Enhancing Efficiency in Aviation and Transportation Through Intelligent Radial Basis Function
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-7243-2_25
Reference15 articles.
1. Heidari, A., Navimipour, N.J., Unal, M.: A secure intrusion detection platform using blockchain and radial basis function neural networks for internet of drones. IEEE Internet Things J. (2023)
2. Baklacioglu, T.: Predicting the fuel flow rate of commercial aircraft via multilayer perceptron, radial basis function and ANFIS artificial neural networks. Aeronaut. J. 125(1285), 453–471 (2021)
3. Lopac, N., Jurdana, I., Lerga, J., Wakabayashi, N.: Particle-swarm-optimization-enhanced radial-basis-function-kernel-based adaptive filtering applied to maritime data. J. Mar. Sci. Eng. 9(4), 439 (2021)
4. Natarajan, Y., et al.: An IoT and machine learning-based routing protocol for reconfigurable engineering application. IET Commun. 16(5), 464–475 (2022)
5. Wang, R., Li, D., Miao, K.: Optimized radial basis function neural network based intelligent control algorithm of unmanned surface vehicles. J. Mar. Sci. Eng. 8(3), 210 (2020)
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