References.
|
1. SCOPUS database, , retrieved 2022.06.01.
2. Matlab (n.d.) https://ch.mathworks.com/help/textanalytics/ug/create-co-occurrence-network.html
3. Rajita B. S. A. S., Narwa B. S., Panda S. (2021) An efficient approach for event prediction using collaborative distance score of communities. In:
International Conference on Distributed Computing and Internet Technology (pp. 271279). Springer, Cham.
4. Newman M. E. (2004). Coauthorship networks and patterns of scientific collaboration. Proceedings of the National Academy of Sciences 101(suppl_-
1), 52005205.
5. Zhang Y., Wu M., Tian G. Y., Zhang G., Lu J. (2021) Ethics and privacy of artificial intelligence: Understandings from bibliometrics. KnowledgeBased Systems 222, 106994.
6. Elmsili B., Outtaj B. (2018) Artificial neural networks applications in economics and management research: An exploratory literature review. In:
2018 4th International Conference on Optimization and Applications (ICOA) (pp. 16). IEEE.
7. Ahli, H., Merabtene, T., Seddique, M. (2021, December). Optimization of a Conceptual Rainfall-Runoff Model using Evolutionary Computing methods.
In: 2021 14th International Conference on Developments in eSystems Engineering (DeSE) (pp. 424431). IEEE.
8. Storn R., Price K. (1997). Differential evolutiona simple and efficient heuristic for global optimization over continuous spaces. Journal of Global
Optimization 11(4), 341359.
9. Jebaraj L. (2022) Applications of Differential Evolution in Electric Power Systems. In: Differential Evolution: From Theory to Practice (pp.
265296). Springer, Singapore.
10. Yan W., Bai Y., Xu R., Neculaes V. B. (2022) X-ray source design optimization using differential evolution algorithms A case study. Review of
Scientific Instruments 93(5), 053101.
11. Long W., Gao Y. (2022) Artificial Intelligence Education System Based on Differential Evolution Algorithm to Optimize SVM. Scientific Programming.
12. Liu J., Liang B., Ji W. (2021) An anomaly detection approach based on hybrid differential evolution and K-means clustering in crowd intelligence.
International Journal of Crowd Science.
13. Yu Y., Wang H., Liu S., Guo L., Yeoh P. L., Vucetic B., Li, Y. (2021). Distributed multi-agent target tracking: A Nash-combined adaptive differential
evolution method for UAV systems. IEEE Transactions on Vehicular Technology 70(8), 81228133.
14. Choi T. J., Togelius J. (2021) Self-referential quality diversity through differential MAP-Elites. In: Proceedings of the Genetic and Evolutionary
Computation Conference (pp. 502509).
15. Lambrinidis G., Tsantili-Kakoulidou A. (2021) Multi-objective optimization methods in novel drug design. Expert Opinion on Drug Discovery 16(6),
647658.
16. Boukhari N., Debbat F., Monmarchι N., Slimane M. (2021) Solving Mono- and Multi-Objective Problems Using Hybrid Evolutionary Algorithms and
Nelder-Mead Method. International Journal of Applied Metaheuristic Computing (IJAMC) 12(4), 98116.
17. Nie X., Luo J. (2021) The hybrid intelligent optimization algorithm and multi-objective optimization based on big data. In: Journal of Physics:
Conference Series (Vol. 1757, No. 1, p. 012132). IOP Publishing.
18. Wang T., Yang X., Mi C. (2021) An efficient hybrid reliability analysis method based on active learning Kriging model and multimodal optimization
based importance sampling. International Journal for Numerical Methods in Engineering 122(24), 76647682.
19. De Melo M. C., Santos P. B., Faustino E., Bastos-Filho C. J., Sodrι A. C. (2021) Computational Intelligence-Based Methodology for Antenna Development. IEEE Access 10, 18601870.
20. Kumar R., Wang W., Kumar J., Yang T., Khan A., Ali W., Ali I. (2021) An integration of blockchain and AI for secure data sharing and detection of
CT images for the hospitals. Computerized Medical Imaging and Graphics 87, 101812.
