Intelligent cost estimation by machine learning in supply management: A structured literature review
F Bodendorf, P Merkl, J Franke - Computers & Industrial Engineering, 2021 - Elsevier
In the automotive industry, cost estimation of components to be purchased plays an
important role for price negotiations with suppliers and, therefore, for cost control within the …
important role for price negotiations with suppliers and, therefore, for cost control within the …
Fuzzy detection system for rumors through explainable adaptive learning
Nowadays, rumor spreading has gradually evolved into a kind of organized behaviors,
accompanied with strong uncertainty and fuzziness. However, existing fuzzy detection …
accompanied with strong uncertainty and fuzziness. However, existing fuzzy detection …
Long-term load forecasting: models based on MARS, ANN and LR methods
Electric energy plays an irreplaceable role in nearly every person's life on earth; it has
become an important subject in operational research. Day by day, electrical load demand …
become an important subject in operational research. Day by day, electrical load demand …
Short-term probabilistic prediction of significant wave height using bayesian model averaging: Case study of chabahar port, Iran
Accurate predictions of significant wave heights are important for a number of maritime
applications, such as design of coastal and offshore structures. In the present study, an …
applications, such as design of coastal and offshore structures. In the present study, an …
Prediction of transportation energy demand: multivariate adaptive regression splines
MA Sahraei, H Duman, MY Çodur, E Eyduran - Energy, 2021 - Elsevier
Energy usage in the transportation sector has been increasing in Turkey. Good
management of energy is important as well as a reliable prediction of the energy demand in …
management of energy is important as well as a reliable prediction of the energy demand in …
An EEG-based cross-subject interpretable CNN for game player expertise level classification
L Lin, P Li, Q Wang, B Bai, R Cui, Z Yu, D Gao… - Expert Systems with …, 2024 - Elsevier
Electroencephalogram (EEG) signals have been demonstrated to be an effective method for
game player expertise level classification, as it can reflect the activity state of the player's …
game player expertise level classification, as it can reflect the activity state of the player's …
Natural gas consumption forecast with MARS and CMARS models for residential users
Prediction natural gas consumption is indispensable for efficient system operation and
required for planning decisions at natural gas Local Distribution Companies (LDCs) …
required for planning decisions at natural gas Local Distribution Companies (LDCs) …
The use of machine learning techniques for assessing the potential of organizational resilience
T Ewertowski, BÇ Güldoğuş, S Kuter, S Akyüz… - … European Journal of …, 2024 - Springer
Organizational resilience (OR) increases when the company has the ability to anticipate,
plan, make decisions, and react quickly to changes and disruptions. Thus the company …
plan, make decisions, and react quickly to changes and disruptions. Thus the company …
Retrieval of fractional snow covered area from MODIS data by multivariate adaptive regression splines
In this paper, a novel approach to estimate fractional snow cover (FSC) from MODIS data in
a complex and heterogeneous Alpine terrain is represented by using a state-of-the-art …
a complex and heterogeneous Alpine terrain is represented by using a state-of-the-art …
RCMARS: Robustification of CMARS with different scenarios under polyhedral uncertainty set
Our recently developed CMARS is powerful in handling complex and heterogeneous data.
We include into CMARS the existence of uncertainty about the scenarios. Indeed, data …
We include into CMARS the existence of uncertainty about the scenarios. Indeed, data …