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 >

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 >

Hong-Sen Yan^1,2, Jiao-Jun Zhang^1,2, Qi-Ming Sun^1,2

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 >

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 >

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 >

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 >

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 >

Nan Pan¹, Dilin Pan², Yi Liu²

Intelligent Automation & Soft Computing, Vol.25, No.2, pp. 413-419, 2019, DOI:10.31209/2019.100000103

Abstract In order to solve the cutting tools classification problem, a crime tool identification algorithm based on GVF-Harris-SIFT and KNN is put forward. The proposed algorithm uses a gradient vector to smooth the gradient field of the image, and then uses the Harris angle detection algorithm to detect the tool angle. After that, the descriptors of the eigenvectors in corresponding feature points were using SIFT to obtained. Finally, the KNN machine learning algorithms is employed to for classification and recognition. The experimental results of the comparison of the cutting tools show the accuracy and reliability of the algorithm. More >

Yuchi Kang^1,2, Meihong Liu¹, Sharon Kao‐Walter^2,3, Jinbin Liu¹, Qihong Cen⁴

Intelligent Automation & Soft Computing, Vol.25, No.2, pp. 405-411, 2019, DOI:10.31209/2019.100000102

Abstract A two-dimensional model of staggered tube banks of the bristle pack with different pitch ratios was solved by computational fluid dynamics (CFD). The pressure distribution along the gap centerlines and bristle surfaces were studied for different upstream pressure from 0.2 to 0.6MPa and models. The results show that the pressure is exponentially rather than strictly linearly decreasing distributed inside the bristle pack. The pressure distribution is symmetry about the circle’s horizontal line. The most obvious pressure drop occurred from about 60º to 90º. There is no stationary state reached between the kinetic energy and the static pressure when the upstream… More >