21. Shankar K., Perumal E., D΄?az V. G., Tiwari P., Gupta D., Saudagar A. K. J., Muhammad K. (2021) An optimal cascaded recurrent neural network for
intelligent COVID-19 detection using Chest X-ray images. Applied Soft Computing 113, 107878.
22. Afza F., Sharif M., Khan M. A., Tariq U., Yong H. S., Cha J. (2022) Multiclass skin lesion classification using hybrid deep features selection and
extreme learning machine. Sensors 22(3), 799.
23. Fatani A., Abd Elaziz M., Dahou A., Al-Qaness M. A., Lu S. (2021) IoT intrusion detection system using deep learning and enhanced transient search
optimization. IEEE Access 9, 123448123464.
24. Mishra P., Gupta A., Aggarwal P., Pilli E. S. (2022) vServiceInspector: Introspection-assisted evolutionary bag-of-ngram approach to detect malware
in cloud servers. Ad Hoc Networks 131, 102836.
25. Florkowski M. (2021) Anomaly Detection, Trend Evolution, and Feature Extraction in Partial Discharge Patterns. Energies 14(13), 3886.
26. Ge M. (2022) Recognition and Detection Methods of Artificial Intelligence in Computer Network Faults under the Background of Big Data. Wireless
Communications and Mobile Computing 2022.
27. Erfanian P. Y., Cami B. R., Hassanpour H. (2022) An evolutionary event detection model using the Matrix Decomposition Oriented Dirichlet Process.
Expert Systems with Applications 189, 116086.
28. Rajita B. S. A. S., Bansal M., Narwa B. S., Panda, S. (2022) Cuckoo search in threshold optimization for better event detection in social networks.
Social Network Analysis and Mining 12(1), 119.
29. Aslan S. (2021) Modified artificial bee colony algorithms for solving multiple circle detection problem. The Visual Computer 37(4), 843856.
30. Lai X., Jin C., Yi W., Han X., Feng X., Zheng Y., Ouyang M. (2021) Mechanism, modeling, detection, and prevention of the internal short circuit in
lithium-ion batteries: recent advances and perspectives. Energy Storage Materials 35, 470499.
31. Zahedi L., Ghareh Mohammadi F., Amini M. H. (2022) A2BCF: An Automated ABC-Based Feature Selection Algorithm for Classification Models in
an Education Application. Applied Sciences 12(7), 3553.
32. Chen J., Ramanathan, L., Alazab M. (2021). Holistic big data integrated artificial intelligent modeling to improve privacy and security in data management
of smart cities. Microprocessors and Microsystems 81, 103722.
33. Chaitra H. V., RaviKumar G. K. (2021) Secure and Energy-Efficient Data Transmission. In: Advances in Artificial Intelligence and Data Engineering
(pp. 13111322). Springer, Singapore.
34. Bokhari S. M. A., Theel O. (2020) Designing New Data Replication Strategies Automatically. In: International Conference on Agents and Artificial
Intelligence (pp. 308331). Springer, Cham.
35. Sekera J., Novak A. (2021) The future of data communication in Aviation 4.0 environment. ΄ INCAS Bulletin 13(3), 165178.
36. Gong J., Sihag V., Kong Q., Zhao L. (2021) Visualizing Knowledge Evolution Trends and Research Hotspots of Personal Health Data Research:
Bibliometric Analysis. JMIR Medical Informatics 9(11), e31142.
37. Rahmani A. M., Azhir E., Naserbakht M., Mohammadi M., Aldalwie A. H. M., Majeed M. K., Hosseinzadeh M. (2022) Automatic COVID-19 detection
mechanisms and approaches from medical images: a systematic review. Multimedia Tools and Applications 120.
38. Pourdarbani R., Sabzi S., Rohban M. H., Garc΄?a-Mateos G., Arribas, J. I. (2021) Nondestructive nitrogen content estimation in tomato plant leaves by
Vis-NIR hyperspectral imaging and regression data models. Applied Optics 60(30), 95609569.
39. Taghizadeh-Mehrjardi R., Emadi M., Cherati A., Heung B., Mosavi A., Scholten T. (2021) Bio-inspired hybridization of artificial neural networks: An
application for mapping the spatial distribution of soil texture fractions. Remote Sensing 13(5), 1025.
