Yu Xue^1,2,* , Yan Zhao¹

Journal on Internet of Things, Vol.3, No.3, pp. 109-118, 2021, DOI:10.32604/jiot.2021.014980 - 16 December 2021

Abstract As a new intelligent optimization method, brain storm optimization (BSO) algorithm has been widely concerned for its advantages in solving classical optimization problems. Recently, an evolutionary classification optimization model based on BSO algorithm has been proposed, which proves its effectiveness in solving the classification problem. However, BSO algorithm also has defects. For example, large-scale datasets make the structure of the model complex, which affects its classification performance. In addition, in the process of optimization, the information of the dominant solution cannot be well preserved in BSO, which leads to its limitations in classification performance. Moreover,… More >

Shuai Zheng, An-Nan Jiang^*, Kai-Shuai Feng

CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 149-166, 2021, DOI:10.32604/cmes.2021.016761 - 24 August 2021

Abstract The randomness of rock joint development is an important factor in the uncertainty of geotechnical engineering stability. In this study, a method is proposed to evaluate the reliability of intermittent jointed rock slope. The least squares support vector machine (LSSVM) evolved by a bacterial foraging optimization algorithm (BFOA) is used to establish a response surface model to express the mapping relationship between the intermittent joint parameters and the slope safety factor. The training samples are obtained from the numerical calculation based on the joint finite element method during this process. Considering the randomness of the… More >

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 >

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 >

Huan Zhang^1,2, Jiliu Zhou^1,2,*, Xi Wu²

CMES-Computer Modeling in Engineering & Sciences, Vol.127, No.3, pp. 1151-1175, 2021, DOI:10.32604/cmes.2021.015462 - 24 May 2021

Abstract In hardware Trojan detection technology, destructive reverse engineering can restore an original integrated circuit with the highest accuracy. However, this method has a much higher overhead in terms of time, effort, and cost than bypass detection. This study proposes an algorithm, called mixed-feature gene expression programming, which applies non-destructive reverse engineering to the chip with bypass detection data. It aims to recover the original integrated circuit hardware, or else reveal the unknown circuit design in the chip. More >

Changchun Gao¹, Shiyu Liu^1,*, Chenhui Yu¹, Peng Guo²

Computer Systems Science and Engineering, Vol.38, No.3, pp. 365-379, 2021, DOI:10.32604/csse.2021.016506 - 19 May 2021

Abstract The creative industry is a knowledge-based industry, but it is difficult and complex to create knowledge for enterprises. The principle of cooperation-sharing posits that companies’ limited resources prohibit them from gaining a competitive advantage in all business areas. Therefore, cooperation-sharing can help businesses overcome this hurdle. Cooperation-sharing expedites economic development, breaks the barrier of independent knowledge creation, and enhances resource utilization. However, the effectiveness and stability of knowledge cooperation-sharing are key problems facing governments and other regulators. This study can help regulators promote honesty in enterprise cooperation-sharing. Based on the hypothesis of bounded rationality, the… More >

V. Nivedhitha^1,*, A. Gopi Saminathan², P. Thirumurugan³

Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 603-616, 2021, DOI:10.32604/iasc.2021.016780 - 20 April 2021

Abstract Several protocols strive to improve network longevity but fail to ameliorate the uneven overhead imparted upon the sensor nodes that lead to temporal deaths. The proposed work uses a metaheuristic approach that promotes load balancing and energy-efficient data transmission using the fruit fly optimization algorithm (FFOA). The approach combines the LEACH protocol with differential evolution (DE) to select an optimum cluster head in every cluster. The algorithm is designed to provide energy-efficient data transmissions based on the smell and vision foraging behavior of fruit flies. The approach considers the compactness of nodes, energy capacity, and More >

Farhan Aadil¹, Bilal Mehmood¹, Najam Ul Hasan², Sangsoon Lim^3,*, Sadia Ejaz¹, Noor Zaman⁴

CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2499-2513, 2021, DOI:10.32604/cmc.2021.014647 - 13 April 2021

Abstract A wireless body area network (WBAN) consists of tiny health-monitoring sensors implanted in or placed on the human body. These sensors are used to collect and communicate human medical and physiological data and represent a subset of the Internet of Things (IoT) systems. WBANs are connected to medical servers that monitor patients’ health. This type of network can protect critical patients’ lives due to the ability to monitor patients’ health continuously and remotely. The inter-WBAN communication provides a dynamic environment for patients allowing them to move freely. However, during patient movement, the WBAN patient nodes… More >

Ying Fu^1,2,*, Minxue Gong¹, Guang Yang¹, Hong Wei³, Jiliu Zhou^1,2

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1359-1374, 2021, DOI:10.32604/cmc.2021.016536 - 22 March 2021

Abstract Generative adversarial networks (GANs) have considerable potential to alleviate challenges linked to data scarcity. Recent research has demonstrated the good performance of this method for data augmentation because GANs synthesize semantically meaningful data from standard signal distribution. The goal of this study was to solve the overfitting problem that is caused by the training process of convolution networks with a small dataset. In this context, we propose a data augmentation method based on an evolutionary generative adversarial network for cardiac magnetic resonance images to extend the training data. In our structure of the evolutionary GAN,… More >

Fatimah O. Albalawi, Mashael S. Maashi^*

Intelligent Automation & Soft Computing, Vol.28, No.1, pp. 39-52, 2021, DOI:10.32604/iasc.2021.015657 - 17 March 2021

Abstract In the software field, a large number of projects fail, and billions of dollars are spent on these failed projects. Many software projects are also produced with poor quality or they do not exactly meet customers’ expectations. Moreover, these projects may exceed project budget and/or time. The complexity of managing software development projects and the poor selection of software development life cycle (SDLC) models are among the top reasons for such failure. Various SDLC models are available, but no model is considered the best or worst. In this work, we propose a new methodology that… More >