Chung Wen Hung, Wei Lung Mao, Han Yi Huang

Intelligent Automation & Soft Computing, Vol.25, No.2, pp. 329-341, 2019, DOI:10.31209/2019.100000093

Abstract Nonlinear system modeling and identification is the one of the most important areas in engineering problem. The paper presents the recurrent fuzzy neural network (RFNN) trained by modified particle swarm optimization (MPSO) methods for identifying the dynamic systems and chaotic observation prediction. The proposed MPSO algorithms mainly modify the calculation formulas of inertia weights. Two MPSOs, namely linear decreasing particle swarm optimization (LDPSO) and adaptive particle swarm optimization (APSO) are developed to enhance the convergence behavior in learning process. The RFNN uses MPSO based method to tune the parameters of the membership functions, and it uses gradient descent (GD) based… More >

Yasir Mehmood, Waseem Shahzad

Intelligent Automation & Soft Computing, Vol.25, No.1, pp. 91-103, 2019, DOI:10.31209/2018.100000017

Abstract Particle swarm optimization (PSO) algorithm is a global optimization technique that is used to find the optimal solution in multimodal problems. However, one of the limitation of PSO is its slow convergence rate along with a local trapping dilemma in complex multimodal problems. To address this issue, this paper provides an alternative technique known as ACPSO algorithm, which enables to adopt a new simplified velocity update rule to enhance the performance of PSO. As a result, the efficiency of convergence speed and solution accuracy can be maximized. The experimental results show that the ACPSO outperforms most of the compared PSO… More >

Fuquan Huang¹, Zijun Liu¹, Tinghuang Wang¹, Haitai Zhang^{2, *}, Tony Yip³

CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 865-878, 2020, DOI:10.32604/cmc.2020.010724

Abstract In order to quickly and accurately locate the fault location of the distribution network and increase the stability of the distribution network, a fault recovery method based on multi-objective optimization algorithm is proposed. The optimization of the power distribution network fault system based on multiagent technology realizes fast recovery of multi-objective fault, solve the problem of network learning and parameter adjustment in the later stage of particle swarm optimization algorithm falling into the local extreme value dilemma, and realize the multi-dimensional nonlinear optimization of the main grid and the auxiliary grid. The system proposed in this study takes power distribution… More >

Nana Zhang¹, Kun Zhu¹, Shi Ying^{1, *}, Xu Wang²

CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 279-308, 2020, DOI:10.32604/cmc.2020.011001

Abstract Software defect prediction plays an important role in software quality assurance. However, the performance of the prediction model is susceptible to the irrelevant and redundant features. In addition, previous studies mostly regard software defect prediction as a single objective optimization problem, and multi-objective software defect prediction has not been thoroughly investigated. For the above two reasons, we propose the following solutions in this paper: (1) we leverage an advanced deep neural network—Stacked Contractive AutoEncoder (SCAE) to extract the robust deep semantic features from the original defect features, which has stronger discrimination capacity for different classes (defective or non-defective). (2) we… More >

Bao Le Nguyen¹, E. Laxmi Lydia², Mohamed Elhoseny³, Irina V. Pustokhina⁴, Denis A. Pustokhin⁵, Mahmoud Mohamed Selim⁶, Gia Nhu Nguyen^{7, 8}, K. Shankar^{9, *}

CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 87-107, 2020, DOI:10.32604/cmc.2020.011599

Abstract In present digital era, an exponential increase in Internet of Things (IoT) devices poses several design issues for business concerning security and privacy. Earlier studies indicate that the blockchain technology is found to be a significant solution to resolve the challenges of data security exist in IoT. In this view, this paper presents a new privacy-preserving Secure Ant Colony optimization with Multi Kernel Support Vector Machine (ACOMKSVM) with Elliptical Curve cryptosystem (ECC) for secure and reliable IoT data sharing. This program uses blockchain to ensure protection and integrity of some data while it has the technology to create secure ACOMKSVM… More >

N. Ganesh¹, R. K. Ghadai², A. K. Bhoi³, K. Kalita^4,*, Xiao-Zhi Gao⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.2, pp. 459-476, 2020, DOI:10.32604/cmes.2020.09645

Abstract Electrical Discharge Machining (EDM) is a popular non-traditional machining process that is widely used due to its ability to machine hard and brittle materials. It does not require a cutting tool and can machine complex geometries easily. However, it suffers from drawbacks like a poor rate of machining and excessive tool wear. In this research, an attempt is made to address these issues by using an intelligent predictive model coupled global optimization approach to predict suitable combinations of input parameters (current, pulse on-time and pulse off-time) that would effectively increase the material removal rate and minimize the tool wear. The… More >

Kun Fang^{1, 2}, Jianquan Ouyang^{1, *}

Journal on Artificial Intelligence, Vol.2, No.1, pp. 1-15, 2020, DOI:10.32604/jai.2020.09738

Abstract Generating an Adversarial network (GAN) has shown great development prospects in image generation and semi-supervised learning and has evolved into TripleGAN. However, there are still two problems that need to be solved in Triple-GAN: based on the KL divergence distribution structure, gradients are easy to disappear and training instability occurs. Since Triple-GAN tags the samples manually, the manual marking workload is too large. Marked uneven and so on. This article builds on this improved Triple-GAN model (Improved Triple-GAN), which uses Random Forests to classify real samples, automate tagging of leaf nodes, and use Least Squares Generative Adversarial Networks (LSGAN) ideological… More >

Xiaofu Wang^1,*, Xiong Zhang¹, Yan He², Chunming Lian³

Journal of Renewable Materials, Vol.8, No.8, pp. 947-968, 2020, DOI:10.32604/jrm.2020.011327

Abstract In order to solve the problem of urban surface runoff, it is necessary to study permeable brick deeply. Tensile test and DMA test were used to study the binder material of permeable brick, and a material with the best mechanical properties was selected as the binder of resin based permeable brick; The permeable brick with single gradation and continuous gradation and porosity of 0.1–0.5 gradient is constructed by 3D modeling method. The particle composition and the seepage simulation results of permeable brick under different design parameters were analyzed; A resin-based permeable brick with micro-pores was prepared using the selected binder… More >

Bin Xu^{1, 2}, Yong Tang¹, Yi Zhu¹, Wenqing Yan¹, Cheng He³, Jin Qi^{1, *}

CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 2031-2042, 2020, DOI:10.32604/cmc.2020.011149

Abstract Manufacturing service composition of the supply side and scheduling of the demand side are two important components of Cloud Manufacturing, which directly affect the quality of Cloud Manufacturing services. However, the previous studies on the two components are carried out independently and thus ignoring the internal relations and mutual constraints. Considering the two components on both sides of the supply and the demand of Cloud Manufacturing services at the same time, a Bilateral Collaborative Optimization Model of Cloud Manufacturing (BCOM-CMfg) is constructed in this paper. In BCOM-CMfg, to solve the manufacturing service scheduling problem on the supply side, a new… More >

Long Chen¹, Li Xu¹, Kai Wang¹, Baotong Li^2,*, Jun Hong²

CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.1, pp. 203-225, 2020, DOI:10.32604/cmes.2020.09896

Abstract The geometric model and the analysis model can be unified together through the isogeometric analysis method, which has potential to achieve seamless integration of CAD and CAE. Parametric design is a mainstream and successful method in CAD field. This method is not continued in simulation and optimization stage because of the model conversion in conventional optimization method based on the finite element analysis. So integration of the parametric modeling and the structural optimization by using isogeometric analysis is a natural and interesting issue. This paper proposed a method to realize a structural optimization of parametric complex shapes by using isogeometric… More >