Baydaa Abdul Kareem^1,2, Salah L. Zubaidi^2,3, Nadhir Al-Ansari^4,*, Yousif Raad Muhsen^2,5

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 1-41, 2024, DOI:10.32604/cmes.2023.027954

Abstract Forecasting river flow is crucial for optimal planning, management, and sustainability using freshwater resources. Many machine learning (ML) approaches have been enhanced to improve streamflow prediction. Hybrid techniques have been viewed as a viable method for enhancing the accuracy of univariate streamflow estimation when compared to standalone approaches. Current researchers have also emphasised using hybrid models to improve forecast accuracy. Accordingly, this paper conducts an updated literature review of applications of hybrid models in estimating streamflow over the last five years, summarising data preprocessing, univariate machine learning modelling strategy, advantages and disadvantages of standalone ML techniques, hybrid models, and performance… More > Graphic Abstract

Cho Mar Aye¹, Kittinan Wansaseub², Sumit Kumar³, Ghanshyam G. Tejani⁴, Sujin Bureerat¹, Ali R. Yildiz⁵, Nantiwat Pholdee^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2111-2128, 2023, DOI:10.32604/cmes.2023.028632

Abstract This work presents multi-fidelity multi-objective infill-sampling surrogate-assisted optimization for airfoil shape optimization. The optimization problem is posed to maximize the lift and drag coefficient ratio subject to airfoil geometry constraints. Computational Fluid Dynamic (CFD) and XFoil tools are used for high and low-fidelity simulations of the airfoil to find the real objective function value. A special multi-objective sub-optimization problem is proposed for multiple points infill sampling exploration to improve the surrogate model constructed. To validate and further assess the proposed methods, a conventional surrogate-assisted optimization method and an infill sampling surrogate-assisted optimization criterion are applied with multi-fidelity simulation, while their… More > Graphic Abstract

Ahmad A. A. Alkhatib^*, Adnan A. Hnaif, Thaer Sawalha

Computer Systems Science and Engineering, Vol.47, No.1, pp. 637-656, 2023, DOI:10.32604/csse.2023.037345

Abstract Large cities suffer from traffic congestion, particularly at intersections, due to a large number of vehicles, which leads to the loss of time by increasing carbon emissions, including fuel consumption. Therefore, the need for optimising the flow of vehicles at different intersections and reducing the waiting time is a critical challenge. Conventional traffic lights have been used to control traffic flow at different intersections and have been improved to become more efficient by using different algorithms, sensors and cameras. However, they also face some challenges, such as high-cost installation, operation, and maintenance issues. This paper develops a new system based… More >

Qifen Li, Xiaoxiao Yan^*, Yongwen Yang, Liting Zhang, Yuanbo Hou

Journal of Renewable Materials, Vol.11, No.7, pp. 3177-3191, 2023, DOI:10.32604/jrm.2023.027749

Abstract Microbial Electrolytic Cell (MEC) is an electrochemical reaction device that uses electrical energy as an energy input and microorganisms as catalysts to produce fuels and chemicals. The regenerative electrochemical system is a MEC improvement system for methane gas produced by biological carbon sequestration technology using renewable energy sources to provide a voltage environment. In response to the influence of fluctuating disturbances of renewable electricity and the long system start-up time, this paper analyzes the characteristics of two strategies, regulating voltage parameter changes and activated sludge pretreatment, on the methane production efficiency of the renewable gas electrochemical system. In this system,… More >

Zhonghai Jiang¹, Qian Wang¹, Liangbing Zhou^2,*, Chun Xiao³

FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.6, pp. 1693-1708, 2023, DOI:10.32604/fdmp.2023.025270

Abstract A two-layer implicit difference scheme is employed in the present study to determine the temperature distribution in an asphalt pavement. The calculation of each layer only needs four iterations to achieve convergence. Furthermore, in order to improve the calculation accuracy a swarm intelligence optimization algorithm is also exploited to inversely analyze the laws by which the thermal physical parameters of the asphalt pavement materials change with temperature. Using the basic cuckoo and the gray wolf algorithms, an adaptive hybrid optimization algorithm is obtained and used to determine the relationship between the thermal diffusivity of two types of asphalt pavement materials… More >