40. Uchihira N. (2021) Dialogue Tool for Value Creation in Digital Transformation: Roadmapping for Machine Learning Applications. In: International
Conference on Applied Human Factors and Ergonomics (pp. 518526). Springer, Cham.
41. Almosnino S., Cappelletto J. (2021) Minimizing low back cumulative loading during design of manual material handling tasks: An optimization
approach. IISE Transactions on Occupational Ergonomics and Human Factors 9(34), 124133.
42. De Lima Mendes R., da Silva Alves A. H., de Souza Gomes M., Bertarini P. L. L., do Amaral L. R. (2021) Many Layer Transfer Learning Genetic Algorithm
(MLTLGA): a New Evolutionary Transfer Learning Approach Applied To Pneumonia Classification. In: 2021 IEEE Congress on Evolutionary
Computation (CEC) (pp. 24762482). IEEE.
43. Polkowski Z., Mishra J. P., Mishra S. K. (2021) Prioritization of complex heterogeneous queries using evolutionary and computational approach. In:
2021 13th International Conference on Electronics, Computers and Artificial Intelligence (ECAI) (pp. 15). IEEE.
44. Adeleke O., Akinlabi S., Jen T. C., Dunmade I. (2022) A machine learning approach for investigating the impact of seasonal variation on physical
composition of municipal solid waste. Journal of Reliable Intelligent Environments 120.
45. Nayeri Z. M., Ghafarian T., Javadi B. (2021) Application placement in Fog computing with AI approach: Taxonomy and a state of the art survey.
Journal of Network and Computer Applications 185, 103078.
46. Abdollahizad S., Balafar M. A., Feizizadeh B., Babazadeh Sangar A., Samadzamini K. (2021) Using hybrid artificial intelligence approach based on a
neuro-fuzzy system and evolutionary algorithms for modeling landslide susceptibility in East Azerbaijan Province, Iran. Earth Science Informatics
14(4), 18611882.
47. Repecka D., Jauniskis V., Karpus L., Rembeza E., Rokaitis I., Zrimec J., Zelezniak A. (2021) Expanding functional protein sequence spaces using
generative adversarial networks. Nature Machine Intelligence 3(4), 324333.
48. Rives A., Meier J., Sercu T., Goyal S., Lin Z., Liu J., Fergus R. (2021). Biological structure and function emerge from scaling unsupervised learning to
250 million protein sequences. Proceedings of the National Academy of Sciences, 118(15), e2016239118.
49. Gopinath T., Manu V. S., Weber D. K., Veglia G. (2022) PHRONESIS: a one-shot approach for sequential assignment of protein resonances by ultrafast
MAS solid-state NMR spectroscopy. ChemPhysChem
50. Czajkowski M., Jurczuk K., Kretowski M. (2021) Accelerated evolutionary induction of heterogeneous decision trees for gene expression-based classification.
In: Proceedings of the Genetic and Evolutionary Computation Conference (pp. 946954).
51. Beni G., Wang, J. (1993). Swarm intelligence in cellular robotic systems. In: Robots and Biological Systems: Towards a New Bionics? (pp. 703712).
Springer, Berlin, Heidelberg.
52. Kadkol, A. A. (2021) Mathematical model of particle swarm optimization: numerical optimization problems. In: Applying Particle Swarm Optimization (pp. 7395). Springer, Cham.
53. Mittal A., Pattnaik A., Tomar A. (2021) Different variants of particle swarm optimization algorithms and its application: A review. Metaheuristic and
Evolutionary Computation: Algorithms and Applications 131163.
54. Chen P. Y., Chen R. B., Wong, W. K. (2022) Particle swarm optimization for searching efficient experimental designs: A review.
Wiley Interdisciplinary Reviews: Computational Statistics e1578.
55. Liu, Y., Qin, W., Zhang, J., Li M., Zheng, Q., Wang J. (2021) Multi-Objective Ant Lion Optimizer Based on Time Weight. IEICE Transactions on
Information and Systems 104(6), 901904.
56. Li L., Sun L., Xue Y., Li S., Huang X., Mansour R. F. (2021) Fuzzy multilevel image thresholding based on improved coyote optimization algorithm.
