IEEE

A fast and elitist multiobjective genetic algorithm: NSGA-II

Abstract: Multi-objective evolutionary algorithms (MOEAs) that use non-dominated sorting and sharing have been criticized mainly for: (1) their O(MN/sup 3/) computational complexity (where M is the ...
jme.bmj

Who is afraid of black box algorithms? On the epistemological and ethical basis of trust in medical AI

The use of black box algorithms in medicine has raised scholarly concerns due to their opaqueness and lack of trustworthiness. Concerns about potential bias, accountability and responsibility, patient ...
IEEE

A Survey of Clustering Algorithms for Big Data: Taxonomy and Empirical Analysis

Abstract: Clustering algorithms have emerged as an alternative powerful meta-learning tool to accurately analyze the massive volume of data generated by modern applications. In particular, their main ...
IEEE

An Evolutionary Algorithm for Solving Large-Scale Robust Multiobjective Optimization Problems

Abstract: Robust multiobjective optimization problems (RMOPs) widely exist in real-world applications, which introduce a variety of uncertainty in optimization models. While some evolutionary ...
IEEE

A Comprehensive Survey of Path Planning Algorithms for Autonomous Systems and Mobile Robots: Traditional and Modern Approaches

Abstract: Path planning is a crucial component for robotics and autonomous systems, which facilitate navigation through dynamic and uncertain environments while avoiding obstacles. This review paper ...
IEEE

A Comprehensive Survey on Delaunay Triangulation: Applications, Algorithms, and Implementations Over CPUs, GPUs, and FPGAs

Abstract: Delaunay triangulation is an effective way to build a triangulation of a cloud of points, i.e., a partitioning of the points into simplices (triangles in 2D, tetrahedra in 3D, and so on), ...
IEEE

Deep Learning for Credit Card Fraud Detection: A Review of Algorithms, Challenges, and Solutions

Abstract: Deep learning (DL), a branch of machine learning (ML), is the core technology in today’s technological advancements and innovations. Deep learning-based approaches are the state-of-the-art ...
IEEE

Two-Archive Evolutionary Algorithm for Constrained Multiobjective Optimization

When solving constrained multiobjective optimization problems, an important issue is how to balance convergence, diversity, and feasibility simultaneously. To address this issue, this paper proposes a ...
IEEE

Deep Reinforcement Learning Based Optimization Algorithm for Permutation Flow-Shop Scheduling

Abstract: As a new analogy paradigm of human learning process, reinforcement learning (RL) has become an emerging topic in computational intelligence (CI). The synergy between the RL and CI is an ...
IEEE

Lightweight Cryptography Algorithms for Resource-Constrained IoT Devices: A Review, Comparison and Research Opportunities

Abstract: IoT is becoming more common and popular due to its wide range of applications in various domains. They collect data from the real environment and transfer it over the networks. There are ...
IEEE

A Comprehensive Review of Recent Advances on Intelligence Algorithms and Information Engineering Applications

Abstract: The advent of artificial intelligence (AI) has catalyzed transformative changes across diverse domains, establishing itself as a disruptive technology. Traditional methods often fall short ...