Qing Ai^1,2,*, Yude Kang¹, Anna Wang²

Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 205-220, 2021, DOI:10.32604/iasc.2021.013357

Abstract Multi-label learning is a meaningful supervised learning task in which each sample may belong to multiple labels simultaneously. Due to this characteristic, multi-label learning is more complicated and more difficult than multi-class classification learning. The multi-label twin support vector machine (MLTSVM) [], which is an effective multi-label learning algorithm based on the twin support vector machine (TSVM), has been widely studied because of its good classification performance. To obtain good generalization performance, the MLTSVM often needs a large number of labelled samples. In practical engineering problems, it is very time consuming and difficult to obtain all labels of all samples… More >

Xiaohong Ji¹, Junjun Du¹, Guoqing Jia^1,*, Weidong Fang^2,3

Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 221-231, 2021, DOI:10.32604/iasc.2021.013145

Abstract Sparse code multiple access (SCMA) is a new non-orthogonal multiple access scheme suitable for 5G communication, which can effectively improve spectrum efficiency and support massive connections. Multiple users in the SCMA system realize the sharing of the same time-frequency resources by mapping data into codewords of a special code book (Code Book, CB). A typical SCMA system increases the spectrum utilization to 150%. In order to further improve the system spectrum utilization and increase the number of user connections, this paper proposes an uplink SCMA codebook reuse transmission and reception scheme (CB-Reuse-SCMA), which reuse a codebook to multiple users. The… More >

Peng Mei¹, Gangyi Ding¹, Qiankun Jin¹, Fuquan Zhang^2,*, Yeh-Cheng Chen³

Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 159-171, 2021, DOI:10.32604/iasc.2021.012813

Abstract Community structure is a key component in complex network systems. This paper aims to improve the effectiveness of community detection and community discovery in complex network systems by providing directions for the reconstruction and optimization of community structures to expand the application of intelligent optimization algorithms in community structures. First, deep learning algorithms and ant colony algorithms are used to elaborate the community detection and community discovery in complex networks. Next, we introduce the technology of transfer learning and propose an algorithm of deep self-encoder modeling based on transfer learning (DSEM-TL). The DSEM-TL algorithm’s indicators include normalized mutual information and… More >

Zejian Zhang¹, Dawei Wang^2,*, Xiao-Zhi Gao³

Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 173-189, 2021, DOI:10.32604/iasc.2021.012805

Abstract The interval type-2 fuzzy sets can describe nonlinear plants with uncertain parameters. It exists in nonlinearity. The parameter uncertainties extensively exist in the nonlinear practical Networked Control Systems (NCSs), and it is paramount to investigate the stabilization of the NCSs on account of the section type-2 fuzzy systems. Notice that most of the existing research work is only on account of the convention Parallel Distribution Compensation (PDC). For overcoming the weak point of the PDC and acquire certain guard stability conditions, the state tickling regulator under imperfect premise matching can be constructed to steady the NCSs using the section type-2… More >

Chunhua Zhou^*, Jianjing Shen, Xiaofeng Guo, Zhenyu Zhou

Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 127-141, 2021, DOI:10.32604/iasc.2021.012532

Abstract In the process of interaction between users and battlefield situation information, combat tasks are the key factors that affect users’ information selection. In order to solve the problems of battlefield situation information recommendation (BSIR) for combat tasks, we propose a task-oriented battlefield situation information hybrid recommendation model (TBSI-HRM) based on tensor factorization and deep learning. In the model, in order to achieve high-precision personalized recommendations, we use Tensor Factorization (TF) to extract correlation relations and features from historical interaction data, and use Deep Neural Network (DNN) to learn hidden feature vectors of users, battlefield situation information and combat tasks from… More >

Tao Ni¹, Lingtao Huang^1,*, Huanfei Zheng², Hongyan Zhang¹

Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 143-158, 2021, DOI:10.32604/iasc.2021.012268

Abstract To overcome the problem that a teleoperation system loses robustness when the target moves outside the robot’s visual field or it is far away from the desired position, and to improve the operability and controllability of a master-slave teleoperation system, we present an image servo based haptic feedback (ISBHF) control method for teleoperating. The ISBHF control method involves extracting target feature points and constructing image servo based virtual force. First, the image characteristics of the environment and targets are identified and extracted by a 3D reconstruction method. A composite image Jacobian matrix is used to construct virtual guidance force based… More >

Qi Chen, Wei Cui^*, Jianqiu Sun, Xingguang Li, Xuyu Tian

Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 115-126, 2021, DOI:10.32604/iasc.2021.011617

Abstract The existing range-Doppler algorithms for SAR imaging are affected by a fast-time Doppler effect so they cannot be directly applied to FMCW SAR. Moreover, range migration is more evident in squint mode. To reveal the influence of the continuous motion of FMCW SAR in the squint mode on the echo signal and optimize the imaging process, an improved range-Doppler algorithm is based on squint FMCW SAR imaging is proposed in this paper. Firstly, the imaging geometry model and echo signal model of FMCW SAR are analyzed and deduced. The problem of Doppler center offset under squint mode is eliminated by… More >

Rizwan Munir^1,*, Yifei Wei¹, Rahim Ullah², Iftikhar Hussain³, Kaleem Arshid⁴, Umair Tariq¹

Journal of Quantum Computing, Vol.2, No.4, pp. 193-202, 2020, DOI:10.32604/jqc.2020.016151

Abstract A smart grid is the evolved form of the power grid with the integration of sensing, communication, computing, monitoring, and control technologies. These technologies make the power grid reliable, efficient, and economical. However, the smartness boosts the volume of data in the smart grid. To obligate full benefits, big data has attractive techniques to process and analyze smart grid data. This paper presents and simulates a framework to make sure the use of big data computing technique in the smart grid. The offered framework comprises of the following four layers: (i) Data source layer, (ii) Data transmission layer, (iii) Data… More >

Saptarshi Sahoo^1,*, Amit Kumar Mandal¹, Pijus Kanti Samanta², Indranil Basu¹, Pratik Roy¹

Journal of Quantum Computing, Vol.2, No.4, pp. 181-192, 2020, DOI:10.32604/jqc.2020.015688

Abstract Quantum Computing and Quantum Information Science seem very promising and developing rapidly since its inception in early 1980s by Paul Benioff with the proposal of quantum mechanical model of the Turing machine and later By Richard Feynman and Yuri Manin for the proposal of a quantum computers for simulating various problems that classical computer could not. Quantum computers have a computational advantage for some problems, over classical computers and most applications are trying to use an efficient combination of classical and quantum computers like Shor’s factoring algorithm. Other areas that are expected to be benefitted from quantum computing are Machine… More >

Dandan Peng, Le Sun^*

Journal of Quantum Computing, Vol.2, No.4, pp. 171-179, 2020, DOI:10.32604/jqc.2020.015402

Abstract The purpose of this work aims is to automatically build top-k (the number of suggested results) light weight service based systems (LitSBSs) on the basis of user-given keywords. Compared with our previous work, we use a score (oscore) to evaluate the keyword matching degree and QoS performance of a service so that we could find top-k LitSBSs with both high keyword matching degree and great QoS performance at the same time. In addition, to guarantee the quality of found top-k LitSBSs and improve the time efficiency, we redesign the database-driven algorithm (LitDB). We add the step of referential services selecting… More >