A framework of Optimization using Machine Learning and Deep Learning Algorithms

Abstract

The Evolutionary algorithm detects the top problem solution provided by the natural testing process, which is used to solve the problem of multiple optimizations on the computer edge. The machine learning algorithm is employed to handle the most arduous challenges by consistently building a model from observation (reinforcement learning) or training data. Evolutionary algorithm as a genetic algorithm can solve a number of end-to-end computer research issues such as job planning. Machine learning method transforms the computer development problem at the edges into partitions or retreats or problems to make smarter decisions and solve, for example, the right download decision. Advanced Reading can be used without predefined data with a traffic forecasting label, which can be used for resource allocation and uploading. This paper focuses on Machine Learning, Edge Computing, Research Challenges, Mathematical Models and Applications.