Jiamin Xiang¹, Ying Zhang¹, Xiaohua Cao^1,*, Zhigang Zhou²

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3443-3466, 2023, DOI:10.32604/cmc.2023.045120

Abstract This paper presents an improved hybrid algorithm and a multi-objective model to tackle the scheduling problem of multiple Automated Guided Vehicles (AGVs) under the composite operation mode. The multi-objective model aims to minimize the maximum completion time, the total distance covered by AGVs, and the distance traveled while empty-loaded. The improved hybrid algorithm combines the improved genetic algorithm (GA) and the simulated annealing algorithm (SA) to strengthen the local search ability of the algorithm and improve the stability of the calculation results. Based on the characteristics of the composite operation mode, the authors introduce the combined coding and parallel decoding… More >

Shanshan Wang^1,2,3, Quan Yuan¹, Weiwei Tan¹, Tengfei Yang¹, Liang Zeng^1,2,3,*

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3057-3075, 2023, DOI:10.32604/cmc.2023.044807

Abstract Feature Selection (FS) is an important problem that involves selecting the most informative subset of features from a dataset to improve classification accuracy. However, due to the high dimensionality and complexity of the dataset, most optimization algorithms for feature selection suffer from a balance issue during the search process. Therefore, the present paper proposes a hybrid Sine-Cosine Chimp Optimization Algorithm (SCChOA) to address the feature selection problem. In this approach, firstly, a multi-cycle iterative strategy is designed to better combine the Sine-Cosine Algorithm (SCA) and the Chimp Optimization Algorithm (ChOA), enabling a more effective search in the objective space. Secondly,… More >

Xiangmin Guo^1,2, Guangjun Liang^1,2,*, Jiayin Liu^1,2, Xianyi Chen^3,*

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3305-3323, 2023, DOI:10.32604/cmc.2023.044529

Abstract Cloud storage is widely used by large companies to store vast amounts of data and files, offering flexibility, financial savings, and security. However, information shoplifting poses significant threats, potentially leading to poor performance and privacy breaches. Blockchain-based cognitive computing can help protect and maintain information security and privacy in cloud platforms, ensuring businesses can focus on business development. To ensure data security in cloud platforms, this research proposed a blockchain-based Hybridized Data Driven Cognitive Computing (HD2C) model. However, the proposed HD2C framework addresses breaches of the privacy information of mixed participants of the Internet of Things (IoT) in the cloud.… More >

Wei Chen, Ming Li^*, Tingting Pei, Cunyu Sun, Huan Lei

Energy Engineering, Vol.121, No.1, pp. 125-144, 2024, DOI:10.32604/ee.2023.042812

Abstract At present, the operation and maintenance of photovoltaic power generation systems mainly comprise regular maintenance, breakdown maintenance, and condition-based maintenance, which is very likely to lead to over- or under-repair of equipment. Therefore, a preventive maintenance and replacement strategy for PV power generation systems based on reliability as a constraint is proposed. First, a hybrid failure function with a decreasing service age factor and an increasing failure rate factor is introduced to describe the deterioration of PV power generation equipment, and the equipment is replaced when its reliability drops to the replacement threshold in the last cycle. Then, based on… More >

Nasser Alalwan^1,*, Ahmed I. Taloba², Amr Abozeid³, Ahmed Ibrahim Alzahrani¹, Ali H. Al-Bayatti⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2497-2517, 2024, DOI:10.32604/cmes.2023.029910

Abstract An illness known as pneumonia causes inflammation in the lungs. Since there is so much information available from various X-ray images, diagnosing pneumonia has typically proven challenging. To improve image quality and speed up the diagnosis of pneumonia, numerous approaches have been devised. To date, several methods have been employed to identify pneumonia. The Convolutional Neural Network (CNN) has achieved outstanding success in identifying and diagnosing diseases in the fields of medicine and radiology. However, these methods are complex, inefficient, and imprecise to analyze a big number of datasets. In this paper, a new hybrid method for the automatic classification… More >

