Design of fuzzy hyperbox classifiers based on a two-stage genetic algorithm and simultaneous strategy
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Azad C, Mehta AK, Jha VK (2018) Improved data classification using fuzzy euclidean hyperbox classifier. In: 2018 international conference on smart computing and electronic enterprise (ICSCEE), pp 1–6
Bargiela A, Pedrycz W, Tanaka M (2004) An inclusion/exclusion fuzzy hyperbox classifier. Int J Knowl Based Intell Eng Syst 8(2):91–98
Chavan TR, Nandedkar AV (2019) A convolutional fuzzy min-max neural network for image classification. In: Computer vision and image processing - 4th international conference, CVIP 2019, Jaipur, India, September 27–29, 2019, revised selected papers, Part II, Springer, communications in computer and information science, vol 1148, pp 107–116
Davtalab R, Dezfoulian MH, Mansoorizadeh M (2014) Multi-level fuzzy min-max neural network classifier. IEEE Trans Neural Networks Learn Syst 25(3):470–482
Ezerceli AEM (2022) Convolutional neural network (cnn) algorithm based facial emotion recognition (fer) system for fer-2013 dataset. 2022 international conference on electrical. Computer, communications and mechatronics Engineering (ICECCME), pp 1–6
Frank A, Asuncion A (2010) Uci machine learning repository. http://www.ics.uci.edu/mlearn/MLRepository.html. Accessed 7 Oct 2023
Gabrys, Bogdan, Bargiela, Andrzej (2000) General fuzzy min-max neural network for clustering and classification. IEEE Transactions on Neural Networks
Gao H, Qiu B, Duran Barroso RJ, Hussain W, Xu Y, Wang X (2022a) Tsmae: a novel anomaly detection approach for internet of things time series data using memory-augmented autoencoder. IEEE transactions on network science and engineering, pp 1–1
Gao H, Xiao J, Yin Y, Liu T, Shi J (2022b) A mutually supervised graph attention network for few-shot segmentation: the perspective of fully utilizing limited samples. IEEE transactions on neural networks and learning systems, pp 1–13
Huang W, Sun M, Zhu L, Oh SK, Pedrycz W (2022a) Deep fuzzy min-max neural network: analysis and design. IEEE transactions on neural networks and learning systems, pp 1–12. https://doi.org/10.1109/TNNLS.2022.3226040
Huang W, Wang Y, Zhu L (2022b) A time impulse neural network framework for solving the minimum path pair problems of the time-varying network. IEEE transactions on knowledge and data engineering pp 1–12. https://doi.org/10.1109/TKDE.2022.3217394
Huang W, Zhang Y, Wan S (2022c) A sorting fuzzy min-max model in an embedded system for atrial fibrillation detection. ACM Trans Multimedia Comput Commun Appl 18(2s)
Khosravi MR, Rezaee K, Moghimi MK, Wan S, Menon VG (2023) Crowd emotion prediction for human-vehicle interaction through modified transfer learning and fuzzy logic ranking. IEEE transactions on intelligent transportation systems pp 1–10. https://doi.org/10.1109/TITS.2023.3239114
Kumar SA, Kumar A, Bajaj V, Singh GK (2020) An improved fuzzy min-max neural network for data classification. IEEE Transactions on Fuzzy Systems 28(9):1910–1924
Li J, Li L (2019) An improvement proposal of genetic algorithms based on information entropy and game theory. In: Sixth international conference on social networks analysis, management and security, SNAMS 2019, Granada, Spain, October 22–25, 2019, pp 36–43
Lin CL, Hsieh ST, Hu YJ (2013a) Fuzzy neural network-based influenza diagnostic system. In: Proceedings of the 2013 first international symposim on computing and networking, IEEE computer society, USA, CANDAR ’13, pp 633–635
Lin Y, Chang J, Lin C (2013) Identification and prediction of dynamic systems using an interactively recurrent self-evolving fuzzy neural network. IEEE Trans Neural Networks Learn Syst 24(2):310–321
Liu J, Ma Y, Zhang H, Su H, Xiao G (2017) A modified fuzzy min-max neural network for data clustering and its application on pipeline internal inspection data. Neurocomputing 238:56–66
Ma Y, Liu J, Qu F, Zhu H (2022) Evolved fuzzy min-max neural network for new-labeled data classification 52(1):305–320
Malek H, Ebadzadeh MM, Rahmati M (2012) Three new fuzzy neural networks learning algorithms based on clustering, training error and genetic algorithm
Mohammed MF, Lim CP (2015) An enhanced fuzzy min-max neural network for pattern classification. IEEE Trans Neural Networks Learn Syst 26(3):417–429
Mohammed MF, Lim CP (2017) A new hyperbox selection rule and a pruning strategy for the enhanced fuzzy min-max neural network. Neural Networks 86:69–79
Nandedkar AV, Biswas PK (2007) A fuzzy min-max neural network classifier with compensatory neuron architecture. IEEE Trans Neural Networks 18(1):42–54
Nijhout F (1997) An introduction to genetic algorithms. Complex 2(5):39–40
Peng C, Zhang R, ChunHao D (2022) Dynamic hidden variable fuzzy broad neural network based batch process anomaly detection with incremental learning capabilities. Expert Syst Appl 202:117390
Pourpanah F, Lim CP, Wang X, Tan CJ, Seera M, Shi Y (2019) A hybrid model of fuzzy min-max and brain storm optimization for feature selection and data classification. Neurocomputing 333:440–451
Quteishat A, Lim C (2008) Application of the fuzzy min-max neural networks to medical diagnosis. Springer-Verlag
Quteishat A, Lim CP, Tan KS (2010) A modified fuzzy min-max neural network with a genetic-algorithm-based rule extractor for pattern classification. IEEE Trans Syst Man Cybern Part A 40(3):641–650
Quteishat AM, Lim CP (2007) A modified fuzzy min-max neural network and its application to fault classification. Soft Computing in Industrial Applications. Springer, Berlin Heidelberg, Berlin, Heidelberg, pp 179–188
Simpson P (1992) Fuzzy min-max neural networks i classification. IEEE Transactions on Neural Networks 3(5):776–786
Sun Y, Xue B, Zhang M, Yen GG (2020) Completely automated CNN architecture design based on blocks. IEEE Trans Neural Networks Learn Syst 31(4):1242–1254
Upasani N, Om H (2015) Evolving fuzzy min-max neural network for outlier detection. Procedia Computer Science 45:753–761
Wang JG, Tai SC, Lin CJ (2018) The application of an interactively recurrent self-evolving fuzzy cmac classifier on face detection in color images. Neural Comput Appl 29(6):201–213
Wei W, Yang R, Gu H, Zhao W, Chen C, Wan S (2022) Multi-objective optimization for resource allocation in vehicular cloud computing networks. IEEE Transactions on Intelligent Transportation Systems 23(12):25536–25545. https://doi.org/10.1109/TITS.2021.3091321
Xie L, Yuille AL (2017) Genetic cnn. In: IEEE international conference on computer vision, ICCV 2017, Venice, Italy, October 22–29, 2017, pp 1388–1397