Results 21 to 30 of about 1,929 (230)

Particle swarm optimisation for outlier detection [PDF]

Proceedings of the 12th annual conference on Genetic and evolutionary computation, 2010
Outlier detection is an important problem as the underlying data points often contain crucial information, but identifying such points has multiple challenges, e.g. noisy data, imprecise boundaries and lack of training examples. In the novel approach presented in this paper, the outlier detection problem is converted into an optimisation problem.
Mohemmed, Ammar W., Zhang, Mengjie, Browne, Will N.   +2 more
openaire   +2 more sources

A Novel Swarm Optimisation Algorithm Based on a Mixed-Distribution Model

Applied Sciences, 2018
Many swarm intelligence optimisation algorithms have been inspired by the collective behaviour of natural and artificial, decentralised, self-organised systems.
Xiaoming Zhang, Tinghao Feng, Qingsong Niu, Xijin Deng   +3 more
doaj   +1 more source

Frequency optimisation of composite cylinder using an evolutionary algorithm and neural networks [PDF]

MATEC Web of Conferences, 2019
The paper deals with the optimisation of dynamic properties of a composite cantilever cylinder. The optimised parameters are both the fundamental natural frequency f1 as well as the gap in frequency space around a selected external excitation force ...
Miller Bartosz, Ziemiański Leonard
doaj   +1 more source

An efficient spotted hyena optimization based network log intrusions in massive server infrastructure [PDF]

Yugoslav Journal of Operations Research
With advancement of information technology, intrusion is becoming more common in the internet era. The increased use of cloud services have also resulted in assaults on servers.
Rajalingam R., Kavitha K.
doaj   +1 more source

Hybrid self-inertia weight adaptive particle swarm optimisation with local search using C4.5 decision tree classifier for feature selection problems

Connection Science, 2020
Feature selection is an important task to improve the classifier’s accuracy and to decrease the problem size. A number of methodologies have been presented for feature selection problems using metaheuristic algorithms.
Arfan Ali Nagra, Fei Han, Qing Hua Ling, Muhammad Abubaker, Farooq Ahmad, Sumet Mehta, Abeo Timothy Apasiba   +6 more
doaj   +1 more source

Source Localisation Using Wavefield Correlation-Enhanced Particle Swarm Optimisation

Robotics, 2022
Particle swarm optimisation (PSO) is a swarm intelligence algorithm used for controlling robotic swarms in applications such as source localisation. However, conventional PSO algorithms consider only the intensity of the received signal.
George Rossides, Alan Hunter, Benjamin Metcalfe   +2 more
doaj   +1 more source

Novelty-Driven Binary Particle Swarm Optimisation for Truss Optimisation Problems

, 2022
Topology optimisation of trusses can be formulated as a combinatorial and multi-modal problem in which locating distinct optimal designs allows practitioners to choose the best design based on their preferences. Bilevel optimisation has been successfully applied to truss optimisation to consider topology and sizing in upper and lower levels ...
Hirad Assimi, Frank Neumann, Markus Wagner, Xiaodong Li   +3 more
openaire   +2 more sources

Soft Actor-Critic Approach to Self-Adaptive Particle Swarm Optimisation

Mathematics
Particle swarm optimisation (PSO) is a swarm intelligence algorithm that finds candidate solutions by iteratively updating the positions of particles in a swarm.
Daniel von Eschwege, Andries Engelbrecht
doaj   +1 more source

By dawn or dusk—how circadian timing rewrites bacterial infection outcomes

FEBS Letters, EarlyView.
The circadian clock shapes immune function, yet its influence on infection outcomes is only beginning to be understood. This review highlights how circadian timing alters host responses to the bacterial pathogens Salmonella enterica, Listeria monocytogenes, and Streptococcus pneumoniae revealing that the effectiveness of immune defense depends not only
Devons Mo, Catherine S. Palmer, Jacqueline M. Kimmey   +2 more
wiley   +1 more source

Optimisation‐based training of evolutionary convolution neural network for visual classification applications

IET Computer Vision, 2020
Training of the convolution neural network (CNN) is a problem of global optimisation. This study proposed a hybrid modified particle swarm optimisation (MPSO) and conjugate gradient (CG) algorithm for efficient training of CNN. The training involves MPSO–
Shanshan Tu, Sadaqat urRehman, Muhammad Waqas, Obaid ur Rehman, Zhongliang Yang, Basharat Ahmad, Zahid Halim, Wei Zhao   +7 more
doaj   +1 more source