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  • Open Access

    ARTICLE

    Quad-Rotor Directional Steering System Controller Design Using Gravitational Search Optimization

    M. A. Kamela, M. A. Abidob, Moustafa Elshafeic

    Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 795-805, 2018, DOI:10.1080/10798587.2017.1342414

    Abstract Directional Steering System (DSS) has been established for well drilling in the oilfield in order to accomplish high reservoir productivity and to improve accessibility of oil reservoirs in complex locations. In this paper, a novel feedback linearization controller to cancel the nonlinear dynamics of a DSS is proposed. The proposed controller design problem is formulated as an optimization problem for optimal settings of the controller feedback gains. Gravitational Search Algorithm (GSA) is developed to search for optimal settings of the proposed controller. The objective function considered is to minimize the tracking error and drilling efforts. In this study, the DSS… More >

  • Open Access

    ARTICLE

    Feature Selection for Activity Recognition from Smartphone Accelerometer Data

    Juan C. Quiroza, Amit Banerjeeb, Sergiu M. Dascaluc, Sian Lun Laua

    Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 785-793, 2018, DOI:10.1080/10798587.2017.1342400

    Abstract We use the public Human Activity Recognition Using Smartphones (HARUS) data-set to investigate and identify the most informative features for determining the physical activity performed by a user based on smartphone accelerometer and gyroscope data. The HARUS data-set includes 561 time domain and frequency domain features extracted from sensor readings collected from a smartphone carried by 30 users while performing specific activities. We compare the performance of a decision tree, support vector machines, Naive Bayes, multilayer perceptron, and bagging. We report the various classification performances of these algorithms for subject independent cases. Our results show that bagging and the multilayer… More >

  • Open Access

    ARTICLE

    Improving Performance Prediction on Education Data with Noise and Class Imbalance

    Akram M. Radwana,b, Zehra Cataltepea,c

    Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 777-783, 2018, DOI:10.1080/10798587.2017.1337673

    Abstract This paper proposes to apply machine learning techniques to predict students’ performance on two real-world educational data-sets. The first data-set is used to predict the response of students with autism while they learn a specific task, whereas the second one is used to predict students’ failure at a secondary school. The two data-sets suffer from two major problems that can negatively impact the ability of classification models to predict the correct label; class imbalance and class noise. A series of experiments have been carried out to improve the quality of training data, and hence improve prediction results. In this paper,… More >

  • Open Access

    ARTICLE

    Output Consensus of Heterogeneous Multi-agent Systems under Directed Topologies via Dynamic Feedback

    Xiaofeng Liu, Siqi An, Dongxu Zhang

    Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 771-775, 2018, DOI:10.1080/10798587.2017.1337667

    Abstract This paper discusses the problem of dynamic output consensus for heterogeneous multi-agent systems (MAS) with fixed topologies. All the agents possess unique linear dynamics, and only the output information of each agent is delivered throughout the communication digraphs. A series of conditions and protocols are set for reaching the consensus. With the proper feedback controllers, the output consensus of the overall system is guaranteed. An application illustrates the theorems. More >

  • Open Access

    ARTICLE

    Performance Analyses of Nature-inspired Algorithms on the Traveling Salesman’s Problems for Strategic Management

    Julius Beneoluchi Odilia, Mohd Nizam Mohmad Kahara, A. Noraziaha,b, M. Zarinac, Riaz Ul Haqa

    Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 759-769, 2018, DOI:10.1080/10798587.2017.1334370

    Abstract This paper carries out a performance analysis of major Nature-inspired Algorithms in solving the benchmark symmetric and asymmetric Traveling Salesman’s Problems (TSP). Knowledge of the workings of the TSP is very useful in strategic management as it provides useful guidance to planners. After critical assessments of the performances of eleven algorithms consisting of two heuristics (Randomized Insertion Algorithm and the Honey Bee Mating Optimization for the Travelling Salesman’s Problem), two trajectory algorithms (Simulated Annealing and Evolutionary Simulated Annealing) and seven population-based optimization algorithms (Genetic Algorithm, Artificial Bee Colony, African Buffalo Optimization, Bat Algorithm, Particle Swarm Optimization, Ant Colony Optimization and… More >

