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Hassanien, A. E., and J. M. H. Ali, "A Fuzzy-Rule based Algorithm for Contrast Enhancement of Mammograms Breast Masses", Wseas Transaction, 2014. AbstractWebsite

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Merkl, C., L. N. Smith, M. R. Mahfouz, and A. M. Badawi, "Fuzzy-Neural multiple bone sex classification system utilizing genetic algorithms", Cairo International Biomedical Engineering Conference Dec. 2006 (CIBEC06): IEEE, 2006. Abstract
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Nabil, E., A. Badr, and I. Farag, "A Fuzzy-Membrane-Immune Algorithm For Breast Cancer Diagnosis", Universitatis Babeş-Bolyai Informatica, vol. LVII, issue 2, 2012. Abstracta_fuzzy-membrane-immune_algorithm_for_breast_cancer_diagnosis.pdf

Abstract. The automatic diagnosis of breast cancer is an important medical problem. This paper hybridizes metaphors from cells membranes and intercommunication between compartments with clonal selection principle together with fuzzy logic to produce a fuzzy rule system in order to be used in diagnosis. The fuzzy-membrane-immune algorithm suggested were implemented and tested on the Wisconsin breast cancer diagnosis (WBCD) problem. The developed solution scheme is compared with five previous works based on neural networks and genetic algorithms. The algorithm surpasses all of them. There are two motivations for using fuzzy rules with the membrane-immune algorithm in the underline problem. The first is attaining high classification performance. The second is the possibility of attributing a confidence measure (degree of benignity or malignancy) to the output diagnosis, beside the simplicity of the diagnosis system, which means that the system is human interpretable.

E.Nabil, A.Badr, and I.Farag, "A Fuzzy-Membrane-Immune Algorithm For Breast Cancer Diagnosis", Babes Bolyai, vol. 7, pp. 3-19, 2012. Abstract

The automatic diagnosis of breast cancer is an important medical problem. This paper hybridizes metaphors from cells membranes and intercommunication between compartments with clonal selection principle together with fuzzy logic to produce a fuzzy rule system in order to be used in diagnosis. The fuzzy-membrane-immune algorithm suggested were implemented and tested on the Wisconsin breast cancer diagnosis (WBCD) problem. The developed solution scheme is compared with five previous works based on neural networks and genetic algorithms. The algorithm surpasses all of them. There are two motivations for using fuzzy rules with the membrane-immune algorithm in the underline problem. The first is attaining high classification performance. The second is the possibility of attributing a confidence measure (degree of benignity or malignancy) to the output diagnosis, beside the simplicity of the diagnosis system, which means that the system is human interpretable.

Badr, A., and others, A fuzzy-membrane-immune algorithm for Breast cancer diagnosis, : Studia univ. Babes{\c{}}–bolyai, informatica, 2012. Abstract
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AbouNasser, H., G.Selim, and A.Badr, "A fuzzy-Immune Algorithm for Autonomous Robot Navigation", Computing and Information Systems Journal, 2007.
Shemis, E., G. F. Elhady, A. Mohammed, and A. Keshk, "A Fuzzy-Crisp Frequent Concept Lattice Generation Algorithm", 2022 2nd International Mobile, Intelligent, and Ubiquitous Computing Conference (MIUCC), pp. 75-80, 2022. Abstract
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Besheer, A. H., H. M. Emara, and M. M. Abdel Aziz, "Fuzzy-based output-feedback H∞ control for uncertain nonlinear systems: an LMI approach", IET Control Theory & Applications, vol. 1, no. 4: IET, pp. 1176–1185, 2007. Abstract
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Marzouk, M., and R. A., "Fuzzy-Based Methodology for Risk Assessment in Water Treatment Plants", Journal of Performance of Constructed Facilities, vol. 32, issue 1, pp. 04017129, 2018.
Marzouk, M., and A. Osama, "Fuzzy-Based Methodology for Integrated Infrastructure Asset Management", International Journal of Computational Intelligence Systems , vol. 10, pp. 745–759, 2017.
Gadallah, A. M., and A. H. Mohammed, "Fuzzy-Based Approach for Reducing the Impacts of Climate Changes on Agricultural Crops", : Handbook of Research on Machine Learning Innovations and Trends: IGI Global, 2017. -fuzzy-based-approach-for-reducing-the-impacts-of-climate-changes-on-agricultural-crops.pdf
Alsawy, A. A., and H. A. Hefny, "Fuzzy-based ant colony optimization algorithm", Computer Technology and Development (ICCTD), 2010.
Fathy, C., M. T. El-Hadidi, and M. Abou El-Nasr, "Fuzzy-based Adaptive Cross Layer Routing Protocol for Mobile Ad hoc Networks", 30th IEEE International Performance Computing and Communications Conference (IPCCC2011), Orlando (USA), pp. 1-2, 17 - 19 November, 2011. Abstract

