Artificial neural networks based optimization techniques: A review

MGM Abdolrasol, SMS Hussain, TS Ustun, MR Sarker… - Electronics, 2021 - mdpi.com
In the last few years, intensive research has been done to enhance artificial intelligence (AI)
using optimization techniques. In this paper, we present an extensive review of artificial …

A systematic literature review on the impact of artificial intelligence on workplace outcomes: A multi-process perspective

V Pereira, E Hadjielias, M Christofi, D Vrontis - Human Resource …, 2023 - Elsevier
Artificial intelligence (AI) can bring both opportunities and challenges to human resource
management (HRM). While scholars have been examining the impact of AI on workplace …

Application of meta-heuristic algorithms for training neural networks and deep learning architectures: A comprehensive review

M Kaveh, MS Mesgari - Neural Processing Letters, 2023 - Springer
The learning process and hyper-parameter optimization of artificial neural networks (ANNs)
and deep learning (DL) architectures is considered one of the most challenging machine …

A review of deep learning with special emphasis on architectures, applications and recent trends

S Sengupta, S Basak, P Saikia, S Paul… - Knowledge-Based …, 2020 - Elsevier
Deep learning (DL) has solved a problem that a few years ago was thought to be intractable—
the automatic recognition of patterns in spatial and temporal data with an accuracy superior …

A comprehensive survey on particle swarm optimization algorithm and its applications

Y Zhang, S Wang, G Ji - Mathematical problems in engineering, 2015 - Wiley Online Library
Particle swarm optimization (PSO) is a heuristic global optimization method, proposed
originally by Kennedy and Eberhart in 1995. It is now one of the most commonly used …

Pyramid particle swarm optimization with novel strategies of competition and cooperation

T Li, J Shi, W Deng, Z Hu - Applied Soft Computing, 2022 - Elsevier
Particle swarm optimization (PSO) has shown its advantages in various optimization
problems. Topology and updating strategies are among its key concepts and have …

Application of optimized machine learning techniques for prediction of occupational accidents

S Sarkar, S Vinay, R Raj, J Maiti, P Mitra - Computers & Operations …, 2019 - Elsevier
Although, the usefulness of the machine learning (ML) technique in predicting future
outcomes has been established in different domains of applications (eg, heath care), its …

Hybrid artificial intelligence and robust optimization for a multi-objective product portfolio problem Case study: The dairy products industry

A Goli, HK Zare, R Tavakkoli-Moghaddam… - Computers & industrial …, 2019 - Elsevier
The optimization of the product portfolio problem under return uncertainty is addressed here.
The contribution of this study is based on the application of a hybrid improved artificial …

Machine learning in occupational accident analysis: A review using science mapping approach with citation network analysis

S Sarkar, J Maiti - Safety science, 2020 - Elsevier
The present study reviews the publications that examine the application of machine learning
(ML) approaches in occupational accident analysis. The review process includes four …

Intelligent computing for numerical treatment of nonlinear prey–predator models

M Umar, Z Sabir, MAZ Raja - Applied Soft Computing, 2019 - Elsevier
In this study, a new computing paradigm is presented for evaluation of dynamics of
nonlinear prey–predator mathematical model by exploiting the strengths of integrated …