  • Open Access

    ARTICLE

    Analysis of Collaborative Brain Computer Interface (BCI) Based Personalized GUI for Differently Abled

    M. Umaa,c, T. Sheelab

    Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 747-757, 2018, DOI:10.1080/10798587.2017.1332804

    Abstract Brain-Computer Interfaces (BCI) use Electroencephalography (EEG) signals recorded from the brain scalp, which enable a communication between the human and the outside world. The present study helps the patients who are people locked-in to manage their needs such as accessing of web url’s, sending/receiving sms to/from mobile device, personalized music player, personalized movie player, wheelchair control and home appliances control. In the proposed system, the user needs are designed as a button in the form of a matrix, in which the main panel of rows and columns button is flashed in 3 sec intervals. Subjects were asked to choose the… More >

  • Open Access

    ARTICLE

    Hierarchical Optimization of Network Resource for Heterogeneous Service in Cloud Scenarios

    Dong Huanga,b, Yong Baib, Jingcheng Liuc, Hongtao Chend, Jinghua Lind, Jingjing Wud

    Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 883-889, 2018, DOI:10.1080/10798587.2017.1327634

    Abstract With limited homogeneous and heterogeneous resources in a cloud computing system, it is not feasible to successively expand network infrastructure to adequately support the rapid growth in the cloud service. In this paper, an approach for optimal transmission of hierarchical network for heterogeneous service in Cloud Scenarios was presented. Initially, the theoretical optimal transmission model of a common network was transformed into the hierarchical network with the upper and lower optimization transmission model. Furthermore, the computation simplification and engineering transformation were presented for an approximation method at the low cost of computational complexity. In the final section, the average delay… More >

  • Open Access

    ARTICLE

    Portrait Vision Fusion for Augmented Reality

    Li-Hong Juanga, Ming-Ni Wub, Feng-Mao Tsoub

    Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 739-745, 2018, DOI:10.1080/10798587.2017.1327549

    Abstract Kinect(+openCV); Dynamic portrait segmentation; Skeletal tracking; Edge transparent processing; Video interactive More >

  • Open Access

    ARTICLE

    A Novel Strategy for Mining Highly Imbalanced Data in Credit Card Transactions

    Masoumeh Zareapoor, Jie Yang

    Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 721-727, 2018, DOI:10.1080/10798587.2017.1321228

    Abstract The design of an efficient credit card fraud detection technique is, however, particularly challenging, due to the most striking characteristics which are; imbalancedness and non-stationary environment of the data. These issues in credit card datasets limit the machine learning algorithm to show a good performance in detecting the frauds. The research in the area of credit card fraud detection focused on detection the fraudulent transaction by analysis of normality and abnormality concepts. Balancing strategy which is designed in this paper can facilitate classification and retrieval problems in this domain. In this paper, we consider the classification problem in supervised learning… More >

  • Open Access

    ARTICLE

    A Multi Criterion Fuzzy Based Energy Efficient Routing Protocol for Ad hoc Networks

    Geetha N., Sankar A.

    Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 711-719, 2018, DOI:10.1080/10798587.2017.1309003

    Abstract The routing protocol for an ad hoc network should be efficient in utilizing the available resources to prolong the network lifetime. A Multi Criterion Fuzzy based Energy Efficient Routing Protocol (MCFEER) for Ad hoc Networks selects the path on constraints like bandwidth, battery life, hop count and buffer occupancy. In the route discovery phase, fuzzy system is applied for optimal route selection by destination node leading to successful data transmission. Multiple stable paths are preserved in route cache for usage during the route maintenance phase. The results are competitive when compared with Power aware Energy Efficient Routing (PEER) protocol using… More >

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