Min Cao¹, Sijing Zhou¹, Honghao Gao^1,2,3

Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 595-604, 2019, DOI:10.31209/2019.100000114

Abstract Recommender methods using reviews have become an area of active research in e-commerce systems. The use of auxiliary information in reviews as a way to effectively accommodate sparse data has been adopted in many fields, such as the product field. The existing recommendation methods using reviews typically employ aspect preference; however, the characteristics of product reviews are not considered adequate. To this end, this paper proposes a novel recommendation approach based on using product attributes to improve the efficiency of recommendation, and a hybrid collaborative filtering is presented. The product attribute model and a new recommendation ranking formula are introduced… More >

Weilie Liu, Jialing He, Meng Li, Rui Jin, Jingjing Hu, Zijian Zhang

Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 585-593, 2019, DOI:10.31209/2019.100000113

Abstract Smart energy disaggregation is receiving increasing attention because it can be used to save energy and mine consumer's electricity privacy by decomposing aggregated meter readings. Many smart energy disaggregation schemes have been proposed; however, the accuracy and efficiency of these methods need to be improved. In this work, we consider a supervised energy disaggregation method which initially learns the power consumption of each appliance and then disaggregates meter readings using the previous learning result. In this study, we improved the fast search and find of density peaks clustering algorithm to cluster appliance power signals twice to learn appliance feature matrices.… More >

Wang Hui¹, Sun Guang-Yu^2,5, Zhang Qin-Yan², Liu Kai-Min³, Xi Meng³, Zhang Yuan-Yuan⁴

Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 573-583, 2019, DOI:10.31209/2019.100000112

Abstract With the current explosion of mobile applications and smart devices, more organizations are beginning to expose Web APIs, which makes APIs more widely used. How can these APIs be managed and utilized safely and effectively for businesses? It is not easy to say. Today's Web services mainly include traditional structured WSDL and unstructured RESTful. A RESTful architecture can effectively constrain and help to achieve a simpler, lighter, and more scalable system. How to uniformly organize and merge RESTful APIs is also a problem to be solved. To solve the above problems, this article has designed an API management system that… More >

Yu Zhang^1,2, Yan-Ge Wang¹, Yan-Ping Bai³, Yong-Zhen Li^1,4, Zhao-Yong Lv⁵, Hong-Wei Ding⁶

Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 561-572, 2019, DOI:10.31209/2019.100000111

Abstract Rockburst phenomenon is a kind of phenomenon that the rock is out and ejected because the mineral was dug out, and the original force balance was destroyed in the process of mineral exploitation. From 2007, GeoLab (abbreviation of State Key Laboratory in China for GeoMechanics and Deep Underground Engineering) had made a series of important achievements in rockburst. Up to now, GeoLab’s rockburst experiment data is reached 800T, and these data may occupy about 2PB hard disk space after analyzed. At this ratio, GeoLab need to buy a new hard disk to save all these data every 46 hours rockburst… More >

Honghao Gao^{1, 2, 5}, Wanqiu Huang^{1, 4}, Xiaoxian Yang³

Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 547-559, 2019, DOI:10.31209/2019.100000110

Abstract Path planning is an important topic of research in modern intelligent traffic systems (ITSs). Traditional path planning methods aim to identify the shortest path and recommend this path to the user. However, the shortest path is not always optimal, especially in emergency rescue scenarios. Thus, complex and changeable factors, such as traffic congestion, road construction and traffic accidents, should be considered when planning paths. To address this consideration, the maximum passing probability of a road is considered the optimal condition for path recommendation. In this paper, the traffic network is abstracted as a directed graph. Probabilistic data on traffic flow… More >

Jilin Zhang^1,4,5, Xuechao Liu^1,5, Jian Wan^2,1,5, Yongjian Ren^1,5, Binglin Xu^1,5, Jianfan He^1,5, Yuchen Fan^1,5, Li Zhou^1,5, Zhenguo Wei⁶, Juncong Zhang⁶, Jue Wang³

Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 527-546, 2019, DOI:10.31209/2019.100000109

Abstract A numerical optimization algorithm for unsteady flows of rotor based on web service is proposed. Space discretization uses the finite volume method, time discretization uses the implicit dual-time steps method, and turbulence model uses the Spalart–Allmaras (S–A) model. In order to efficiently use the computing resources of the cluster, a service-oriented service computing architecture is used in a parallel computing service program. In order to realize the load balance of hybrid grid partition, the grid is partitioned by Metis Library. Meanwhile, data communication based on Message Passing Interface (MPI) technology guarantees the consistency of convergence between parallel algorithm and serial… More >

Yanmei Zhang¹, Xiao Geng², Shuiguang Deng³

Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 513-525, 2019, DOI:10.31209/2019.100000108

Abstract With the development of service computing technologies, the online services are massive and disordered now. How to find appropriate services quickly and build a more powerful composed service according to user interests has been a research focus in recent years. Current service recommendation algorithms often directly follow the traditional recommendation framework of ecommerce, which cannot effectively assist users to complete dynamic online business construction. Therefore, a novel service recommendation approach named UISCS (User-Interest- initial Services-Correlation-successor Services) is proposed, which is designed for interactive scenario of service composition, and it mines the user implicit interests and the service correlations for service… More >

Ying Li¹, Honghao Gao², Yueshen Xu³

Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 511-512, 2019, DOI:10.31209/2019.100000107

Abstract This article has no abstract. More >

Caifeng Cheng^1,2, Deshu Lin^3,*

Journal on Internet of Things, Vol.2, No.1, pp. 47-54, 2020, DOI:10.32604/jiot.2020.09117

Abstract In this paper, the observation matrix and reconstruction algorithm of compressed sensing sampling theorem are studied. The advantages and disadvantages of greedy reconstruction algorithm are analyzed. The disadvantages of signal sparsely are preset in this algorithm. The sparsely adaptive estimation algorithm is proposed. The compressed sampling matching tracking algorithm supports the set selection and culling atomic standards to improve. The sparse step size adaptive compressed sampling matching tracking algorithm is proposed. The improved algorithm selects the sparsely as the step size to select the support set atom, and the maximum correlation value. Half of the threshold culling algorithm supports the… More >

Caifeng Cheng^1,2, Deshu Lin^3,*

Journal on Internet of Things, Vol.2, No.1, pp. 37-45, 2020, DOI:10.32604/jiot.2020.09116

Abstract Compressive sensing theory mainly includes the sparsely of signal processing, the structure of the measurement matrix and reconstruction algorithm. Reconstruction algorithm is the core content of CS theory, that is, through the low dimensional sparse signal recovers the original signal accurately. This thesis based on the theory of CS to study further on seismic data reconstruction algorithm. We select orthogonal matching pursuit algorithm as a base reconstruction algorithm. Then do the specific research for the implementation principle, the structure of the algorithm of AOMP and make the signal simulation at the same time. In view of the OMP algorithm reconstruction… More >