AIMC Topic: Problem Solving

Clear Filters Showing 31 to 40 of 146 articles

Machine Learning-Based Anomaly Detection in NFV: A Comprehensive Survey.

Sensors (Basel, Switzerland)
Network function virtualization (NFV) is a rapidly growing technology that enables the virtualization of traditional network hardware components, offering benefits such as cost reduction, increased flexibility, and efficient resource utilization. Mor...

An accelerated end-to-end method for solving routing problems.

Neural networks : the official journal of the International Neural Network Society
The application of neural network models to solve combinatorial optimization has recently drawn much attention and shown promising results in dealing with similar problems, like Travelling Salesman Problem. The neural network allows to learn solution...

Variable Binding for Sparse Distributed Representations: Theory and Applications.

IEEE transactions on neural networks and learning systems
Variable binding is a cornerstone of symbolic reasoning and cognition. But how binding can be implemented in connectionist models has puzzled neuroscientists, cognitive psychologists, and neural network researchers for many decades. One type of conne...

Solving time delay fractional optimal control problems via a Gudermannian neural network and convergence results.

Network (Bristol, England)
In this paper, we propose a Gudermannian neural network scheme to solve optimal control problems of fractional-order system with delays in state and control. The fractional derivative is described in the Caputo sense. The problem is first transformed...

Computational Thinking Training and Deep Learning Evaluation Model Construction Based on Scratch Modular Programming Course.

Computational intelligence and neuroscience
To improve the algorithmic dimension, critical thinking, and problem-solving ability of computational thinking (CT) in students' programming courses, first, a programming teaching model is constructed based on the scratch modular programming course. ...

Interaction with Industrial Digital Twin Using Neuro-Symbolic Reasoning.

Sensors (Basel, Switzerland)
Digital twins have revolutionized manufacturing and maintenance, allowing us to interact with virtual yet realistic representations of the physical world in simulations to identify potential problems or opportunities for improvement. However, traditi...

DR.BENCH: Diagnostic Reasoning Benchmark for Clinical Natural Language Processing.

Journal of biomedical informatics
The meaningful use of electronic health records (EHR) continues to progress in the digital era with clinical decision support systems augmented by artificial intelligence. A priority in improving provider experience is to overcome information overloa...

Emulating future neurotechnology using magic.

Consciousness and cognition
Recent developments in neuroscience and artificial intelligence have allowed machines to decode mental processes with growing accuracy. Neuroethicists have speculated that perfecting these technologies may result in reactions ranging from an invasion...

Self-regulated learning and the future of diagnostic reasoning education.

Diagnosis (Berlin, Germany)
Diagnostic reasoning is a foundational ability of health professionals. The goal of enhancing clinical reasoning education is improved diagnostic accuracy and reduced diagnostic error. In order to do so, health professions educators need not only hel...

On a Finitely Activated Terminal RNN Approach to Time-Variant Problem Solving.

IEEE transactions on neural networks and learning systems
This article concerns with terminal recurrent neural network (RNN) models for time-variant computing, featuring finite-valued activation functions (AFs), and finite-time convergence of error variables. Terminal RNNs stand for specific models that adm...