Call for Papers – Knowledge-infused System for Intelligent Ocean Applications

A PeerJ Computer Science Special Issue aiming to advance emerging technologies related to Intelligent Ocean Applications

“Intelligent ocean applications are less mature than terrestrial counterparts, generally with fewer technical advances, due to the difficulty in analysing and overcoming chaotic ocean environments” – Jiachen Yang, Professor, Tianjin University.

Intelligent ocean applications involve the fusion of artificial intelligence techniques with various fields including engineering, physics, geo-science, chemistry and biology. This integration aims to develop groundbreaking solutions that offer substantial practical advantages. However, current intelligent ocean systems face numerous challenges. These challenges include the integration and harmonization of diverse disciplines, the representation and fusion of multidisciplinary knowledge, the assurance of data quality, and the achievement of interpretability and comprehensibility.

“Intelligent ocean applications are expected to effectively manage and process vast quantities of data, accurately forecast oceanic conditions and weather patterns, as well as enable the autonomous programming of underwater devices“. Qinggang Meng, Professor, Loughborough University

In response to the aforementioned challenges, the knowledge-infused system emerges as an effective solution. The knowledge-infused system is a machine learning model that integrates domain-specific knowledge into its architecture or training process. The purpose of a knowledge-infused system is to harness expert knowledge and emphasize the most pertinent features or instances during the learning process, to attain multidisciplinary coordination, effective expression, interpretability, and high-confidence outcomes.

“A knowledge injection system refers to a machine learning model that incorporates domain-specific knowledge into both its architecture and training process, making a significant contribution to the advancement of emerging technologies“. Muhammad Khurram Khan, Professor, King Saud University

This special issue aims to advance emerging technologies in relevant fields, creating a more trustworthy, intelligent, and sustainable environment for the future generation of intelligent ocean applications.

To find out more, and to submit your abstract, see: peerj.com/special-issues/136-intelligent-ocean-applications