Multi-sensor information fusion based on machine learning for real applications in human activity recognition: State-of-the-art and research challenges
This paper firstly introduces common wearable sensors, smart wearable devices and the key
application areas. Since multi-sensor is defined by the presence of more than one model or …
application areas. Since multi-sensor is defined by the presence of more than one model or …
[HTML][HTML] Artificial neural networks based optimization techniques: A review
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 …
using optimization techniques. In this paper, we present an extensive review of artificial …
Hunger games search: Visions, conception, implementation, deep analysis, perspectives, and towards performance shifts
Y Yang, H Chen, AA Heidari, AH Gandomi - Expert Systems with …, 2021 - Elsevier
A recent set of overused population-based methods have been published in recent years.
Despite their popularity, most of them have uncertain, immature performance, partially done …
Despite their popularity, most of them have uncertain, immature performance, partially done …
[HTML][HTML] Protein nanoparticles in drug delivery: animal protein, plant proteins and protein cages, albumin nanoparticles
E Kianfar - Journal of Nanobiotechnology, 2021 - Springer
In this article, we will describe the properties of albumin and its biological functions, types of
sources that can be used to produce albumin nanoparticles, methods of producing albumin …
sources that can be used to produce albumin nanoparticles, methods of producing albumin …
Slime mould algorithm: A new method for stochastic optimization
In this paper, a new stochastic optimizer, which is called slime mould algorithm (SMA), is
proposed based on the oscillation mode of slime mould in nature. The proposed SMA has …
proposed based on the oscillation mode of slime mould in nature. The proposed SMA has …
Chaotic random spare ant colony optimization for multi-threshold image segmentation of 2D Kapur entropy
Although the continuous version of ant colony optimizer (ACOR) has been successfully
applied to various problems, there is room to boost its stability and improve convergence …
applied to various problems, there is room to boost its stability and improve convergence …
Dispersed foraging slime mould algorithm: Continuous and binary variants for global optimization and wrapper-based feature selection
The slime mould algorithm (SMA) is a logical swarm-based stochastic optimizer that is easy
to understand and has a strong optimization capability. However, the SMA is not suitable for …
to understand and has a strong optimization capability. However, the SMA is not suitable for …
A novel deep-learning model for automatic detection and classification of breast cancer using the transfer-learning technique
Breast cancer (BC) is one of the primary causes of cancer death among women. Early
detection of BC allows patients to receive appropriate treatment, thus increasing the …
detection of BC allows patients to receive appropriate treatment, thus increasing the …
Towards augmented kernel extreme learning models for bankruptcy prediction: algorithmic behavior and comprehensive analysis
Y Zhang, R Liu, AA Heidari, X Wang, Y Chen, M Wang… - Neurocomputing, 2021 - Elsevier
Bankruptcy prediction is a crucial application in financial fields to aid in accurate decision
making for business enterprises. Many models may stagnate to low-accuracy results due to …
making for business enterprises. Many models may stagnate to low-accuracy results due to …
Multi-population differential evolution-assisted Harris hawks optimization: Framework and case studies
The first powerful variant of the Harris hawks optimization (HHO) is proposed in this work.
HHO is a recently developed swarm-based stochastic algorithm that has previously shown …
HHO is a recently developed swarm-based stochastic algorithm that has previously shown …