Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep ...

This toolbox offers more than 40 wrapper feature selection methods include PSO, GA, DE, ACO, GSA, and etc. They are simple and easy to implement.

Robot applications encompass a multitude of edge computing tasks, such as image processing, health monitoring, path planning, and infotainment. However, task scheduling within such environments ...

Abstract: With the development of the manufacturing industry towards high quality and customized production, the flexible job shop scheduling problem has become an important issue for optimizing ...

Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu 610054, China Department of Computer Science, Abdul Wali Khan University Mardan, ...

Abstract: This paper proposes a hybrid algorithm based on genetic algorithm combined with improved Aquila Optimizer (IAO-GA) to solve the flexible job shop scheduling problem (F JSP). This paper ...

A current remarkable technique is based on artificial intelligence algorithms (Hamet and Tremblay, 2017). The increasing abundance of clinical, genetic, radiological and metabolic data in ...

Proteogenomics explores how genetic information translates into protein expression and function, and the role of changes across DNA, RNA, and proteins in influencing disease development and ...