An overview of the fuzzy data envelopment analysis research and its successful applications

W Zhou, Z Xu - International journal of fuzzy systems, 2020 - Springer
Data envelopment analysis (DEA) is a prominent technique to make decisions and improve
alternatives based on non-parameter modeling and ratio calculation. However, an obvious …

Factors influencing maintenance labor productivity in the electricity industry

M Alzeraif, A Cheaitou - … Journal of System Assurance Engineering and …, 2024 - Springer
This paper aims at identifying and examining the most influential factors affecting the
productivity of maintenance labor, with a focus on the electricity industry of the United Arab …

The interaction between non-technical and technical risks in upstream natural gas project schedule overruns: Evidence from Australia

M Basak, V Coffey, RK Perrons - The Extractive Industries and Society, 2021 - Elsevier
Upstream natural gas projects are extremely complex and encounter a range of non-
technical risks (NTRs) and technical risks (TRs) that frequently get in the way of timely …

[PDF][PDF] Predicting Maintenance Labor Productivity in Electricity Industry using Machine Learning: A Case Study and Evaluation

M Alzeraif, A Cheaitou, AB Nassif - International Journal of Advanced …, 2023 - academia.edu
Predicting maintenance labor productivity is crucial for effective planning and decision-
making in the electricity industry. This paper aims at predicting maintenance labor …

ANFIS and regression-based ANOVA for attribute and variable prediction: a case of quality characteristics in the cement bags industry

MA El-Sharief, O Salah… - International Journal of …, 2023 - inderscienceonline.com
Efficient models are significant to manufacturing systems for the purpose of prediction and
performance evaluation. Traditionally, regression models have been widely held for this …

Factores incidentes en la productividad del sector agroindustrial en el departamento del Atlántico

SM Urdaneta Cuesta - 2023 - bonga.unisimon.edu.co
En el mundo, en Colombia y en el departamento del Atlántico, la agroindustria ha tomado
un puesto preponderante, debido a que toma lo producido por la tierra y los animales, para …

Prediction of the productivity coefficient of wells using machine learning in the Matlab program

M Sharipov, E Muravyova, F Abdrafikova - AIP Conference …, 2023 - pubs.aip.org
At any field, there is a drop in well production over time. The reason for this can be many
factors, ranging from technical parameters (the distance between the clusters of wells, the …

Formation of a training sample for machine learning

F Abdrafikova, E Muravyova, M Sharipov - AIP Conference …, 2023 - pubs.aip.org
In this paper, the Eastern section of the Chutyrsko-Kiengopskoye field was considered as an
example. It was determined which input variables affect the oil production process. An …

Preparation of data for machine learning in the Matlab program

F Abdrafikova, E Muravyova, M Sharipov - AIP Conference …, 2023 - pubs.aip.org
In this paper, input and output variables that affect the process of oil production and have a
mutual influence were determined. The well productivity coefficient was analyzed. Using the …

Прогнозирование коэффициента продуктивности скважин с боковым стволом (на примере Уньвинского месторождения)

АА Щербаков, ГП Хижняк, ВИ Галкин - Известия Томского …, 2019 - cyberleninka.ru
Актуальность. Многие месторождения Соликамской депрессии Пермского края
характеризуются завершающей стадией разработки и имеют высокий коэффициент …