Abstract: In complex networks, predicting the formation of new connections, or links, within complex networks has been a central challenge, traditionally addressed using graph-based models. These ...

Abstract: In this paper, an optimization algorithm based on deep reinforcement learning is proposed to optimize complex networks in fixed-time convergence of continuous action iteration dilemmas. The ...

Learn how Network in Network (NiN) architectures work and how to implement them using PyTorch. This tutorial covers the concept, benefits, and step-by-step coding examples to help you build better ...

ABSTRACT: This paper investigates the application of machine learning techniques to optimize complex spray-drying operations in manufacturing environments. Using a mixed-methods approach that combines ...

Whenever we mull over what film to watch on Netflix, or deliberate between different products on an e-commerce platform, the gears of recommendation algorithms spin under the hood. These systems sort ...

Though introduced recently, complex networks research has grown steadily because of its potential to represent, characterize and model a wide range of intricate natural systems and phenomena. Because ...

Background: This study employs a network analysis approach to explore the interconnections between anxiety, depression, and sleep problems and smartphone addiction among college students using network ...

In many ways, networking is a mature, stable industry, based on established technologies like Wi-Fi and Ethernet, which just celebrated its 50th anniversary. But networking vendors are constantly ...

Introduction: As China continues to develop the advanced power systems, the network structure of distribution networks is becoming increasingly complex. The integration of numerous power electronic ...

In order to uncover the relationship between structure and function, researchers used microfluidic devices to study neuronal networks. Uncovering the relationship between structure (connectivity) and ...