إطار عمل للاستفادة من الذكاء الاصطناعي في تحسين ممارسات التصميم الصناعي

1.  Abduljabbar, Rusul & Dia, Hussein & Liyanage, Sohani & Bagloee, Saeed. (2019). Applications of Artificial Intelligence in Transport: An Overview. Sustainability. 11. 189. 10.3390/su11010189.
2. Bose, Bimal. (2017). Artificial Intelligence Techniques in Smart Grid and Renewable Energy Systems—Some Example Applications. Proceedings of the IEEE. 105. 2262-2273. 10.1109/JPROC.2017.2756596.
3. E. Brynjolfsson, A. Mcafee. (2017). The business of artificial intelligence, Harv. Bus. Rev. 3–11.
4. Cai, Hongming & Xu, Lida & Xu, Boyi & Zhang, Pengzhu & Guo, Jingzhi & Zhang, Yuran. (2018). A service governance mechanism based on process mining for cloud-based applications. Enterprise Information Systems. 12. 1-18. 10.1080/17517575.2018.1442933.
5. Caramelo Gomes, Cristina & Preto, Sandra. (2018). Artificial Intelligence and Interaction Design for a Positive Emotional User Experience. 10.1007/978-3-319-73888-8_11.
6. Cappelli, Peter & Tambe, Prasanna & Yakubovich, Valery. (2018). Artificial Intelligence in Human Resources Management: Challenges and a Path Forward. SSRN Electronic Journal. 10.2139/ssrn.3263878.
7. Chen, Hong & Li, Ling & Chen, Yong. (2020). Explore success factors that impact artificial intelligence adoption on telecom industry in China. Journal of Management Analytics. 8. 1-33. 10.1080/23270012.2020.1852895.
8. Chen, Liuqing & Wang, Panny & Dong, Hao & Shi, Feng & Han, Ji & Guo, Yike & Childs, Peter & Xiao, Jun & Wu, Chao. (2019). An artificial intelligence-based data-driven approach for design ideation. Journal of Visual Communication and Image Representation. 61. 10.1016/j.jvcir.2019.02.009.
9. Chen, Xue-Wen & Lin, Xiaotong. (2014). Big Data Deep Learning: Challenges and Perspectives. Access, IEEE. 2. 514-525. 10.1109/ACCESS.2014.2325029.
10. Duan, Lian & Xu, Li. (2012). Business Intelligence for Enterprise Systems: A Survey. Industrial Informatics, IEEE Transactions on. 8. 679-687. 10.1109/TII.2012.2188804..
11. Duan, Na & Liu, Lizheng & Yu, Xianjia & L., Qingqing & Yeh, Shih-Ching. (2018). Classification of multichannel surface-electromyography signals based on convolutional neural networks. Journal of Industrial Information Integration. 15. 10.1016/j.jii.2018.09.001.
12. Erhan, Dumitru & Courville, Aaron & Bengio, Y. & Vincent, Pascal. (2010). Why Does Unsupervised Pre-training Help Deep Learning?. Journal of Machine Learning Research - Proceedings Track. 9. 201-208.
13. Hu, Shisheng & Liang, Ying-Chang & Xiong, Zehui & Niyato, Dusit. (2021).Blockchain and Artificial Intelligence for Dynamic Resource Sharing in 6G and Beyond. IEEE Wireless Communications. PP. 1-7. 10.1109/MWC.001.2000409.
14. Guo, Taiyuan & Eckert, Roland & Li, Mei. (2020). Application of Big Data and Artificial Intelligence Technology in Industrial Design. International Journal of Advanced Trends in Computer Science and Engineering. Vol 5. 10-14.
15. Iansiti, M., and K. Lakhani. 2020a. Competing in the age of artificial intelligence. Cambridge, MA: Harvard Business Press.
16. Kasture, Pranjali & Gadge, Jayant. (2012). Cluster based Outlier Detection. International Journal of Computer Applications. 58. 10.5120/9317-3549.
17. Khan, Abid & Sheikh, Shakil & Chaudhry, Imran Ali & Hussain, Tanweer. (2003). Artificial Intelligence Techniques in Engineering Design Synthesis. Engineering Horizons. 7 - 12.
18. Lakhani, Karim & Iansiti, Marco. (2020). Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World.
19. Le, Tan & Hu, Rose & Hanzo, L.. (2019). Twin-Timescale Artificial Intelligence Aided Mobility-Aware Edge Caching and Computing in Vehicular Networks. IEEE Transactions on Vehicular Technology. PP. 10.1109/TVT.2019.2893898.
20. Liao, Jing & Hansen, Preben & Chai, Chunlei. (2020). A framework of artificial intelligence augmented design support. Human-Computer Interaction. 35. 1-34. 10.1080/07370024.2020.1733576.
