Journals / IASC / Vol.25, No.3


    BDI Agent and QPSO-based Parameter Optimization for a Marine Generator Excitation Controller

    Wei Zhang1, Weifeng Shi2, Bing Sun3
    Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 423-431, 2019, DOI:10.31209/2018.100000045
    Abstract An intelligent optimization algorithm for a marine generator excitation controller is proposed to improve dynamic performance of shipboard power systems. This algorithm combines a belief–desire–intention agent with a quantum-behaved particle swarm optimization (QPSO) algorithm to optimize a marine generator excitation controller. The shipboard zonal power system is simulated under disturbance due to load change or severe fault. The results show that the proposed optimization algorithm can improve marine generator stability compared with conventional excitation controllers under various operating conditions. Moreover, the proposed intelligent algorithm is highly robust because its performance is insensitive to the accuracy of system parameters. More >


    Development of Available Transfer Capability Enhancement Using Intelligent Genetic Algorithm for IEEE Bus System

    R. Rohini1, Dasari Narasimha Rao2, S. Ravi3, V. Sampath Kumar4
    Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 433-440, 2019, DOI:10.31209/2018.100000015
    Abstract Improving Available Transfer Capability is an important issue in the deregulated power systems. The Available Transfer Capability of a transmission network is the transfer capabilities of a transmission network for the transfer of power for further commercial activity, over and above already committed usage. It is a proven fact that Flexible Alternating Current Transmission System technology can control voltage magnitude, phase angle, and circuit reactance. Therefore, it is important to investigate the impact of Flexible Alternating Current Transmission System controllers on the available transfer capability. This paper is focuses on the evaluation impact of Thyristor controlled switched capacitors and static… More >


    Design and Implementation of an Intelligent Ultrasonic Cleaning Device

    Fecir Duran1, Mustafa Teke2
    Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 441-449, 2019, DOI:10.31209/2018.11006161
    Abstract Ultrasonic cleaners are devices that perform ultrasonic cleaning by using ultrasonic converters. Ultrasonic cleaners have been employed to clean dirty and rusty materials such as optic, jewelers, automotive and dental prosthesis sectors. Due to non-identified correctly cleaning time, cavitation erosion has been occurred at some materials, which desire for cleaning. In this study, an intelligent cleaning device that runs autonomously identified cleaning time, saves energy, and makes the cleaning process safely has been designed and implemented. An ultrasonic cleaning time has been adjusted automatically by monitoring of turbidity and conductivity values of liquid that is put in to the cleaning… More >


    Intelligent Service Robot Vision Control Using Embedded System

    Li-Hong Juang1, Shengxiang Zhang2
    Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 451-458, 2019, DOI:10.31209/2019.100000126
    Abstract Intelligent robots are the combination of computer engineering, software engineering, control engineering, electronic engineering, mechanical engineering, and systems design engineering in order to design, and manufacture useful products. In this paper, the author derives some novel computing and algorithm applications on computer vision and image processing and intelligent control and navigation of mobile robots for the intelligent service robot system. In this paper, we proposed an idea of flexible design for a intelligent service robot, which refers to a single robot with a variety of flexure structure. We presented an integrated system for vision-guided finding the person and completing obstacle… More >


    Balanced GHM Mutiwavelet Transform Based Contrast Enhancement Technique for Dark Images Using Dynamic Stochastic Resonance

    S. Deivalakshmi*, P. Palanisamy1, X. Z. Gao2
    Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 459-471, 2019, DOI:10.31209/2018.100000001
    Abstract The main aim of this paper is to propose a new technique for enhancing the contrast of dark images using Dynamic Stochastic Resonance (DSR) and Multi Wavelet Transform (MWT), which is computationally more efficient than the conventional methods. In the work, for enhancing the contrast of dark images, the intrinsic noise (darkness) of dark images has been used. The proposed MWT-based DSR scheme (MWT-DSR) can yield better performances in terms of visual information and color preservation than already reported techniques. The desired output response is validated by the Relative Contrast Enhancement Factor (F), Perceptual Quality Measures (PQM) and Color Enhancement… More >


    Accurate Location Prediction of Social‐Users Using mHMM

    Ahsan Hussain, Bettahally N. Keshavamurthy, Ravi Prasad K. Jagannath
    Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 473-486, 2019, DOI:10.31209/2018.11007092
    Abstract Prediction space of distinct check-in locations in Location-Based Social Networks is a challenge. In this paper, a thorough analysis of Foursquare Check-ins is done. Based on previous check-in sequences, next location of social-users is accurately predicted using multinomial-Hidden Markov Model (mHMM) with Steady-State probabilities. This information benefits security-agencies in tracking suspects and restaurant-owners to predict their customers’ arrivals at different venues on given days. Higher accuracy and Steady-State venuepopularities obtained for location-prediction using the proposed method, outperform various other baseline methods. More >


    MTN Optimal Control of SISO Nonlinear Time-varying Discrete-time Systems for Tracking by Output Feedback*

