Qasim M. Zainel¹, Murad B. Khorsheed², Saad Darwish^3,*, Amr A. Ahmed⁴

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3813-3828, 2021, DOI:10.32604/cmc.2021.014759 - 24 August 2021

Abstract Convolutional Neural Networks (CNNs) models succeed in vast domains. CNNs are available in a variety of topologies and sizes. The challenge in this area is to develop the optimal CNN architecture for a particular issue in order to achieve high results by using minimal computational resources to train the architecture. Our proposed framework to automated design is aimed at resolving this problem. The proposed framework is focused on a genetic algorithm that develops a population of CNN models in order to find the architecture that is the best fit. In comparison to the co-authored work,… More >

Rihem Farkh^1,2, Yasser Fouad^1,*, Haykel Marouani¹

Intelligent Automation & Soft Computing, Vol.30, No.3, pp. 837-851, 2021, DOI:10.32604/iasc.2021.018214 - 20 August 2021

Abstract In industrial practice, certain processes are unstable, such as different types of reactors, distillation columns, and combustion systems. To ensure greater maneuverability and improve the speed of response command, certain systems in the military and aviation fields are purposely configured to be unstable. These systems are often more difficult to control than stable systems and are of particular interest to designers and control engineers. Despite all advances in process control over the past six decades, the proportional–integral–derivative (PID) controller is still the most common. The main reasons are the simplicity, robustness, and successful applications provided… More >

Yu Xue^1,*, Asma Aouari¹, Romany F. Mansour², Shoubao Su³

Journal of Cyber Security, Vol.3, No.2, pp. 117-124, 2021, DOI:10.32604/jcs.2021.017018 - 02 August 2021

Abstract One of the main problems of machine learning and data mining is to develop a basic model with a few features, to reduce the algorithms involved in classification’s computational complexity. In this paper, the collection of features has an essential importance in the classification process to be able minimize computational time, which decreases data size and increases the precision and effectiveness of specific machine learning activities. Due to its superiority to conventional optimization methods, several metaheuristics have been used to resolve FS issues. This is why hybrid metaheuristics help increase the search and convergence rate More >

Prince Waqas Khan, Yung-Cheol Byun^*

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1893-1913, 2021, DOI:10.32604/cmc.2021.018523 - 21 July 2021

Abstract Despite the advancement within the last decades in the field of smart grids, energy consumption forecasting utilizing the metrological features is still challenging. This paper proposes a genetic algorithm-based adaptive error curve learning ensemble (GA-ECLE) model. The proposed technique copes with the stochastic variations of improving energy consumption forecasting using a machine learning-based ensembled approach. A modified ensemble model based on a utilizing error of model as a feature is used to improve the forecast accuracy. This approach combines three models, namely CatBoost (CB), Gradient Boost (GB), and Multilayer Perceptron (MLP). The ensembled CB-GB-MLP model’s… More >

Anil Kumar Gulivindala¹, M. V. A. Raju Bahubalendruni¹, R. Chandrasekar^1,2, Ejaz Ahmed², Mustufa Haider Abidi^3,*, Abdulrahman Al-Ahmari⁴

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2531-2548, 2021, DOI:10.32604/cmc.2021.018014 - 21 July 2021

Abstract The evolution of Industry 4.0 made it essential to adopt the Internet of Things (IoT) and Cloud Computing (CC) technologies to perform activities in the new age of manufacturing. These technologies enable collecting, storing, and retrieving essential information from the manufacturing stage. Data collected at sites are shared with others where execution automatedly occurs. The obtained information must be validated at manufacturing to avoid undesirable data losses during the de-manufacturing process. However, information sharing from the assembly level at the manufacturing stage to disassembly at the product end-of-life state is a major concern. The current… More >

İlyas Kacar^*

CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.1, pp. 87-108, 2021, DOI:10.32604/cmes.2021.015227 - 28 June 2021

Abstract Locking nuts are widely used in industry and any defects from their manufacturing may cause loosening of the connection during their service life. In this study, simulations of the folding process of a nut’s flange made from AISI 1040 steel are performed. Besides the bilinear isotropic hardening rule, Chaboche’s nonlinear kinematic hardening rule is employed with associated flow rule and Hill48 yield criterion to set a plasticity model. The bilinear isotropic hardening rule’s parameters are determined by means of a monotonic tensile test. The Chaboche’s parameters are determined by using a low cycle tension/compression test… More >

Muhammad Irshad Nazeer^1,2,*, Ghulam Ali Mallah¹, Raheel Ahmed Memon²

Intelligent Automation & Soft Computing, Vol.29, No.2, pp. 633-648, 2021, DOI:10.32604/iasc.2021.017771 - 16 June 2021

Abstract Network Coding is a potential technology for the future wireless communications and Internet of Things (IoT) as it reduces the number of transmissions and offers energy efficiency. It is vulnerable to threat and attack that can harm intermediate nodes. Indeed, it exhibits an ability to incorporate security of transmitted data, yet a lot of work needs to be done to provide a safeguard from threats. The purpose of this study is to strengthen the existing Network Coding scheme with a set of generic requirements for Network Coding Protocols by adopting system models and a Genetic… More >

Hissah A. Ben Zayed, Mashael S. Maashi^*

Intelligent Automation & Soft Computing, Vol.29, No.1, pp. 307-318, 2021, DOI:10.32604/iasc.2021.017239 - 12 May 2021

Abstract Software testing is a fundamental step in the software development lifecycle. Its purpose is to evaluate the quality of software applications. Regression testing is an important testing methodology in software testing. The purpose of regression testing is to validate the software after each change of its code. This involves adding new test cases to the test suite and running the test suite as the software changes, making the test suite larger. The cost and time of the project are affected by the test suite size. The challenge is to run regression testing with a smaller… More >

Ahmed S. Ghiduk^1,*, Moheb R. Girgis³, Eman Hassan^2,4, Sultan Aljahdali¹

Intelligent Automation & Soft Computing, Vol.29, No.1, pp. 147-164, 2021, DOI:10.32604/iasc.2021.015708 - 12 May 2021

Abstract Path-based testing involves two main steps: 1) finding all paths throughout the code under test; 2) creating a test suite to cover these paths. Unfortunately, covering all paths in the code under test is impossible. Path-based testing could be achieved by targeting a subset of all feasible paths that satisfy a given testing criterion. Then, a test suite is created to execute this paths subset. Generating those paths is a key problem in path testing. In this paper, a new path testing technique is presented. This technique employs Particle Swarm Optimization (PSO) for generating a… More >

Mohammad Javad Jafari¹, Mohsen Niknam Sharak², Ali Khavanin³, Touraj Ebadzadeh⁴, Mahmood Fazlali⁵, Rohollah Fallah Madvari^6,*

Sound & Vibration, Vol.55, No.2, pp. 117-130, 2021, DOI:10.32604/sv.2021.09729 - 21 April 2021

Abstract Fabricating of metal foams with desired morphological parameters including pore size, porosity and pore opening is possible now using sintering technology. Thus, if it is possible to determine the morphology of metal foam to absorb sound at a given frequency, and then fabricate it through sintering, it is expected to have optimized metal foams for the best sound absorption. Theoretical sound absorption models such as Lu model describe the relationship between morphological parameters and the sound absorption coefficient. In this study, the Lu model was used to optimize the morphological parameters of Aluminum metal foam… More >