Επιστημονικές Δημοσιεύσεις

ΠΑΡΑΓΟΥΜΕ ΓΝΩΣΗ

Δεν αξιοποιούμε μόνο τη γνώση. Συμμετέχουμε ενεργά στη δημιουργία της.

Αναγνωρίζοντας το εκθετικά αυξανόμενο εύρος της γνώσης και τις ραγδαίες εξελίξεις που σημειώνονται στον επιστημονικό και τεχνολογικό χώρο, οι ερευνητές μας συνεργάζονται με κορυφαία ακαδημαϊκά στελέχη και ερευνητικές ομάδες από όλο τον κόσμο. Συμμετέχουμε ενεργά στην παραγωγή πρωτότυπης γνώσης, νέων ιδεών και καινοτόμων προσεγγίσεων, με δημοσιεύσεις ερευνητικών αποτελεσμάτων σε διεθνή, peer-reviewed επιστημονικά περιοδικά και συνέδρια.

BIOMAC—Decision Support Tool for assessing Value Chains of nano-reinforced bio-polymers

Thayana Rigo Caser, Dr. Marinella Tsakalova, Maria Voumvoulaki, Dr. Ioanna Deligkiozi, Dionisis Koutsantonis, Konstantinos Koutsantonis

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Micro-algae proteins for food and feed? Yes, but how? A Decision Support framework for the assessment of their sutainable production

Dr. Marinella Tsakalova, Dionisis Koutsantonis, Thayana Rigo, Dr. Ioanna Deligkiozi

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Using Machine Learning and Finite Element Modelling to Develop a Formula to Determine the Deflection of Horizontally Curved Steel I-beams. International Conference on Agents and Artificial Intelligence

Elvis Ababu, George Markou, and Nikolaos Bakas

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Improved Predictive Fundamental Period Formula for Reinforced Concrete Structures through the Use of Machine Learning Algorithms

Nathan Carstens, George Markou, and Nikolaos Bakas

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Inverse Transform Sampling for Bibliometric Literature Analysis

Nikos Bakas, Dionisis Koutsantonis, Vagelis Plevris, Andreas Langousis, and Savvas Chatzichristofis

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Investigation of performance metrics in regression analysis and machine learning-based prediction models

Vagelis Plevris, German Solorzano, Nikolaos Bakas, and Mohamed El Amine Ben Seghie

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Development of a New Fundamental Period Formula for Steel Structures Considering the Soil-structure Interaction with the Use of Machine Learning Algorithms

Ashley Westhuizen, George Markou, and Nikolaos Bakas

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Prediction of the shear capacity of reinforced concrete slender beams without stirrups by applying artificial intelligence algorithms in a big database of beams generated by 3D nonlinear finite element analysis

George Markou and Nikolaos Bakas

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Developing design formulae for reinforced concrete structures through AI algorithms and modelling

George Markou and Nikolaos P. Bakas

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Δημοσιεύσεις

ΠΑΡΑΓΟΥΜΕ ΓΝΩΣΗ

Δεν αξιοποιούμε μόνο τη γνώση. Συμμετέχουμε ενεργά στη δημιουργία της.

BIOMAC—Decision Support Tool for assessing Value Chains of nano-reinforced bio-polymers

Micro-algae proteins for food and feed? Yes, but how? A Decision Support framework for the assessment of their sutainable production

An Innovative Portable Device for Diesel Engines and Transmission Electronic Control Units Diagnosis and Debug

Bibliometric Literature Review of Adaptive Learning Systems

Using AI and ML to develop more accurate design formulae in civil engineering George Markou and Nikolaos P. Bakas

Using Machine Learning and Finite Element Modelling to Develop a Formula to Determine the Deflection of Horizontally Curved Steel I-beams. International Conference on Agents and Artificial Intelligence

Improved Predictive Fundamental Period Formula for Reinforced Concrete Structures through the Use of Machine Learning Algorithms

Inverse Transform Sampling for Bibliometric Literature Analysis

Investigation of performance metrics in regression analysis and machine learning-based prediction models

Development of a New Fundamental Period Formula for Steel Structures Considering the Soil-structure Interaction with the Use of Machine Learning Algorithms

Prediction of the shear capacity of reinforced concrete slender beams without stirrups by applying artificial intelligence algorithms in a big database of beams generated by 3D nonlinear finite element analysis

Developing design formulae for reinforced concrete structures through AI algorithms and modelling

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