Results 121 to 130 of about 20,360 (272)

Lifecycle‐Based Governance to Build Reliable Ethical AI Systems

Systems Research and Behavioral Science, EarlyView.
ABSTRACT Artificial intelligence (AI) systems represent a paradigm shift in technological capabilities, offering transformative potential across industries while introducing novel governance and implementation challenges. This paper presents a comprehensive framework for understanding AI systems through three critical dimensions: trustworthiness ...
Maikel Leon
wiley   +1 more source

Phylogeny, species delimitation and machine learning bridge the gap between DNA sequences and morphology in the lichen genus Arctomia (Arctomiaceae, Ascomycota)

TAXON, EarlyView.
Abstract This study investigates species boundaries in the lichen genus Arctomia (Arctomiaceae, Ascomycota) using an integrative approach combining molecular phylogenetics, full Bayesian population delimitation, heuristic and model‐based species delimitation, and supervised machine learning applied to morphological data.
Stefan Ekman, Måns Svensson, Martin Westberg   +2 more
wiley   +1 more source

A machine learning-based selection approach for solving the single machine scheduling problem with Early/Tardy jobs

BizInfo
Today, the algorithm selection paradigm has become one of the promising approaches in the field of optimization problems. Its main goal is to solve each case of an optimization problem with the most accurate algorithm using machine learning techniques ...
Ahmed Adnane Abdessemed, Leila Hayet Mouss, Khaled Benaggoune, Toufik Bentrcia   +3 more
doaj   +1 more source

Feasibility restoration for iterative meta-heuristics search algorithms [PDF]

, 2002
Randall, Marcus
core   +1 more source

Data privacy model using blockchain reinforcement federated learning approach for scalable internet of medical things

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract Internet of Medical Things (IoMT) has typical advancements in the healthcare sector with rapid potential proof for decentralised communication systems that have been applied for collecting and monitoring COVID‐19 patient data. Machine Learning algorithms typically use the risk score of each patient based on risk factors, which could help ...
Chandramohan Dhasaratha, Mohammad Kamrul Hasan, Shayla Islam, Shailesh Khapre, Salwani Abdullah, Taher M. Ghazal, Ahmed Ibrahim Alzahrani, Nasser Alalwan, Nguyen Vo, Md Akhtaruzzaman   +9 more
wiley   +1 more source

Deviation‐Guided Attention for Semi‐Supervised Anomaly Detection With Contrastive Regularisation

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Anomaly detection (AD) aims to identify abnormal patterns that deviate from normal behaviour, playing a critical role in applications such as industrial inspection, medical imaging and autonomous driving. However, AD often faces a scarcity of labelled data. To address this challenge, we propose a novel semi‐supervised anomaly detection method,
Guanglei Xie, Xiaochang Hu, Yi Sun, Wenzhuo Zhang, Yafeng Bu, Hao Fu, Xin Xu   +6 more
wiley   +1 more source

Coevolutionary Neural Dynamics With Learnable Parameters for Nonconvex Optimisation

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Nonconvex optimisation plays a crucial role in science and industry. However, existing methods often encounter local optima or provide inferior solutions when solving nonconvex optimisation problems, lacking robustness in noise scenarios. To address these limitations, we aim to develop a robust, efficient and globally convergent solver for ...
Yipiao Chen, Wenbin Du, Huichao Cao, Long Jin   +3 more
wiley   +1 more source

A Universal Meta‐Heuristic Framework for Influence Maximisation in Hypergraphs

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Influence maximisation (IM) aims to select a small number of nodes that are able to maximise their influence in a network and covers a wide range of applications. Despite numerous attempts to provide effective solutions in simple networks, higher‐order interactions between entities in various real‐world systems are usually not taken into ...
Ming Xie, Chuang Liu, Yang Chen, Zi‐Ke Zhang, Xiaoyang Liu, Xiu‐Xiu Zhan   +5 more
wiley   +1 more source

Building Blocks as Experiences in Dynamic Capacitated Arc Routing Problems

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT The dynamic capacitated arc routing problem (DCARP) aims to update the service paths of vehicles in the capacitated arc routing problem when uncertain factors deteriorate the current schedule of vehicles' services. A DCARP scenario comprises a series of DCARP instances that share similarities with each other. Therefore, optimisation experience
Hao Tong, Leandro L. Minku, Stefan Menzel, Bernhard Sendhoff, Xin Yao   +4 more
wiley   +1 more source

EFFICIENCY OF SELECTED META-HEURISTICS APPLIED TO THE TSP PROBLEM: A SIMULATION STUDY

TASK Quarterly, 2003
The paper presents a simulation study of the usefulness of a number of meta-heuristics used as optimisation methods for TSP problems. The five considered approaches are outlined: Genetic Algorithm, Simulated Annealing, Ant Colony System, Tabu Search and
HALINA KWAŚNICKA
doaj