K. Sreelakshmy¹, Himanshu Gupta¹, Om Prakash Verma¹, Kapil Kumar², Abdelhamied A. Ateya³, Naglaa F. Soliman^4,*

Computer Systems Science and Engineering, Vol.45, No.3, pp. 2483-2503, 2023, DOI:10.32604/csse.2023.032737

Abstract Unmanned Aerial Vehicles (UAVs) or drones introduced for military applications are gaining popularity in several other fields as well such as security and surveillance, due to their ability to perform repetitive and tedious tasks in hazardous environments. Their increased demand created the requirement for enabling the UAVs to traverse independently through the Three Dimensional (3D) flight environment consisting of various obstacles which have been efficiently addressed by metaheuristics in past literature. However, not a single optimization algorithms can solve all kind of optimization problem effectively. Therefore, there is dire need to integrate metaheuristic for general acceptability. To address this issue,… More >

WEI WANG^1,#, YANRONG PEI^2,#, SHUI-HUA WANG¹, JUAN MANUEL GORRZ³, YU-DONG ZHANG^1,*

BIOCELL, Vol.47, No.2, pp. 373-384, 2023, DOI:10.32604/biocell.2023.025905

Abstract Since 2019, the coronavirus disease-19 (COVID-19) has been spreading rapidly worldwide, posing an unignorable threat to the global economy and human health. It is a disease caused by severe acute respiratory syndrome coronavirus 2, a single-stranded RNA virus of the genus Betacoronavirus. This virus is highly infectious and relies on its angiotensin-converting enzyme 2-receptor to enter cells. With the increase in the number of confirmed COVID-19 diagnoses, the difficulty of diagnosis due to the lack of global healthcare resources becomes increasingly apparent. Deep learning-based computer-aided diagnosis models with high generalisability can effectively alleviate this pressure. Hyperparameter tuning is essential in… More >

Rebecca Gedda^1,*, Larisa Beilina², Ruomu Tan³

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.3, pp. 1737-1759, 2023, DOI:10.32604/cmes.2022.019764

Abstract Change point detection becomes increasingly important because it can support data analysis by providing labels to the data in an unsupervised manner. In the context of process data analytics, change points in the time series of process variables may have an important indication about the process operation. For example, in a batch process, the change points can correspond to the operations and phases defined by the batch recipe. Hence identifying change points can assist labelling the time series data. Various unsupervised algorithms have been developed for change point detection, including the optimisation approach which minimises a cost function with certain… More > Graphic Abstract

S. Siamala Devi¹, Chandrakala Kuruba², Yunyoung Nam^3,*, Mohamed Abouhawwash^4,5

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1873-1887, 2023, DOI:10.32604/iasc.2023.025504

Abstract Wireless sensor networks (WSNs) are projected to have a wide range of applications in the future. The fundamental problem with WSN is that it has a finite lifespan. Clustering a network is a common strategy for increasing the lifetime of WSNs and, as a result, allowing for faster data transmission. The clustering algorithm’s goal is to select the best cluster head (CH). In the existing system, Hybrid grey wolf sunflower optimization algorithm (HGWSFO)and optimal cluster head selection method is used. It does not provide better competence and output in the network. Therefore, the proposed Hybrid Grey Wolf Ant Colony Optimisation… More >

Najla Bagais^*, Etimad Fadel, Amal Al-Mansour

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1237-1267, 2022, DOI:10.32604/cmc.2022.026070

Abstract Wireless sensor networks (WSNs) are considered the backbone of the Internet of Things (IoT), which enables sensor nodes (SNs) to achieve applications similarly to human intelligence. However, integrating a WSN with the IoT is challenging and causes issues that require careful exploration. Prolonging the lifetime of a network through appropriately utilising energy consumption is among the essential challenges due to the limited resources of SNs. Thus, recent research has examined mobile sinks (MSs), which have been introduced to improve the overall efficiency of WSNs. MSs bear the burden of data collection instead of consuming energy at the routeing by SNs.… More >