Ronay Ak
TittelSitert avÅr
Two machine learning approaches for short-term wind speed time-series prediction
R Ak, O Fink, E Zio
IEEE transactions on neural networks and learning systems 27 (8), 1734-1747, 2015
652015
NSGA-II-trained neural network approach to the estimation of prediction intervals of scale deposition rate in oil & gas equipment
R Ak, Y Li, V Vitelli, E Zio, ELP Droguett, CMC Jacinto
Expert Systems with Applications 40 (4), 1205-1212, 2013
592013
An interval-valued neural network approach for uncertainty quantification in short-term wind speed prediction
R Ak, V Vitelli, E Zio
IEEE transactions on neural networks and learning systems 26 (11), 2787-2800, 2015
432015
A survey of the advancing use and development of machine learning in smart manufacturing
M Sharp, R Ak, T Hedberg Jr
Journal of manufacturing systems 48, 170-179, 2018
262018
Automatic localization of casting defects with convolutional neural networks
M Ferguson, R Ak, YTT Lee, KH Law
2017 IEEE international conference on big data (big data), 1726-1735, 2017
252017
Adequacy assessment of a wind-integrated system using neural network-based interval predictions of wind power generation and load
R Ak, YF Li, V Vitelli, E Zio
International Journal of Electrical Power & Energy Systems 95, 213-226, 2018
192018
Analysis and optimization based on reusable knowledge base of process performance models
A Brodsky, G Shao, M Krishnamoorthy, A Narayanan, D Menascé, R Ak
The International Journal of Advanced Manufacturing Technology 88 (1-4), 337-357, 2017
162017
A neural network meta-model and its application for manufacturing
D Lechevalier, S Hudak, R Ak, YT Lee, S Foufou
2015 IEEE International Conference on Big Data (Big Data), 1428-1435, 2015
152015
A proposed risk model and a GIS framework for hazardous materials transportation
R Ak, B Bozkaya
2008 IEEE International Engineering Management Conference, 1-5, 2008
152008
A genetic algorithm and neural network technique for predicting wind power under uncertainty
R Aka, YF Lia, V Vitellia, E Zio
Chemical Engineering 33, 1-6, 2013
142013
Multi-objective genetic algorithm optimization of a neural network for estimating wind speed prediction intervals
R Ak, YF Li, V Vitelli, E Zio
132013
Detection and segmentation of manufacturing defects with convolutional neural networks and transfer learning
MK Ferguson, AK Ronay, YTT Lee, KH Law
Smart and sustainable manufacturing systems 2, 2018
112018
Analysis and optimization in smart manufacturing based on a reusable knowledge base for process performance models
A Brodsky, G Shao, M Krishnamoorthy, A Narayanan, D Menascé, R Ak
2015 IEEE International Conference on Big Data (Big Data), 1418-1427, 2015
92015
Performance measurement of insurance companies by using balanced scorecard and anp
R Ak, B Öztayşi
10th International Symposium on the Analytic Hierarchy Process, 2009
92009
Gaussian Process Regression (GPR) Representation in Predictive Model Markup Language (PMML)
J Park, D Lechevalier, R Ak, KH Ferguson, Max, Law, YT Lee, ...
ASTM International's journal, Smart and Sustainable Manufacturing Systems 1 …, 2017
72017
Data analytics and uncertainty quantification for energy prediction in manufacturing
R Ak, R Bhinge
2015 IEEE International Conference on Big Data (Big Data), 2782-2784, 2015
62015
Ensemble Neural Network Model for Predicting the Energy Consumption of a Milling Machine
R Ak, MM Helu, S Rachuri
ASME 20th Design for Manufacturing and the Life Cycle Conference (DFMLC), 2015
62015
Development of a justification tool for advanced technologies: An example for RFID
E Bozdag, R Ak, T Koc
2007 1st Annual RFID Eurasia, 1-4, 2007
52007
Summary of the symposium on data analytics for advanced manufacturing
AN Narayanan, R Ak, YTT Lee, R Ghosh, S Rachuri
Advanced Manufacturing Series (NIST AMS)-100-7, 2017
42017
A survey on knowledge transfer for manufacturing data analytics
SH Bang, R Ak, A Narayanan, YT Lee, H Cho
Computers in Industry 104, 116-130, 2019
32019
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Artikler 1–20