21. Liedtka, J. 2015. Perspective: Linking design thinking with innovation outcomes through cognitive bias reduction. Journal of Product Innovation Management 32 (6): 925–38.
22. Li, Lynn. (2000). Knowledge-based problem solving: an approach to health assessment. : Expert Systems with Applications 16(1) (1999) 33–42. Expert Systems with Applications. 18. 153.
23. Li, Lynn. (2002). Proposing an architectural framework of hybrid knowledge-based system for production rescheduling. Expert Systems. 16. 273 - 279. 10.1111/1468-0394.00119.
24. Li, Hongxing & Li, L.X. (2002). Representing diverse mathematical problems using neural networks in hybrid intelligent systems. Expert Systems. 16. 262 - 272. 10.1111/1468-0394.00118.
25. Liedtka, Jeanne. (2014). Perspective: Linking Design Thinking with Innovation Outcomes through Cognitive Bias Reduction. Journal of Product Innovation Management. 32. 10.1111/jpim.12163.
26. Liu, Li & Ouyang, Wanli & Wang, Xiaogang & Fieguth, Paul & Chen, Jie & Liu, Xinwang & Pietikäinen, Matti. (2020). Deep Learning for Generic Object Detection: A Survey. International Journal of Computer Vision. 128. 10.1007/s11263-019-01247-4.
27. Liu, Jiaying & Kong, Xiangjie & Xia, Feng & Bai, Xiaomei & Wang, Lei & Qing, Qing & Lee, Ivan. (2018). Artificial Intelligence in the 21st Century. IEEE Access. PP. 1-1. 10.1109/ACCESS.2018.2819688.
28. G. Litjens, T. Kooi, B.E. Bejnordi, A.A.A. Setio, F. Ciompi, M. Ghafoorian, J.A. Van Der Laak, B. Van Ginneken, C.I S´anchez, (2017). A survey on deep learning in medical image analysis, Med. Image Anal. 42,p 60–88
29. Liu, Ziwei & Luo, Ping & Wang, Xiaogang & Tang, Xiaoou. (2014). Deep Learning Face Attributes in the Wild. 10.1109/ICCV.2015.425.
30. Lu, Lifei & Xu, Lida & Xu, Boyi & Li, Guoqiang & Cai, Hongming. (2018). Fog Computing Approach for Music Cognition System Based on Machine Learning Algorithm. IEEE Transactions on Computational Social Systems. PP. 1-10. 10.1109/TCSS.2018.2871694.
31. Miotto, Riccardo & Wang, Fei & Wang, Shuang & Jiang, Xiaoqian. (2017). Deep learning for healthcare: review, opportunities and challenges. Briefings in bioinformatics. 19. 10.1093/bib/bbx044.
32. Moreira da Silva, A. (2018). Will Sketching Survive with the Use of Artificial Intelligence Tools?. In: Karwowski, W., Ahram, T. (eds) Intelligent Human Systems Integration. IHSI 2018. Advances in Intelligent Systems and Computing, vol 722. Springer, Cham. https://doi.org/10.1007/978-3-319-73888-8_48.
33. Morocho-Cayamcela, Manuel Eugenio & Lim, Wansu. (2018). Artificial Intelligence in 5G Technology: A Survey. 860-865. 10.1109/ICTC.2018.8539642.
34. Reddy, Mr & Naik, N. & Prashanth, A. & Kumar, B.. (2022). An Efficient Spam Detection Technique for IoT Devices Using Machine Learning. International Journal for Research in Applied Science and Engineering Technology. 10. 1001-1005. 10.22214/ijraset.2022.42311.
35. Reichstein, Markus & Camps-Valls, Gustau & Stevens, Bjorn & Jung, Martin & Denzler, Joachim & Carvalhais, Nuno & Prabhat, Mr. (2019). Deep learning and process understanding for data-driven Earth system science. Nature. 566. 195. 10.1038/s41586-019-0912-1.
36. Schliferstein, A.. (1981). Principles of artificial intelligence. Proceedings of the IEEE. 69. 1171- 1172. 10.1109/PROC.1981.12145.
37. Shone, Nathan & Tran Nguyen, Ngoc & Vu Dinh, Phai & Shi, Qi. (2018). A Deep Learning Approach to Network Intrusion Detection. IEEE Transactions on Emerging Topics in Computational Intelligence. 2. 41-50. 10.1109/TETCI.2017.2772792.
38. Simon, H. A. 1982. The sciences of the artificial. Cambridge, MA: The MIT Press.
39. Simon, H. (1982) Models of Bounded Rationality: Behavioral Economics and Business Organization. Vol. 2, MIT Press, Cambridge, MA.
40. Sohn, Kwonsang & Kwon, Ohbyung. (2020). Technology Acceptance Theories and Factors Influencing Artificial Intelligence-based Intelligent Products. Telematics and Informatics. 101324.