IEEE Access 9, 3359533607.
57. Kounte M.R., Niveditha E., Afrose K., Sai Sudeshna A. (2020) Problem Solving Techniques Using Ant Colony Optimization in Computational Intelligence.
2nd International Conference on Data Science, Machine Learning and Applications, ICDSMLA 2020. Volume 783, pp. 739747.
58. Qi X., Gan Z., Liu C., Xu Z., Zhang X., Li W., Ouyang C. (2021) Collective intelligence evolution using ant colony optimization and neural networks.
Neural Computing and Applications 33(19), 1272112735.
59. Karaboga D. (2005) An idea based on honey bee swarm for numerical optimization (Vol. 200, pp. 110). Technical Report - tr06, Erciyes University,
Engineering Faculty, Computer Engineering Department.
60. Zhang J., Zhang Z., Lin X. (2021) An Improved Artificial Bee Colony with Self-Adaptive Strategies and Application. In:2021 International Conference
on Computer Network, Electronic and Automation (ICCNEA) (pp. 101104). IEEE.
61. Solgi R., Loaiciga H. A. (2021) Bee-inspired metaheuristics for global optimization: a performance comparison. ΄ Artificial Intelligence Review 54(7),
49674996.
62. Yang X. S. (2008) Nature-Inspired Metaheuristic Algorithms. Luniver Press.
63. Kaur G., Moulik B., Rao K. U. (2021) Determining the optimum TMS and PS of overcurrent relays using the Firefly Algorithm for solving the relay
coordination problem. In: 2021 5th International Conference on Computing Methodologies and Communication (ICCMC) (pp. 10111015). IEEE.
64. Yang X. S., Deb S. (2009) Cuckoo search via Lιvy flights. In 2009 World Congress on Nature Biologically Inspired Computing (NaBIC) (pp.
210214). IEEE.
65. Yang X. S. (2010) A new metaheuristic bat-inspired algorithm. In Nature-Inspired Cooperative Strategies for Optimization (NICSO 2010) (pp. 6574).
Springer, Berlin, Heidelberg.
66. Huang M., Liu S., Zhang Y., Cui K., Wen Y. (2022) Basic Theory and Practice Teaching Method Based on the Cerebellar Model Articulation Controller
Learning Algorithm. Wireless Communications and Mobile Computing 2022.
67. Wang G. G., Zhao X., Deb S. (2015) A novel monarch butterfly optimization with greedy strategy and self-adaptive. In: 2015 Second International
Conference on Soft Computing and Machine Intelligence (ISCMI) (pp. 4550). IEEE.
68. Ghetas M., Yong C. H., Sumari P. (2015) Harmony-based monarch butterfly optimization algorithm. In: 2015 IEEE International Conference on
Control System, Computing and Engineering (ICCSCE) (pp. 156161). IEEE.
69. Feng Y., Deb S., Wang G. G., Alavi A. H. (2021) Monarch butterfly optimization: a comprehensive review. Expert Systems with Applications, 168,
114418.
70. Pierezan, J., Coelho, L. D. S. (2018, July). Coyote optimization algorithm: a new metaheuristic for global optimization problems. In: 2018 IEEE
Congress on Evolutionary Computation (CEC) (pp. 18). IEEE.
71. Li F. (2021) Research and Design of Artificial Intelligence Training Platform Based on Improved ant Colony Algorithm. In: 2021 International
Conference on Aviation Safety and Information Technology (pp. 860863).
72. Sulaiman M. H., Mustaffa Z., Saari M. M., Daniyal H. (2020) Barnacles mating optimizer: a new bio-inspired algorithm for solving engineering
optimization problems. Engineering Applications of Artificial Intelligence 87, 103330.
73. Fountas N. A., Vaxevanidis N. M. (2021) Optimization of abrasive flow nano-finishing processes by adopting artificial viral intelligence. Journal of
Manufacturing and Materials Processing 5(1), 22.
74. Wu S. (2022) Application of Artificial Immune Algorithm in Evolutionary Creation. In: International Conference on Cognitive-based Information
Processing and Applications (CIPA 2021) (pp. 766771). Springer, Singapore.
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