    Hong-Sen Yan1,2, Jiao-Jun Zhang1,2, Qi-Ming Sun1,2
    Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 487-507, 2019, DOI:10.31209/2018.100000037
    Abstract MTN optimal control scheme of SISO nonlinear time-varying discrete-time systems based on multi-dimensional Taylor network (MTN) is proposed to achieve the real-time output tracking control for a given reference signal. Firstly, an ideal output signal is selected and Pontryagin minimum principle adopted to obtain the numerical solution of the optimal control law for the system relative to the ideal output signal, with the corresponding optimal output termed as desired output signal. Then, MTN optimal controller (MTNC) is generated automatically to fit the optimal control law, and the conjugate gradient (CG) method is employed to train the weight parameters of MTNC… More >


    Special Section on Big Data and Service Computing  

    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 >


    A Novel Service Recommendation Approach in Mashup Creation

    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 >


    Numerical Optimization Algorithm for Unsteady Flows of Rotor Based on Web Service

    Jilin Zhang1,4,5, Xuechao Liu1,5, Jian Wan2,1,5, Yongjian Ren1,5, Binglin Xu1,5, Jianfan He1,5, Yuchen Fan1,5, Li Zhou1,5, 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 >


    Applying Probabilistic Model Checking to Path Planning in an Intelligent Transportation System Using Mobility Trajectories and Their Statistical Data

    Honghao Gao1, 2, 5, Wanqiu Huang1, 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 >


    A New Rockburst Experiment Data Compression Storage Algorithm Based on Big Data Technology

    Yu Zhang1,2, Yan-Ge Wang1, Yan-Ping Bai3, Yong-Zhen Li1,4, 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 >


    The Design and Implementation of a Service Composition System Based on a RESTful API

    Wang Hui1, Sun Guang-Yu2,5, 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 >


    An Efficient Supervised Energy Disaggregation Scheme for Power Service in Smart Grid

    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 >


    A Recommendation Approach Based on Product Attribute Reviews: Improved Collaborative Filtering Considering the Sentiment Polarity

    Min Cao1, Sijing Zhou1, Honghao Gao1,2,3
    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 >


    Virtual Machine Based on Genetic Algorithm Used in Time and Power Oriented Cloud Computing Task Scheduling

    Tongmao Ma1,2, Shanchen Pang1, Weiguang Zhang1, Shaohua Hao1
    Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 605-613, 2019, DOI:10.31209/2019.100000115
    Abstract In cloud computing, task scheduling is a challenging problem in cloud data center, and there are many different kinds of task scheduling strategies. A good scheduling strategy can bring good effectiveness, where plenty of parameters should be regulated to achieve acceptable performance of cloud computing platform. In this work, combined elitist strategy, three parameters values oriented genetic algorithms are proposed. Specifically, a model built by Generalized Stochastic Petri Nets (GSPN) is introduced to describe the process of scheduling in cloud datacenter, and then the workflow of the algorithms is showed. After that, the effectiveness of the algorithms is found to… More >


    Building an Open Cloud Virtual Dataspace Model for Materials Scientific Data

    Yang Li1, Jianjiang Li1, Peng Shi2, Xiaoning Qin3
    Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 615-624, 2019, DOI:10.31209/2019.100000116
    Abstract The applications to process large amounts of materials scientific data at different scales, have been placed the field of materials science on the verge of a revolution. This domain faces serious challenges, including diversity of format of scientific data, and missing unified platform for sharing. A Virtual DataSpace model and the evolution model is introduced to organize heterogeneous data according to the user requirements and track the variations of data. The open cloud model is embedded in a materials scientific data sharing platform in our experiments to verify its effectiveness. The results show the model has made efforts making more… More >


    A Longest Matching Resource Mapping Algorithm with State Compression Dynamic Programming Optimization

    Zhang Min, Teng Haibin, Jiang Ming, Wen Tao, Tang Jingfan
    Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 625-635, 2019, DOI:10.31209/2019.100000117
    Abstract Mapping from sentence phrases to knowledge graph resources is an important step for applications such as search engines, automatic question answering systems based on acknowledge base and knowledge graphs. The existing solution maps a simple phrase to a knowledge graph resource strictly or approximately from the text. However, it is difficult to detect phrases and map the composite semantic resource. This paper proposes a longest matching resource mapping scheme to solve this problem, namely, to find the longest substring in a sentence that can match the knowledge base resource. Based on this scheme, we propose an optimization algorithm based on… More >


    Novel Android Malware Detection Method Based on Multi-dimensional Hybrid Features Extraction and Analysis

    Yue Li1, Guangquan Xu2,3, Hequn Xian1,*, Longlong Rao3, Jiangang Shi4,*
    Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 637-647, 2019, DOI:10.31209/2019.100000118
    Abstract In order to prevent the spread of Android malware and protect privacy information from being compromised, this study proposes a novel multidimensional hybrid features extraction and analysis method for Android malware detection. This method is based primarily on a multidimensional hybrid features vector by extracting the information of permission requests, API calls, and runtime behaviors. The innovation of this study is to extract greater amounts of static and dynamic features information and combine them, that renders the features vector for training completer and more comprehensive. In addition, the feature selection algorithm is used to further optimize the extracted information to… More >

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