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  • Open Access

    ARTICLE

    Improved Ant Colony Optimization and Machine Learning Based Ensemble Intrusion Detection Model

    S. Vanitha1,*, P. Balasubramanie2

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 849-864, 2023, DOI:10.32604/iasc.2023.032324 - 29 September 2022

    Abstract Internet of things (IOT) possess cultural, commercial and social effect in life in the future. The nodes which are participating in IOT network are basically attracted by the cyber-attack targets. Attack and identification of anomalies in IoT infrastructure is a growing problem in the IoT domain. Machine Learning Based Ensemble Intrusion Detection (MLEID) method is applied in order to resolve the drawback by minimizing malicious actions in related botnet attacks on Message Queue Telemetry Transport (MQTT) and Hyper-Text Transfer Protocol (HTTP) protocols. The proposed work has two significant contributions which are a selection of features… More >

  • Open Access

    ARTICLE

    Memory-Type Control Charts Through the Lens of Cost Parameters

    Sakthiseswari Ganasan1, You Huay Woon2,*, Zainol Mustafa1, Dadasaheb G. Godase3

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 1-10, 2023, DOI:10.32604/iasc.2023.032062 - 29 September 2022

    Abstract A memory-type control chart utilizes previous information for chart construction. An example of a memory-type chart is an exponentially-weighted moving average (EWMA) control chart. The EWMA control chart is well-known and widely employed by practitioners for monitoring small and moderate process mean shifts. Meanwhile, the EWMA median chart is robust against outliers. In light of this, the economic model of the EWMA and EWMA median control charts are commonly considered. This study aims to investigate the effect of cost parameters on the out-of-control average run length in implementing EWMA and EWMA median control charts. The… More >

  • Open Access

    ARTICLE

    Change Point Detection for Process Data Analytics Applied to a Multiphase Flow Facility

    Rebecca Gedda1,*, Larisa Beilina2, Ruomu Tan3

    CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.3, pp. 1737-1759, 2023, DOI:10.32604/cmes.2022.019764 - 20 September 2022

    Abstract Change point detection becomes increasingly important because it can support data analysis by providing labels to the data in an unsupervised manner. In the context of process data analytics, change points in the time series of process variables may have an important indication about the process operation. For example, in a batch process, the change points can correspond to the operations and phases defined by the batch recipe. Hence identifying change points can assist labelling the time series data. Various unsupervised algorithms have been developed for change point detection, including the optimisation approach which minimises a… More > Graphic Abstract

    Change Point Detection for Process Data Analytics Applied to a Multiphase Flow Facility

  • Open Access

    ARTICLE

    Numerical Analysis of the Erosion Mechanism inside the Tube Sockets of Main Steam Thermometers in a Coal-Fired Power Plant

    Yukun Lv1, Fan Yang1,*, Zi’an Wei1, Quan Lu2

    FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.2, pp. 379-397, 2023, DOI:10.32604/fdmp.2022.020373 - 29 August 2022

    Abstract Leakage occurring in the tube sockets of the main steam thermometers can seriously threaten the safe operation of coal-fired power plants. Here, assuming a 300 MW unit as a relevant testbed, this problem is investigated numerically through solution of the equations of fluid-dynamics in synergy with the mathematical treatment of relevant statistics. The results indicate that the steam can form a large-scale spiral flow inside the tube socket and continuously scour the inner wall. In the model with the protective casing setting angle of 60°, the average tangential fluid velocity can reach up to 4.8 m/s,… More > Graphic Abstract

    Numerical Analysis of the Erosion Mechanism inside the Tube Sockets of Main Steam Thermometers in a Coal-Fired Power Plant

  • Open Access

    ARTICLE

    Iris Recognition Based on Multilevel Thresholding Technique and Modified Fuzzy c-Means Algorithm

    Slim Ben Chaabane1,2,*, Rafika Harrabi1,2, Anas Bushnag1, Hassene Seddik2

    Journal on Artificial Intelligence, Vol.4, No.4, pp. 201-214, 2022, DOI:10.32604/jai.2022.032850 - 25 May 2023

    Abstract Biometrics represents the technology for measuring the characteristics of the human body. Biometric authentication currently allows for secure, easy, and fast access by recognizing a person based on facial, voice, and fingerprint traits. Iris authentication is one of the essential biometric methods for identifying a person. This authentication type has become popular in research and practical applications. Unlike the face and hands, the iris is an internal organ, protected and therefore less likely to be damaged. However, the number of helpful information collected from the iris is much greater than the other biometric human organs.… More >

  • Open Access

    ARTICLE

    Swarming Computational Efficiency to Solve a Novel Third-Order Delay Differential Emden-Fowler System