Shimaa M. Amer¹, Ashraf A. M. Khalaf², Amr H. Hussein^3,4, Salman A. Alqahtani⁵, Mostafa H. Dahshan⁶, Hossam M. Kassem^3,4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2749-2767, 2024, DOI:10.32604/cmes.2023.029138

Abstract Side lobe level reduction (SLL) of antenna arrays significantly enhances the signal-to-interference ratio and improves the quality of service (QOS) in recent and future wireless communication systems starting from 5G up to 7G. Furthermore, it improves the array gain and directivity, increasing the detection range and angular resolution of radar systems. This study proposes two highly efficient SLL reduction techniques. These techniques are based on the hybridization between either the single convolution or the double convolution algorithms and the genetic algorithm (GA) to develop the Conv/GA and DConv/GA, respectively. The convolution process determines the element’s excitations while the GA optimizes… More >

Hamzeh Taha Alkasasbeh^1,*, Muhammad Khairul Anuar Mohamed²

Frontiers in Heat and Mass Transfer, Vol.21, pp. 265-279, 2023, DOI:10.32604/fhmt.2023.041539

Abstract The present study numerically investigates the flow and heat transfer of porous Williamson hybrid nanofluid on an exponentially shrinking sheet with magnetohydrodynamic (MHD) effects. The nonlinear partial differential equations which governed the model are first reduced to a set of ordinary differential equations by using the similarity transformation. Next, the BVP4C solver is applied to solve the equations by considering the pertinent fluid parameters such as the permeability parameter, the magnetic parameter, the Williamson parameter, the nanoparticle volume fractions and the wall mass transfer parameter. The single (SWCNTs) and multi-walled carbon nanotubes (MWCNTs) nanoparticles are taken as the hybrid nanoparticles.… More >

Asmaa Habib Alanzi, N. Ameer Ahammad^*

Frontiers in Heat and Mass Transfer, Vol.21, pp. 179-197, 2023, DOI:10.32604/fhmt.2023.042009

Abstract The conversion of solar radiation to thermal energy has recently attracted a lot of interest as the requirement for renewable heat and power grows. Due to their enhanced ability to promote heat transmission, nanofluids can significantly contribute to enhancing the efficiency of solar-thermal systems. This article focus solar energy aspect on the effects of the thermal radiation in the flow of a hyperbolic tangent nanofluid containing magnesium oxide (MgO) and silver (Ag) are the nanoparticle with the base fluid as kerosene through a wedge and stagnation. The system of hybrid nanofluid transport equations are transformed into ordinary differential systems using… More >

Mohammed Z. Swalmeh^1,*, Firas A. Alwawi², A. A. Altawallbeh³, Wejdan Mesa’adeen⁴, Feras M. Al Faqih⁴, Ahmad M. Awajan⁴

Frontiers in Heat and Mass Transfer, Vol.21, pp. 505-522, 2023, DOI:10.32604/fhmt.2023.044300

Abstract In current study, the influence of magnetic field (MHD) on heat transfer of natural convection boundary layer flow in Casson ternary hybrid nanofluid past a stretching sheet is studied using numerical simulation. The Newtonian heating boundary conditions that depend on the temperature and velocity terms are taken into this investigation. The particular dimensional governing equations, for the studied problem, are converted to the system of partial differential equations utilizing adequate similarity transformation. Consequently, the system of equations is numerically solved using well-known Kellar box numerical techniques. The obtained numerical results are in excellent approval with previous literature results. The existence… More >

Na Yu¹, Changzheng Gao², Xiuna Wang², Dongwei Li^2,*, Weiyang You²

Energy Engineering, Vol.120, No.12, pp. 2879-2901, 2023, DOI:10.32604/ee.2023.029426

Abstract With the goal of “carbon peaking and carbon neutralization”, it is an inevitable trend for investing smart grid to promote the large-scale grid connection of renewable energy. Smart grid investment has a significant driving effect (derivative value), and evaluating this value can help to more accurately grasp the external effects of smart grid investment and support the realization of industrial linkage value with power grid investment as the core. Therefore, by analyzing the characterization of the derivative value of smart grid driven by investment, this paper constructs the evaluation index system of the derivative value of smart grid investment including… More >