Hala AlShamlan^*, Halah AlMazrua^*

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 675-694, 2024, DOI:10.32604/cmc.2024.048146

Abstract In this study, our aim is to address the problem of gene selection by proposing a hybrid bio-inspired evolutionary algorithm that combines Grey Wolf Optimization (GWO) with Harris Hawks Optimization (HHO) for feature selection. The motivation for utilizing GWO and HHO stems from their bio-inspired nature and their demonstrated success in optimization problems. We aim to leverage the strengths of these algorithms to enhance the effectiveness of feature selection in microarray-based cancer classification. We selected leave-one-out cross-validation (LOOCV) to evaluate the performance of both two widely used classifiers, k-nearest neighbors (KNN) and support vector machine (SVM), on high-dimensional cancer microarray… More >

Hao Cui, Yanling Guo^*, Yaning Xiao, Yangwei Wang^*, Jian Li, Yapeng Zhang, Haoyu Zhang

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1635-1675, 2023, DOI:10.32604/cmes.2023.026019

Abstract Harris Hawks Optimization (HHO) is a novel meta-heuristic algorithm that imitates the predation characteristics of Harris Hawk and combines Lévy flight to solve complex multidimensional problems. Nevertheless, the basic HHO algorithm still has certain limitations, including the tendency to fall into the local optima and poor convergence accuracy. Coot Bird Optimization (CBO) is another new swarm-based optimization algorithm. CBO originates from the regular and irregular motion of a bird called Coot on the water’s surface. Although the framework of CBO is slightly complicated, it has outstanding exploration potential and excellent capability to avoid falling into local optimal solutions. This paper… More > Graphic Abstract

V. Nivethitha^*, G. Aghila

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 887-904, 2023, DOI:10.32604/iasc.2023.034247

Abstract Cloud computing is considered to facilitate a more cost-effective way to deploy scientific workflows. The individual tasks of a scientific workflow necessitate a diversified number of large states that are spatially located in different datacenters, thereby resulting in huge delays during data transmission. Edge computing minimizes the delays in data transmission and supports the fixed storage strategy for scientific workflow private datasets. Therefore, this fixed storage strategy creates huge amount of bottleneck in its storage capacity. At this juncture, integrating the merits of cloud computing and edge computing during the process of rationalizing the data placement of scientific workflows and… More >

Latifah Almuqren¹, Manar Ahmed Hamza^2,*, Abdullah Mohamed³, Amgad Atta Abdelmageed²

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 4917-4933, 2023, DOI:10.32604/cmc.2023.037738

Abstract Face recognition technology automatically identifies an individual from image or video sources. The detection process can be done by attaining facial characteristics from the image of a subject face. Recent developments in deep learning (DL) and computer vision (CV) techniques enable the design of automated face recognition and tracking methods. This study presents a novel Harris Hawks Optimization with deep learning-empowered automated face detection and tracking (HHODL-AFDT) method. The proposed HHODL-AFDT model involves a Faster region based convolution neural network (RCNN)-based face detection model and HHO-based hyperparameter optimization process. The presented optimal Faster RCNN model precisely recognizes the face and… More >

Siling Feng¹, Yinjie Chen¹, Mengxing Huang^1,2,*, Feng Shu¹

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 4341-4355, 2023, DOI:10.32604/cmc.2023.037154

Abstract Due to their adaptability, Unmanned Aerial Vehicles (UAVs) play an essential role in the Internet of Things (IoT). Using wireless power transfer (WPT) techniques, an UAV can be supplied with energy while in flight, thereby extending the lifetime of this energy-constrained device. This paper investigates the optimization of resource allocation in light of the fact that power transfer and data transmission cannot be performed simultaneously. In this paper, we propose an optimization strategy for the resource allocation of UAVs in sensor communication networks. It is a practical solution to the problem of marine sensor networks that are located far from… More >

