Items where Author is "Sahawneh, N"

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Number of items: 9.

Ghazal, T M and Khan, Muhammad Adnan and Inairat, M and Sahawneh, N (2022) Quality Requirement Change Management’s Challenges: An Exploratory Study Using SLR. IEEE Access, 10. pp. 127575-127588. ISSN 2169-3536

Sahawneh, N (2022) Activity Based Easy Learning Of PushDown Automata. In: 2022 International Conference on Cyber Resilience (ICCR), 06-07 October 2022, Dubai, United Arab Emirates.

Alzoubi, H M and Sahawneh, N (2022) Analysis Of Cost Prediction In Medical Insurance Using Modern Regression Models. In: 2022 International Conference on Cyber Resilience (ICCR), 06-07 October 2022, Dubai, United Arab Emirates.

Sahawneh, N and Alzoubi, H M (2022) An Intelligent Approach for Predicting Bankruptcy Empowered with Machine Learning Technique. In: 2022 International Conference on Cyber Resilience (ICCR), 06-07 October 2022, Dubai, United Arab Emirates.

Sahawneh, N and Al-kassem, A H (2022) Education, Employment and Women Empowerment in an Agrarian Economy: Acase Study Note: Sub-titles are not captured in Xplore and should not be used. In: 2022 International Conference on Business Analytics for Technology and Security (ICBATS), 16-17 Feb. 2022, Dubai, United Arab Emirates.

Alzoubi, H M and Ghazal, T M and Sahawneh, N and Al-kassem, A H (2022) Fuzzy assisted human resource management for supply chain management issues. Annals of Operations Research. ISSN 0254-5330

Al-kassem, A H and Sahawneh, N and Inairat, M (2022) Is there any Impact of Money Supply and Exchange Rate on Agricultural Prices? In: 2022 International Conference on Business Analytics for Technology and Security (ICBATS), 16-17 Feb. 2022, Dubai, United Arab Emirates.

Ghazal, T M and Sahawneh, N (2022) Smart cities: Fusion-based intelligent traffic congestion control system for vehicular networks using machine learning techniques. Egyptian Informatics Journal. ISSN 11108665

Ghazal, T M and Khan, Muhammad Adnan and Sahawneh, N Smart cities:Fusion-based intelligent traffic congestion control system for vehicular networks using machine learning techniques. Egyptian Informatics Journal, 23 (3). pp. 417-426. ISSN 1110-8665

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