessment is established. The number of infected persons in the risk indicators of returning to school is quantified based on the quantified model parameters. According to the value characteristics of the parameters, the number of infected persons is taken as a function of discrete random variables. The probability distribution of the infected …
Influence Of The Inherent Safety Principles On Quantitative Risk In Process Industry: Application Of Genetic Algorithm Process Optimization (Gapo), Mehdi Jahangiri, Abolfazl Moghadasi, Mojtaba Kamalinia, Farid Sadeghianjahromi, Sean Banaee
Influence Of The Inherent Safety Principles On Quantitative Risk In Process Industry: Application Of Genetic Algorithm Process Optimization (Gapo), Mehdi Jahangiri, Abolfazl Moghadasi, Mojtaba Kamalinia, Farid Sadeghianjahromi, Sean Banaee
Community & Environmental Health Faculty Publications
Inherent safety (IS) refers to a set of measures that enhance the safety level of processes and equipment, rendering additional equipment and/or add-ons. The early design phase of processes is suited best for implementation of IS strategies as some of such strategies either are impossible to be implemented at the operation phase or substantially increase costs. The purpose of this study is to present a new approach called genetic algorithm process optimization (GAPO), by which processes can be made inherently safer even at the operation phase. This study simulates the IS principle, assessing its impact on quantitative risk and the …