Chandana Gouri Tekkali, Karthika Natarajan^*

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3171-3187, 2023, DOI:10.32604/cmc.2023.036865

Abstract Fraud Transactions are haunting the economy of many individuals with several factors across the globe. This research focuses on developing a mechanism by integrating various optimized machine-learning algorithms to ensure the security and integrity of digital transactions. This research proposes a novel methodology through three stages. Firstly, Synthetic Minority Oversampling Technique (SMOTE) is applied to get balanced data. Secondly, SMOTE is fed to the nature-inspired Meta Heuristic (MH) algorithm, namely Binary Harris Hawks Optimization (BinHHO), Binary Aquila Optimization (BAO), and Binary Grey Wolf Optimization (BGWO), for feature selection. BinHHO has performed well when compared with the other two. Thirdly, features… More >

Basma Mohamed^1,*, Linda Mohaisen², Mohamed Amin¹

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2349-2361, 2023, DOI:10.32604/iasc.2023.032930

Abstract In this paper, we consider the NP-hard problem of finding the minimum connected resolving set of graphs. A vertex set B of a connected graph G resolves G if every vertex of G is uniquely identified by its vector of distances to the vertices in B. A resolving set B of G is connected if the subgraph induced by B is a nontrivial connected subgraph of G. The cardinality of the minimal resolving set is the metric dimension of G and the cardinality of minimum connected resolving set is the connected metric dimension of G. The problem is solved heuristically… More >

T. Mahalekshmi^1,*, P. Maruthupandi²

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 445-460, 2023, DOI:10.32604/iasc.2023.028718

Abstract The eminence of Economic Dispatch (ED) in power systems is significantly high as it involves in scheduling the available power from various power plants with less cost by compensating equality and inequality constrictions. The emission of toxic gases from power plants leads to environmental imbalance and so it is highly mandatory to rectify this issues for obtaining optimal performance in the power systems. In this present study, the Economic and Emission Dispatch (EED) problems are resolved as multi objective Economic Dispatch problems by using Harris Hawk’s Optimization (HHO), which is capable enough to resolve the concerned issue in a wider… More >

V. R. Kavitha¹, K. Nimala², A. Beno³, K. C. Ramya⁴, Seifedine Kadry⁵, Byeong-Gwon Kang⁶, Yunyoung Nam^7,*

Computer Systems Science and Engineering, Vol.44, No.1, pp. 579-593, 2023, DOI:10.32604/csse.2023.024553

Abstract Image Captioning is an emergent topic of research in the domain of artificial intelligence (AI). It utilizes an integration of Computer Vision (CV) and Natural Language Processing (NLP) for generating the image descriptions. It finds use in several application areas namely recommendation in editing applications, utilization in virtual assistance, etc. The development of NLP and deep learning (DL) models find useful to derive a bridge among the visual details and textual semantics. In this view, this paper introduces an Oppositional Harris Hawks Optimization with Deep Learning based Image Captioning (OHHO-DLIC) technique. The OHHO-DLIC technique involves the design of distinct levels… More >

Manar Ahmed Hamza^1,*, Abdelzahir Abdelmaboud², Souad Larabi-Marie-Sainte³, Haya Mesfer Alshahrani⁴, Mesfer Al Duhayyim⁵, Hamza Awad Ibrahim⁶, Mohammed Rizwanullah¹, Ishfaq Yaseen¹

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1951-1965, 2022, DOI:10.32604/cmc.2022.024692

Abstract Generally, software testing is considered as a proficient technique to achieve improvement in quality and reliability of the software. But, the quality of test cases has a considerable influence on fault revealing capability of software testing activity. Test Case Prioritization (TCP) remains a challenging issue since prioritizing test cases is unsatisfactory in terms of Average Percentage of Faults Detected (APFD) and time spent upon execution results. TCP is mainly intended to design a collection of test cases that can accomplish early optimization using preferred characteristics. The studies conducted earlier focused on prioritizing the available test cases in accelerating fault detection… More >