Post-Quantum Encryption for Mathematical Model Using Quantum Machine Learning Approach

Because of the increasing emphasis put on the aviation industry in as a main industry of the global transportation industry, a number of organizations depend on different flight companies to get in touch with parts of the world which may be an effective measure to control the disease from spreading to other areas of the world. However, severe conditions can actually influence airline services in a given area of operation most significantly, flight delays. In this case, service encounters took place between the airline as a large organizational sector and the individual traveling as customers. The working for this issue is to accurately expect such flight delays though enables enhanced performers while in travel in order to be fit for destinations. Disability which will be occasioned by the existence of the aforementioned impediment. Quantum machine learning is used to examine the measures that were used in building models to analyze probability of flights. Problems associated with late and early arrival and; Delays due to unfavorable weather conditions. In the initial the process of project management, in which at the planned stage of the work, we study the feasibility of integration of Support Vector Machine with Python-based linear Regression.