Subject Areas : Electrical Engineering
Arash Mazidi 1 , Fahimeh Roshanfar 2
1 - Department of Computer Engineering, Faculty of Engineering, Golestan University, Gorgan, Iran.
2 - Department of Nanotechnology and Advanced Materials, Materials and Energy Research Center, Karaj, Iran
Keywords:
Abstract :
[1] A. Mazidi, F. Roshanfar, and V. Parvin Darabad, “A Review of Outliers: Towards a Novel Fuzzy Method for Outlier Detection ,” J. Appl. Dyn. Syst. Control, vol. 2, no. 1, pp. 7–17, Jun. 2019.
[2] B. Patel, V. Singh, and D. Patel, “Structural Bioinformatics,” in Essentials of Bioinformatics, Volume I, Cham: Springer International Publishing, 2019, pp. 169–199.
[3] A. Mazidi, M. Fakhrahmad, and M. Sadreddini, “A meta-heuristic approach to CVRP problem : local search optimization based on GA and ant colony,” J. Adv. Comput. Res., vol. 7, no. December, pp. 1–22, 2016.
[4] A. Mazidi and E. Damghanijazi, “Meta-Heuristic Approaches for Solving Travelling Salesman Problem A meta-heuristic approach to CVRP problem View project Meta-Heuristic Approaches for Solving Travelling Salesman Problem View project Meta-Heuristic Approaches for Solving Travelling Salesman Problem,” Int. J. Adv. Res. Comput. Sci., vol. 8, no. 5.
[5] B. Berger and T. Leighton, “Protein folding in the hydrophobic-hydrophilic (HP) model is NP-complete, Mathematics Department and Laboratory for Computer Science,” 1998.
[6] R. Unger and J. Moult, “Genetic algorithms for protein folding simulations,” J. Mol. Biol., vol. 231, no. 1, pp. 75–81, May 1993.
[7] K. F. Lau and K. A. Dill, “A Lattice Statistical Mechanics Model of the Conformational and Sequence Spaces of Proteins,” Macromolecules, vol. 22, no. 10, pp. 3986–3997, Oct. 1989.
[8] A. A. Tantar, N. Melab, E. G. Talbi, B. Parent, and D. Horvath, “A parallel hybrid genetic algorithm for protein structure prediction on the computational grid,” Futur. Gener. Comput. Syst., vol. 23, no. 3, pp. 398–409, Mar. 2007.
[9] V. Cutello, G. Nicosia, M. Pavone, and J. Timmis, “An immune algorithm for protein structure prediction on lattice models,” IEEE Trans. Evol. Comput., vol. 11, no. 1, pp. 101–117, Feb. 2007.
[10] R. Unger, “The Genetic Algorithm Approach to Protein Structure Prediction,” Springer, Berlin, Heidelberg, 2004, pp. 153–175.
[11] H. D. D. Ziero, L. S. Buller, A. Mudhoo, L. C. Ampese, S. I. Mussatto, and T. F. Carneiro, “An overview of subcritical and supercritical water treatment of different biomasses for protein and amino acids production and recovery,” J. Environ. Chem. Eng., p. 104406, Sep. 2020.
[12] A. Mazidi, E. Damghanijazi, and S. Tofighy, “An Energy-efficient Virtual Machine Placement Algorithm based Service Level Agreement in Cloud Computing Environments,” Circ. Comput. Sci., vol. 2, no. 6, pp. 1–6, 2017.
[13] A. Mazidi, M. Golsorkhtabaramiri, and M. Y. Tabari, “Autonomic resource provisioning for multilayer cloud applications with K-nearest neighbor resource scaling and priority-based resource allocation,” Softw. Pract. Exp., Apr. 2020.
[14] Sharapov RR, “Genetic Algorithms: Basic Ideas, Variants and Analysis,” 2007.
[15] M. T. Hoque, M. Chetty, A. Lewis, A. Sattar, and V. M. Avery, “DFS-generated pathways in GA crossover for protein structure prediction,” Neurocomputing, vol. 73, no. 13–15, pp. 2308–2316, Aug. 2010.
[16] A. Mazidi, M. Golsorkhtabaramiri, and M. Yadollahzadeh Tabari, “An autonomic risk- and penalty-aware resource allocation with probabilistic resource scaling mechanism for multilayer cloud resource provisioning,” Int. J. Commun. Syst., p. e4334, Feb. 2020.
[17] I. S. Hart W, “HP Benchmarks,” 2005.
[18] N. Lesh, M. Mitzenmacher, and S. Whitesides, “A complete and effective move set for simplified protein folding,” in Proceedings of the Annual International Conference on Computational Molecular Biology, RECOMB, 2003, pp. 188–195.