    Wajaree Weera1, Zulqurnain Sabir2, Muhammad Asif Zahoor Raja3, Sakda Noinang4, Thongchai Botmart1,*

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4833-4849, 2022, DOI:10.32604/cmc.2022.030888 - 28 July 2022

    Abstract The purpose of this research is to construct an integrated neuro swarming scheme using the procedures of the artificial neural networks (ANNs) with the use of global search particle swarm optimization (PSO) along with the competent local search interior-point programming (IPP) called as ANN-PSOIPP. The proposed computational scheme is implemented for the numerical simulations of the third order nonlinear delay differential Emden-Fowler model (TON-DD-EFM). The TON-DD-EFM is based on two types along with the particulars of shape factor, delayed terms, and singular points. A merit function is performed using the optimization of PSOIPP to find More >

  • Open Access

    ARTICLE

    Optimal Logistics Activities Based Deep Learning Enabled Traffic Flow Prediction Model

    Basim Aljabhan1, Mahmoud Ragab2,3,4,*, Sultanah M. Alshammari4,5, Abdullah S. Al-Malaise Al-Ghamdi4,6,7

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5269-5282, 2022, DOI:10.32604/cmc.2022.030694 - 28 July 2022

    Abstract Traffic flow prediction becomes an essential process for intelligent transportation systems (ITS). Though traffic sensor devices are manually controllable, traffic flow data with distinct length, uneven sampling, and missing data finds challenging for effective exploitation. The traffic data has been considerably increased in recent times which cannot be handled by traditional mathematical models. The recent developments of statistic and deep learning (DL) models pave a way for the effectual design of traffic flow prediction (TFP) models. In this view, this study designs optimal attention-based deep learning with statistical analysis for TFP (OADLSA-TFP) model. The presented… More >

  • Open Access

    ARTICLE

    Swarming Computational Techniques for the Influenza Disease System

    Sakda Noinang1, Zulqurnain Sabir2, Gilder Cieza Altamirano3, Muhammad Asif Zahoor Raja4, Manuel Jesús Sànchez-Chero5, María-Verónica Seminario-Morales5, Wajaree Weera6,*, Thongchai Botmart6

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4851-4868, 2022, DOI:10.32604/cmc.2022.029437 - 28 July 2022

    Abstract The current study relates to designing a swarming computational paradigm to solve the influenza disease system (IDS). The nonlinear system’s mathematical form depends upon four classes: susceptible individuals, infected people, recovered individuals and cross-immune people. The solutions of the IDS are provided by using the artificial neural networks (ANNs) together with the swarming computational paradigm-based particle swarm optimization (PSO) and interior-point scheme (IPA) that are the global and local search approaches. The ANNs-PSO-IPA has never been applied to solve the IDS. Instead a merit function in the sense of mean square error is constructed using More >

  • Open Access

    ARTICLE

    Research on Spatial Statistical Downscaling Method of Meteorological Data Applied to Photovoltaic Prediction

    Yan Jin1,*, Dingmei Wang2, Ruiping Zhang1, Haiying Dong1

    Energy Engineering, Vol.119, No.5, pp. 1923-1940, 2022, DOI:10.32604/ee.2022.018750 - 21 July 2022

    Abstract Aiming at the low spatial resolution of meteorological data output from a numerical model in photovoltaic power prediction, a geographically weighted statistical downscaling method considers the influence factors such as normalized vegetation index (NDVI), digital elevation model (DEM), slope direction, longitude and latitude is proposed. This method is based on the correlation between meteorological data and NDVI, DEM, slope direction, latitude and longitude, and introduces DEM and local Moran index to improve the regression model, and obtains 100 * 100 m high-resolution meteorological spatial distribution data. Finally, combining the measured data of the study area and More >

  • Open Access

    ARTICLE

    Single Point Cutting Tool Fault Diagnosis in Turning Operation Using Reduced Error Pruning Tree Classifier

    E. Akshay1, V. Sugumaran1,*, M. Elangovan2

    Structural Durability & Health Monitoring, Vol.16, No.3, pp. 255-270, 2022, DOI:10.32604/sdhm.2022.0271 - 18 July 2022

    Abstract Tool wear is inevitable in daily machining process since metal cutting process involves the chip rubbing the tool surface after it has been cut by the tool edge. Tool wear dominantly influences the deterioration of surface finish, geometric and dimensional tolerances of the workpiece. Moreover, for complete utilization of cutting tools and reduction of machine downtime during the machining process, it becomes necessary to understand the development of tool wear and predict its status before happening. In this study, tool condition monitoring system was used to monitor the behavior of a single point cutting tool… More >

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