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Fathy, C., M. T. El-Hadidi, and M. A. El-Nasr, "Fuzzy-based Adaptive Cross layer Routing Protocol for Delay Sensitive Applications in MANET", Communications (ICC), 2012 IEEE International Conference on, pp. 248-253, June, 2012. Abstract
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H.bouNasser, G.Selim, and A.Badr, "A fuzzy-ACO Algorithm for Autonomous Robot Navigation", Computing and Information Systems Journal, 2007.
Gabr, H. A., and E. E. Hemayed, "A Fuzzy Type—1 Facial Recognition System", CiT, vol. 3, no. 8, 2011. Abstract
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Gabr, H., and E. E. Hemayed, "A Fuzzy Type-2 Facial Recognition System", Wulfenia Journal, vol. 19, no. 10, pp. 121–135, 2012. Abstract
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Yones, S. A., and A. S. Moussa, "A fuzzy tumor volume estimation approach based on fuzzy segmentation of MR images", World Academy of Science, Engineering and Technology, vol. 71, pp. 720–5, 2012. Abstract
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A.Yones, S., and A. S. Moussa, "A Fuzzy Tumor Volume Estimation Approach Based on Fuzzy Segmentation of MR Images ", International Conference on Bioinformatics, Computational Biology and Biomedical Engineering, Venice, 11 2012. v71-122.pdf
Abd-Elaal, A. K., H. A. Hefny, and A. H. Abd-Elwahab, "Fuzzy time series model for Egypt Gold Reserves forecasting based on fuzzy clustering", International Conference on Computer Engineering & Systems (ICCES), 2011.
Mohammed, A. H., A. G. M. Allah, and H. Hefny, "Fuzzy time series approach for optimizing crops planting dates with climate changes", Computer Engineering Conference (ICENCO), 2014 10th International, Giza, 29-30 Dec. 2014. Abstract

Crops plantation dates is considered one of the most important factors in the success of crops plantation process. Obviously, each crop needs suitable values of climate variables to be planted in a certain soil. In other words, a crop plantation in different soils needs different suitable values of the climate variables. Consequently, each soil has a range of suitable values of climate variables to ensure a productive and profitable plantation process for a specific crop. Unfortunately, the ongoing changes in climate variables affect mainly the suitability of planting most crops in the same soil at the same traditional dates. So, such changes in climate variables like temperature and humidity make the traditional plantation dates of some crops in a given place became not suitable. Instead, it becomes more suitable to plant at other different dates that were not suitable before. This paper presents a fuzzy set based approach for adjust crops plantation dates reflecting climate changes. The proposed approach has three main phases, one for defining a crop suitability membership functions, the second for calculating the suitability degrees of year days, and the last one for selection and optimization of most perfect plantation dates. It has been applied on the potatoes crop with temperature and humidity as climate variables in Alexandria governorate in Egypt. In consequent, the final results are presented to a set of agriculture researchers in the Agriculture Research Center (ARC) in Egypt and they admired the results.

Aboelela, M., A. M. Fetoh, and A. B. Gamal‎, "Fuzzy Speed Controllers of Combined Cycle Power Plants‎", International Journal of Innovations in Electrical Power Systems, vol. 3, issue 2, pp. 109-121, 2011. fuzzy_speed_controllers_paper.pdf
Aboeleela, M., A. Fetoh, and A. B. Gamal, "Fuzzy Speed Controllers of Combined Cycle Power Plants", International Journal of Innovations in Electrical Power Systems, 2011. Abstract

This paper is focused on the implementation of fuzzy logic controllers and a combination between fuzzy logic control and proportional control to control the speed of a combined cycle electric power plant (CCPP). The system is simulated using Matlab/ Simulink and the fuzzy controller is implemented as a box in the simulation. Different types of the fuzzy controller have been tried in order to obtain the required speed response which achieves certain transient and steady state behavior.

Emara, S. M., A. M. Badawi, and A. - B. M. Youssef, "Fuzzy similarity measures for ultrasound tissue characterization [2424-54]", PROCEEDINGS-SPIE THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING: SPIE INTERNATIONAL SOCIETY FOR OPTICAL, pp. 556–556, 1995. Abstract
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Emara, S. M., A. M. Badawi, and A. - B. M. Youssef, "Fuzzy similarity measures for ultrasound tissue characterization", Proceedings of Nonlinear Image Processing SPIE, vol. 2424, pp. 556–566, 1995. Abstract
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