Naser Ghannad

Thèse

TITRE DE LA THÈSE  : Metaheuristics and user-driven learning algorithms for accelerating the Simulation-Optimisation-Problem solving loop

RESPONSABLES DE LA THÈSE : Prof. Roland DE GUIO, Prof. Pierre PARREND

ECOLE DOCTORALE DE RATTACHEMENT : Ecole doctorale mathématiques, sciences de l'information et de l'ingénieur (ED 269) (Strasbourg) , en partenariat avec Laboratoire des sciences de l'Ingénieur, de l'Informatique et de l'Imagerie (equipe de recherche) depuis le 03-10-2019

ÉQUIPE D’ACCUEIL DE LA THÈSE : Complex Systems and Translational Bioinformatics (CSTB), Conception, Système d'Information et Processus inventifs (CSIP)

MOTS CLÉS : A.I, optimisation, industry 4.0, innovation, inventive design, simulation

Papers

• Naser GHANNAD, Roland De Guio, and Pierre Parrend, “Methodology and metrics for evaluating the rules of the rule-based classifiers", "Under review"

• Ghannad Naser, Roland De Guio, and Pierre Parrend, “One-Class Ant-Miner: Selection of Majority Class Rules for Binary Rule-based Classification”, International Conference on Artificial Evolution 2022

• Hanifi, Masih, et al "A method for facilitating and accelerating extraction of the essential data in inventive design", journal Artificial Intelligence for Engineering Design Analysis and Manufacturing, February 2022

• Ghannad, Naser, Roland De Guio, and Pierre Parrend. "Feature Selection-Based Approach for Generalized Physical Contradiction Recognition." International TRIZ Future Conference. Springer, Cham, 2020.

• Malik, Usman, et al. "A generic machine learning based approach for addressee detection in multiparty interaction." Proceedings of the 19th ACM International Conference on Intelligent Virtual Agents, 2019

• Naser Ghannad, Mahdi Yaghoobi, “Chaotic NMEEF-SD: chaotic Parents selection in Non- dominanted Multiobjective Evolutionary Algorithm to extract fuzzy rules for subgroup discovery”, 8th Symposium on Advances in Science & Technology, Ferdowsi University of Mashhad, Iran, 20 May 2013 [in Persian]

• Naser Ghannad, Mahdi Yaghoobi, Mohammad Reza Akbarzadeh-Totonchi, “Forecasting of the number of tourists using the support vector regression and optimization the parameters by chaotic genetic algorithm.”, 8th Symposium on Advances in Science & Technology, Ferdowsi University of Mashhad, Iran, 20 May 2013[in Persian]

• Naser Ghannad, Mahdi Yaghoobi, Mohammad Reza Akbarzadeh-Totonchi, “Forecasting the trend stock market using the combination of SVM and ANFIS based on the feature selection by fuzzy entropy.”, 5th Iranian conference on electrical and electronic engineering, Islamic Azad University of Gonabad, Iran, 12August 2013[in Persian]

• Samira Esmaty, Mahdi Yaghoobi, Naser Ghannad, “Provides a new techniquefor Automatic Traffic Accident Detectionbased on support vector machine.”, 5th Iranian conference on electrical and electronic engineering, Islamic Azad University of Gonabad, Iran, 12 August 2013[in Persian]

• Naser Ghannad, Mahdi Yaghoobi, “forecast stock market movements with using the combination of SVM and RUSBoost based on fuzzy entropy feature selection.”, 5th Iranian conference on electrical and electronic engineering, Islamic Azad University of Gonabad, Iran, 12 August 2013[in Persian]

• Naser Ghannad, Reza Sedighi, Vajihe dehdele, “Chaotic NMEEF-SD: chaotic Non- dominanted Multiobjective Evolutionary Algorithm to extract fuzzy rules for subgroup discovery.”, 11th Iranian conference on intelligence system, Kharazmi University Tehran, Iran, March 2013[in Persian]

• Naser Ghannad, “Web spam detection with using extraction of link quality and relation of link of pages to links in other pages.”, Congress on Electrical, Computer and Information Technology, Khayam Universityof Mashhhad, Iran,8 November, 2013[in Persian]

• Samira Esmaty, Naser Ghannad, Tohid Akhlaghi, “Provides a new technique for Automatic Traffic Accident Detection based on hybrid of support vector machine and Anfis.”, 13th Iranian conference on fuzzy system, Islamic Azad University of Ghazvin, Iran, 27 August 2013[in Persian]

Contact

Adresse e-mail : naser.ghannad@etu.unistra.fr