Genetic Programming Bibliography entries for Amirhessam Tahmassebi

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GP coauthors/coeditors: A H Gandomi, Ian McCann, Mieke H J Schulte, Lianne Schmaal, Anna E Goudriaan, Anke Meyer-Baese, Akbar Telikani, Wolfgang Banzhaf,

Genetic Programming Articles by Amirhessam Tahmassebi

• Akbar Telikani and Amirhessam Tahmassebi and Wolfgang Banzhaf and Amir H. Gandomi. Evolutionary Machine Learning: A Survey. ACM Computing Surveys, 54(8):Article 161, 2021. details

• Amirhessam Tahmassebi and Amir H. Gandomi. Building energy consumption forecast using multi-objective genetic programming. Measurement, 118:164-171, 2018. details

Genetic Programming conference papers by Amirhessam Tahmassebi

1. Amirhessam Tahmassebi and Amir H. Gandomi and Anke Meyer-Baese. A Pareto Front Based Evolutionary Model for Airfoil Self-Noise Prediction. In Marley Vellasco editor, 2018 IEEE Congress on Evolutionary Computation (CEC), Rio de Janeiro, Brazil, 2018. IEEE. details

2. Amirhessam Tahmassebi and Amir H. Gandomi and Anke Meyer-Baese. An Evolutionary Online Framework for MOOC Performance Using EEG Data. In Marley Vellasco editor, 2018 IEEE Congress on Evolutionary Computation (CEC), Rio de Janeiro, Brazil, 2018. IEEE. details

3. Amirhessam Tahmassebi and Amir H. Gandomi and Ian McCann and Mieke H. J. Schulte and Lianne Schmaal and Anna E. Goudriaan and Anke Meyer-Baese. An evolutionary approach for fMRI big data classification. In Jose A. Lozano editor, 2017 IEEE Congress on Evolutionary Computation (CEC), pages 1029-1036, Donostia, San Sebastian, Spain, 2017. IEEE. details

4. Amirhessam Tahmassebi and Amir H. Gandomi and Ian McCann and Mieke H. J. Schulte and Lianne Schmaal and Anna E. Goudriaan and Anke Meyer-Baese. fMRI Smoking Cessation Classification Using Genetic Programming. In Workshop on Data Science meets Optimization, Spain, 2017. details

5. Amirhessam Tahmassebi and Amir H. Gandomi and Anke Meyer-Baese. High Performance GP-Based Approach for fMRI Big Data Classification. In Proceedings of the Practice and Experience in Advanced Research Computing 2017 on Sustainability, Success and Impact, PEARC17, pages 57:1-57:4, New Orleans, LA, USA, 2017. ACM. details

6. Amirhessam Tahmassebi and Amir H. Gandomi. Genetic Programming Based on Error Decomposition: A Big Data Approach. In Wolfgang Banzhaf and Randal S. Olson and William Tozier and Rick Riolo editors, Genetic Programming Theory and Practice XV, pages 135-147, University of Michigan in Ann Arbor, USA, 2017. Springer. details