Elaine Yi-Ling Wu^*

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.1, pp. 1185-1214, 2025, DOI:10.32604/cmes.2025.064636 - 11 April 2025

Abstract Hybrid renewable energy systems (HRES) offer cost-effectiveness, low-emission power solutions, and reduced dependence on fossil fuels. However, the renewable energy allocation problem remains challenging due to complex system interactions and multiple operational constraints. This study develops a novel Multi-Neighborhood Enhanced Harris Hawks Optimization (MNEHHO) algorithm to address the allocation of HRES components. The proposed approach integrates key technical parameters, including charge-discharge efficiency, storage device configurations, and renewable energy fraction. We formulate a comprehensive mathematical model that simultaneously minimizes levelized energy costs and pollutant emissions while maintaining system reliability. The MNEHHO algorithm employs multiple neighborhood structures… More >

Yuting Zhu^1,*, Wenyu Zhang^1,2, Hainan Wang¹, Junjie Hou¹, Haining Wang¹, Meng Wang¹

CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 2177-2198, 2025, DOI:10.32604/cmc.2024.057441 - 17 February 2025

Abstract Addressing the complex issue of emergency resource distribution center site selection in uncertain environments, this study was conducted to comprehensively consider factors such as uncertainty parameters and the urgency of demand at disaster-affected sites. Firstly, urgency cost, economic cost, and transportation distance cost were identified as key objectives. The study applied fuzzy theory integration to construct a triangular fuzzy multi-objective site selection decision model. Next, the defuzzification theory transformed the fuzzy decision model into a precise one. Subsequently, an improved Chaotic Quantum Multi-Objective Harris Hawks Optimization (CQ-MOHHO) algorithm was proposed to solve the model. The… More >

Hala AlShamlan^*, Halah AlMazrua^*

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 675-694, 2024, DOI:10.32604/cmc.2024.048146 - 25 April 2024

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… 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 - 26 June 2023

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… 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 - 29 April 2023

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… 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 - 29 April 2023

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… 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 - 31 March 2023

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… More >

Chandana Gouri Tekkali, Karthika Natarajan^*

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3171-3187, 2023, DOI:10.32604/cmc.2023.036865 - 31 March 2023

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 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 - 05 January 2023

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 by… More >

T. Mahalekshmi^1,*, P. Maruthupandi²

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 445-460, 2023, DOI:10.32604/iasc.2023.028718 - 29 September 2022

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… More >