An improved moth flame optimization algorithm based on modified dynamic opposite learning strategy DOI
Saroj Kumar Sahoo, Apu Kumar Saha, Sukanta Nama

et al.

Artificial Intelligence Review, Journal Year: 2022, Volume and Issue: 56(4), P. 2811 - 2869

Published: Aug. 16, 2022

Language: Английский

The Colony Predation Algorithm DOI Creative Commons

Jiaze Tu,

Huiling Chen, Mingjing Wang

et al.

Journal of Bionic Engineering, Journal Year: 2021, Volume and Issue: 18(3), P. 674 - 710

Published: May 1, 2021

Abstract This paper proposes a new stochastic optimizer called the Colony Predation Algorithm (CPA) based on corporate predation of animals in nature. CPA utilizes mathematical mapping following strategies used by animal hunting groups, such as dispersing prey, encircling supporting most likely successful hunter, and seeking another target. Moreover, proposed introduces features unique model that uses success rate to adjust strategy simulate animals’ selective abandonment behavior. also presents way deal with cross-border situations, whereby optimal position value situation replaces improve algorithm’s exploitation ability. The was compared state-of-the-art metaheuristics comprehensive set benchmark functions for performance verification five classical engineering design problems evaluate efficacy optimizing problems. results show algorithm exhibits competitive, superior different search landscapes over other algorithms. source code will be publicly available after publication.

Language: Английский

Citations

511

Artificial Neural Networks Based Optimization Techniques: A Review DOI Open Access
Maher G. M. Abdolrasol, S. M. Suhail Hussain, Taha Selim Ustun

et al.

Electronics, Journal Year: 2021, Volume and Issue: 10(21), P. 2689 - 2689

Published: Nov. 3, 2021

In the last few years, intensive research has been done to enhance artificial intelligence (AI) using optimization techniques. this paper, we present an extensive review of neural networks (ANNs) based algorithm techniques with some famous techniques, e.g., genetic (GA), particle swarm (PSO), bee colony (ABC), and backtracking search (BSA) modern developed lightning (LSA) whale (WOA), many more. The entire set such is classified as algorithms on a population where initial randomly created. Input parameters are initialized within specified range, they can provide optimal solutions. This paper emphasizes enhancing network via by manipulating its tuned or training obtain best structure pattern dissolve problems in way. includes results for improving ANN performance PSO, GA, ABC, BSA respectively, parameters, number neurons hidden layers learning rate. obtained net used solving energy management virtual power plant system.

Language: Английский

Citations

424

Protein nanoparticles in drug delivery: animal protein, plant proteins and protein cages, albumin nanoparticles DOI Creative Commons
Ehsan Kianfar

Journal of Nanobiotechnology, Journal Year: 2021, Volume and Issue: 19(1)

Published: May 29, 2021

Abstract In this article, we will describe the properties of albumin and its biological functions, types sources that can be used to produce nanoparticles, methods producing therapeutic applications importance nanoparticles in production pharmaceutical formulations. view increasing use Abraxane approval for treatment several cancer during final stages clinical trials other cancers, evaluate it compare effectiveness with conventional non formulations chemotherapy Paclitaxel is paid. examine role animal proteins Nano medicine various benefits these biomolecules preparation drug delivery carriers characteristics plant protein cages their potentials diagnosis treatment. Finally, advantages disadvantages are mentioned, as well

Language: Английский

Citations

325

A Novel Deep-Learning Model for Automatic Detection and Classification of Breast Cancer Using the Transfer-Learning Technique DOI Creative Commons
Abeer Saber,

Mohamed Sakr,

Osama M. Abo-Seida

et al.

