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  • Open Access

    ARTICLE

    Detection of DDoS Attack in IoT Networks Using Sample Selected RNN-ELM

    S. Hariprasad1,*, T. Deepa1, N. Bharathiraja2

    Intelligent Automation & Soft Computing, Vol.34, No.3, pp. 1425-1440, 2022, DOI:10.32604/iasc.2022.022856

    Abstract The Internet of Things (IoT) is a global information and communication technology which aims to connect any type of device to the internet at any time and in any location. Nowadays billions of IoT devices are connected to the world, this leads to easily cause vulnerability to IoT devices. The increasing of users in different IoT-related applications leads to more data attacks is happening in the IoT networks after the fog layer. To detect and reduce the attacks the deep learning model is used. In this article, a hybrid sample selected recurrent neural network-extreme learning machine (hybrid SSRNN-ELM) algorithm that… More >

  • Open Access

    ARTICLE

    Experimental Analysis of Methods Used to Solve Linear Regression Models

    Mua’ad Abu-Faraj1,*, Abeer Al-Hyari2, Ziad Alqadi3

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5699-5712, 2022, DOI:10.32604/cmc.2022.027364

    Abstract Predicting the value of one or more variables using the values of other variables is a very important process in the various engineering experiments that include large data that are difficult to obtain using different measurement processes. Regression is one of the most important types of supervised machine learning, in which labeled data is used to build a prediction model, regression can be classified into three different categories: linear, polynomial, and logistic. In this research paper, different methods will be implemented to solve the linear regression problem, where there is a linear relationship between the target and the predicted output.… More >

  • Open Access

    ARTICLE

    Background Subtraction in Surveillance Systems Using Local Spectral Histograms and Linear Regression

    S. Hariharan1,*, R. Venkatesan2

    Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 407-422, 2022, DOI:10.32604/iasc.2022.025309

    Abstract Background subtraction is a fundamental and crucial task for computer vision-based automatic video analysis due to various challenging situations that occur in real-world scenarios. This paper presents a novel background subtraction method by estimating the background model using linear regression and local spectral histogram which captures combined spectral and texture features. Different linear filters are applied on the image window centered at each pixel location and the features are captured via these filter responses. Each feature has been approximated by a linear combination of two representative features, each of which corresponds to either a background or a foreground pixel. These… More >

  • Open Access

    ARTICLE

    Forecasting of Trend-Cycle Time Series Using Hybrid Model Linear Regression

    N. Ashwini1,*, V. Nagaveni2, Manoj Kumar Singh3

    Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 893-908, 2022, DOI:10.32604/iasc.2022.022231

    Abstract Forecasting for a time series signal carrying single pattern characteristics can be done properly using function mapping-based principle by a well-designed artificial neural network model. But the performances degraded very much when time series carried the mixture of different patterns characteristics. The level of difficulty increases further when there is a need to predict far time samples. Among several possible mixtures of patterns, the trend-cycle time series is having its importance because of its occurrence in many real-life applications like in electric power generation, fuel consumption and automobile sales. Over the mixed characteristics of patterns, a neural model, suffered heavily… More >

  • Open Access

    ARTICLE

    COVID-19 Pandemic Prediction and Forecasting Using Machine Learning Classifiers

    Jabeen Sultana1,*, Anjani Kumar Singha2, Shams Tabrez Siddiqui3, Guthikonda Nagalaxmi4, Anil Kumar Sriram5, Nitish Pathak6

    Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 1007-1024, 2022, DOI:10.32604/iasc.2022.021507

    Abstract COVID-19 is a novel virus that spreads in multiple chains from one person to the next. When a person is infected with this virus, they experience respiratory problems as well as rise in body temperature. Heavy breathlessness is the most severe sign of this COVID-19, which can lead to serious illness in some people. However, not everyone who has been infected with this virus will experience the same symptoms. Some people develop cold and cough, while others suffer from severe headaches and fatigue. This virus freezes the entire world as each country is fighting against COVID-19 and endures vaccination doses.… More >

  • Open Access

    ARTICLE

    Enrichment of Crop Yield Prophecy Using Machine Learning Algorithms

    R. Kingsy Grace*, K. Induja, M. Lincy

    Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 279-296, 2022, DOI:10.32604/iasc.2022.019947

