What is she best known for?
The fields of study she is best known for:
- Artificial intelligence
- Machine learning
- Statistics
Elpiniki I. Papageorgiou mainly investigates Fuzzy cognitive map, Artificial intelligence, Machine learning, Fuzzy logic and Soft computing.
Her Fuzzy cognitive map study integrates concerns from other disciplines, such as Algorithm, Particle swarm optimization, Multi-swarm optimization and Knowledge representation and reasoning.
Her Artificial intelligence research focuses on subjects like Data mining, which are linked to Genetic algorithm and Multivariate statistics.
Her Machine learning research is multidisciplinary, relying on both Fuzzy set and Decision support system.
The various areas that Elpiniki I. Papageorgiou examines in her Soft computing study include Fuzzy classification and Robustness.
Her biological study spans a wide range of topics, including Interpretability, Unsupervised learning and Nonlinear system.
Her most cited work include:
- A Review of Fuzzy Cognitive Maps Research During the Last Decade (263 citations)
- Active Hebbian learning algorithm to train fuzzy cognitive maps (250 citations)
- Learning Algorithms for Fuzzy Cognitive Maps—A Review Study (204 citations)
What are the main themes of her work throughout her whole career to date?
Her scientific interests lie mostly in Fuzzy cognitive map, Artificial intelligence, Machine learning, Fuzzy logic and Decision support system.
Her research integrates issues of Soft computing, Hebbian theory, Process and Knowledge representation and reasoning in her study of Fuzzy cognitive map.
Her Artificial intelligence research is multidisciplinary, incorporating elements of Genetic algorithm and Data mining.
Her Machine learning research integrates issues from Fuzzy set, Medical diagnosis and Algorithm.
The study incorporates disciplines such as Operations research, Control theory, Expert system and Nonlinear system in addition to Fuzzy logic.
Her Decision support system research incorporates themes from Intelligent decision support system, Fuzzy rule and Decision tree.
She most often published in these fields:
- Fuzzy cognitive map (81.94%)
- Artificial intelligence (75.77%)
- Machine learning (56.39%)
What were the highlights of her more recent work (between 2018-2021)?
- Artificial intelligence (75.77%)
- Fuzzy cognitive map (81.94%)
- Machine learning (56.39%)
In recent papers she was focusing on the following fields of study:
Elpiniki I. Papageorgiou spends much of her time researching Artificial intelligence, Fuzzy cognitive map, Machine learning, Deep learning and Artificial neural network.
Her research in Artificial intelligence focuses on subjects like Pattern recognition, which are connected to Tree.
Her Fuzzy cognitive map study is concerned with the larger field of Fuzzy logic.
Her work deals with themes such as Neuro-fuzzy and Key, which intersect with Machine learning.
Her studies examine the connections between Neuro-fuzzy and genetics, as well as such issues in Adaptive neuro fuzzy inference system, with regards to Soft computing.
Her Perceptron study in the realm of Artificial neural network interacts with subjects such as Natural gas consumption.
Between 2018 and 2021, her most popular works were:
- Fuzzy Cognitive Map-Based Sustainable Socio-Economic Development Planning for Rural Communities (13 citations)
- Characteristics and scenarios of solar energy development in Iran: Fuzzy cognitive map-based approach (12 citations)
- Application of machine intelligence for osteoarthritis classification: a classical implementation and a quantum perspective (11 citations)
In her most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Statistics
Elpiniki I. Papageorgiou mainly focuses on Artificial intelligence, Fuzzy cognitive map, Deep learning, Environmental economics and Machine learning.
Her Artificial intelligence study incorporates themes from Big data and Pattern recognition.
Her work carried out in the field of Fuzzy cognitive map brings together such families of science as Outcome and Trajectory.
Her Deep learning research includes elements of Variation and Radiology.
As a part of the same scientific family, Elpiniki I. Papageorgiou mostly works in the field of Environmental economics, focusing on Context and, on occasion, Decision-making, Energy management, Scenario analysis, Decision support system and Supply chain management.
The Machine learning study combines topics in areas such as System parameters, Neuro-fuzzy, Inference system and Fuzzy inference.
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