IEEE Access, Journal Year: 2021, Volume and Issue: 9, P. 71194 - 71209

Published: Jan. 1, 2021

Breast cancer (BC) is one of the primary causes death among women. Early detection BC allows patients to receive appropriate treatment, thus increasing possibility survival. In this work, a new deep-learning (DL) model based on transfer-learning (TL) technique developed efficiently assist in automatic and diagnosis suspected area two techniques namely 80-20 cross-validation. DL architectures are modeled be problem-specific. TL uses knowledge gained during solving problem another relevant problem. proposed model, features extracted from mammographic image analysis- society (MIAS) dataset using pre-trained convolutional neural network (CNN) architecture such as Inception V3, ResNet50, Visual Geometry Group networks (VGG)-19, VGG-16, Inception-V2 ResNet. Six evaluation metrics for evaluating performance terms accuracy, sensitivity, specificity, precision, F-score, under ROC curve (AUC) has been chosen. Experimental results show that VGG16 powerful by classifying mammogram breast images with overall AUC 98.96%, 97.83%, 99.13%, 97.35%, 97.66%, 0.995, respectively method 98.87%, 97.27%, 98.2%, 98.84%, 98.04%, 0.993 10-fold cross-validation method.

Language: Английский

Citations

292

Magnetic Nanoparticles in Targeted Drug Delivery: a Review DOI
Ehsan Kianfar

Journal of Superconductivity and Novel Magnetism, Journal Year: 2021, Volume and Issue: 34(7), P. 1709 - 1735

Published: June 17, 2021

Language: Английский

Citations

187

Quantum differential evolution with cooperative coevolution framework and hybrid mutation strategy for large scale optimization DOI
Wu Deng,

Shifan Shang,

Xing Cai

et al.

Knowledge-Based Systems, Journal Year: 2021, Volume and Issue: 224, P. 107080 - 107080

Published: April 30, 2021

Language: Английский

Citations

181

Improving streamflow prediction using a new hybrid ELM model combined with hybrid particle swarm optimization and grey wolf optimization DOI

Rana Muhammad Adnan,

Reham R. Mostafa, Özgür Kişi

et al.

Knowledge-Based Systems, Journal Year: 2021, Volume and Issue: 230, P. 107379 - 107379

Published: Aug. 12, 2021

Language: Английский

Citations

168

Multilevel threshold image segmentation for COVID-19 chest radiography: A framework using horizontal and vertical multiverse optimization DOI
Hang Su, Dong Zhao, Hela Elmannai

et al.

Computers in Biology and Medicine, Journal Year: 2022, Volume and Issue: 146, P. 105618 - 105618

Published: May 18, 2022

Language: Английский

Citations

143

Rolling Element Fault Diagnosis Based on VMD and Sensitivity MCKD DOI Creative Commons

Hongjiang Cui,

Ying Guan,

Huayue Chen

et al.

IEEE Access, Journal Year: 2021, Volume and Issue: 9, P. 120297 - 120308

Published: Jan. 1, 2021

In order to improve the diagnosis accuracy and solve weak fault signal of rolling element bearings due long transmission path, a novel method based on variational mode decomposition (VMD) maximum correlation kurtosis deconvolution (MCKD), namely VMD-MCKD-FD is proposed for elements in this paper. VMD-MCKD-FD, vibration decomposed into series Intrinsic Mode Functions (IMFs) by using VMD method. Then number modes with outstanding information determined Kurtosis criterion calculate period T. The periodic component reconstructed enhanced sensitivity MCKD Finally, power spectrum analyzed detail obtain frequency diagnose bearings. simulation actual are selected verify effectiveness experimental results show that can effectively better accuracy.

Language: Английский

Citations

136

Machine Learning (ML) in Medicine: Review, Applications, and Challenges DOI Creative Commons
Amir Masoud Rahmani, Efat Yousefpoor, Mohammad Sadegh Yousefpoor

et al.

Mathematics, Journal Year: 2021, Volume and Issue: 9(22), P. 2970 - 2970

Published: Nov. 21, 2021

Today, artificial intelligence (AI) and machine learning (ML) have dramatically advanced in various industries, especially medicine. AI describes computational programs that mimic simulate human intelligence, for example, a person’s behavior solving problems or his ability learning. Furthermore, ML is subset of intelligence. It extracts patterns from raw data automatically. The purpose this paper to help researchers gain proper understanding its applications healthcare. In paper, we first present classification learning-based schemes According our proposed taxonomy, healthcare are categorized based on pre-processing methods (data cleaning methods, reduction methods), (unsupervised learning, supervised semi-supervised reinforcement learning), evaluation (simulation-based practical implementation-based real environment) (diagnosis, treatment). classification, review some studies presented We believe helps familiarize themselves with the newest research medicine, recognize their challenges limitations area, identify future directions.

Language: Английский

Citations

123