    Abstract Strong associations exist between the crop productivity and the seasonal, biological, economical causes in natural ecosystems. The linkages like climatic conditions, health of a soil, growth of crop, irrigation, fertilizers, temperature, rainwater, pesticides desired to be preserved in comprehensively managed crop lands which impacts the crop potency. Crop yield prognosis plays a vibrant part in agricultural planning, administration and environs sustainability. Advancements in the field of Machine Learning have perceived novel expectations to improve the prediction performance in Agriculture. Highly gratifying prediction of crop yield helps the majority of agronomists for their rapid decision-making in the choice of crop to… More >

  • Open Access

    ARTICLE

    Characterization and Prediction of Nonlinear Stress-Strain Relation of Geostructures for Seismic Monitoring

    Abdoullah Namdar1,2,3,*

    Structural Durability & Health Monitoring, Vol.15, No.2, pp. 167-182, 2021, DOI:10.32604/sdhm.2021.011127

    Abstract The nonlinearity of the strain energy at an interval period of applying seismic load on the geostructures makes it difficult for a seismic designer to makes appropriate engineering judgments timely. The nonlinear stress and strain analysis of an embankment is needed to evaluate by using a combination of suitable methods. In this study, a large-scale geostructure was seismically simulated and analyzed using the nonlinear finite element method (NFEM), and linear regression method which is a soft computing technique (SC) was applied for evaluating the results of NFEM, and it supports engineering judgment because the design of the geostructures is usually… More >

  • Open Access

    ARTICLE

    Predicted Oil Recovery Scaling-Law Using Stochastic Gradient Boosting Regression Model

    Mohamed F. El-Amin1,5, Abdulhamit Subasi2, Mahmoud M. Selim3,*, Awad Mousa4

    CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2349-2362, 2021, DOI:10.32604/cmc.2021.017102

    Abstract In the process of oil recovery, experiments are usually carried out on core samples to evaluate the recovery of oil, so the numerical data are fitted into a non-dimensional equation called scaling-law. This will be essential for determining the behavior of actual reservoirs. The global non-dimensional time-scale is a parameter for predicting a realistic behavior in the oil field from laboratory data. This non-dimensional universal time parameter depends on a set of primary parameters that inherit the properties of the reservoir fluids and rocks and the injection velocity, which dynamics of the process. One of the practical machine learning (ML)… More >

  • Open Access

    ARTICLE

    Alcoholism Detection by Wavelet Energy Entropy and Linear Regression Classifier

    Xianqing Chen1,2, Yan Yan3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.127, No.1, pp. 325-343, 2021, DOI:10.32604/cmes.2021.014489

    Abstract Alcoholism is an unhealthy lifestyle associated with alcohol dependence. Not only does drinking for a long time leads to poor mental health and loss of self-control, but alcohol seeps into the bloodstream and shortens the lifespan of the body’s internal organs. Alcoholics often think of alcohol as an everyday drink and see it as a way to reduce stress in their lives because they cannot see the damage in their bodies and they believe it does not affect their physical health. As their drinking increases, they become dependent on alcohol and it affects their daily lives. Therefore, it is important… More >

  • Open Access

    ARTICLE

    New Correlations for Determination of Optimum Slope Angle of Solar Collectors

    Ali Khosravi1,*, Oscar Ricardo Sandoval Rodriguez2, Behnam Talebjedi1, Timo Laukkanen1, Juan Jose Garcia Pabon3, Mamdouh El Haj Assad4

    Energy Engineering, Vol.117, No.5, pp. 249-265, 2020, DOI:10.32604/EE.2020.011024

    Abstract The energy coming from solar radiation could be harvested and transformed into electricity through the use of solar-thermal power generation and photovoltaic (PV) power generation. Placement of solar collectors (thermal and photovoltaic) affects the amount of incoming radiation and the absorption rate. In this research, new correlations for finding the monthly optimum slope angle (OSA) on flat-plate collectors are proposed. Twelve equations are developed to calculate the monthly OSA by the linear regression model, for the northern and the southern hemisphere stations from 15° to 55° and –20° to –45°, respectively. Also, a new equation for calculating the yearly tilt… More >

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