41. Sodhro, Ali & Pirbhulal, Sandeep & Albuquerque, V.H.C.. (2019). Artificial Intelligence-Driven Mechanism for Edge Computing-Based Industrial Applications. IEEE Transactions on Industrial Informatics. PP. 1-1. 10.1109/TII.2019.2902878.
42. Sünderhauf, Niko & Brock, Oliver & Scheirer, Walter & Hadsell, Raia & Fox, Dieter & Leitner, Juxi & Upcroft, Ben & Abbeel, Pieter & Burgard, Wolfram & Milford, Michael & Corke, Peter. (2018). The Limits and Potentials of Deep Learning for Robotics. The International Journal of Robotics Research. 37. 10.1177/0278364918770733.
43. S. Tokui, K. Oono, S. Hido, J. Clayton, (2015). Chainer: a next-generation open source framework for deep learning, Proceedings of workshop on machine learning systems (LearningSys) in the twenty-ninth annual conference on neural information processing systems (NIPS) 5 ,1–6.
44. Tan, Wenan & Xu, Yicheng & Xu, Wei & Xu, Lida & Zhao, Xianhua & Wang, li & Fu, Liuliu. (2010). A methodology toward manufacturing grid-based virtual enterprise operation platform. Enterprise IS. 4. 283-309. 10.1080/17517575.2010.504888.
45. Verganti, Roberto & Vendraminelli, Luca & Iansiti, Marco. (2020). Innovation and Design in the Age of Artificial Intelligence. Journal of Product Innovation Management. 37. 10.1111/jpim.12523.
46. Xu, Li. (1999).Preface, Expert Syst. Appl. 16 (1) 1–2
47. Xu, Li. (2013). Introduction: Systems Science in Industrial Sectors. Systems Research and Behavioral Science. 30. 10.1002/sres.2186.
48. Xu, Li & Lu, Yang & Li, Ling. (2021). Embedding Blockchain Technology Into IoT for Security: A Survey. IEEE Internet of Things Journal. PP. 1-1. 10.1109/JIOT.2021.3060508.
49. Yang, Baoan & Li, Ling & Ji, Hai & Xu, Jing. (2001). An early warning system for loan risk assessment using artificial neural networks. Knowl.-Based Syst.. 14. 303-306. 10.1016/S0950-7051(01)00110-1.
50. Yang, Geng & Xie, Li & Mäntysalo, Matti & Zhou, Xiaolin & Pang, Zhibo & Xu, Li & Kao-Walter, Sharon & Chen, Qiang & Zheng, Li-Rong. (2014). A Health-IoT Platform Based on the Integration of Intelligent Packaging, Unobtrusive Bio-Sensor and Intelligent Medicine Box. IEEE Transactions on Industrial Informatics. 10. 1-1. 10.1109/TII.2014.2307795.
51. Yang, Honghong & Wen, Jinming & Wu, Xiao-Jun & He, Li & Mumtaz, Shahid. (2019). An Efficient Edge Artificial Intelligence MultiPedestrian Tracking Method With Rank Constraint. IEEE Transactions on Industrial Informatics. PP. 1-1. 10.1109/TII.2019.2897128.
52. Young, Tom & Hazarika, Devamanyu & Poria, Soujanya & Cambria, Erik. (2017). Recent Trends in Deep Learning Based Natural Language Processing.
53. A. Zappone, M. Di Renzo, M. Debbah, (2019) Wireless networks design in the era of deep learning: model-based, AI-based, or both? IEEE Trans. Commun. 67 (10( 7331–7376
54. Zhang, Caiming & Chen, Yong. (2019). A Review of Research Relevant to the Emerging Industry Trends: Industry 4.0, IoT, Block Chain, and Business Analytics. Journal of Industrial Integration and Management. 05. 10.1142/S2424862219500192.
55. Zhang, Caiming & Xu, Xiaojun & Chen, Hong. (2019). Theoretical foundations and applications of cyber-physical systems: a literature review. Library Hi Tech. ahead-of-print. 10.1108/LHT-11-2017-0230.
56. Zhang, Caiming. (2020). Research on the Economical Influence of the Difference of Regional Logistics Developing Level in China. Journal of Industrial Integration and Management. 05. 10.1142/S2424862220500049.
57. Zhang, Caiming & Lu, Yang. (2021). Study on Artificial Intelligence: The State of the Art and Future Prospects. Journal of Industrial Information Integration. 23. 100224. 10.1016/j.jii.2021.100224.
58. Zhang, Weiqiang & Xiang, Yidan & Liu, Xiaohui & Zhang, Pengzhu. (2019). Domain ontology development of knowledge base in cardiovascular personalized health management. Journal of Management Analytics. 6. 420-455. 10.1080/23270012.2019.1694454.

Zeng, Li & Li, Ling & Duan, Lian. (2012). Business intelligence in enterprise computing environment. Information Technology and Management. 13. 10.1007/s10799-012-0123-z