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  • Open Access


    Artificial Bee Colony with Cuckoo Search for Solving Service Composition

    Fadl Dahan1,2,*, Abdulelah Alwabel3

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3385-3402, 2023, DOI:10.32604/iasc.2023.030651

    Abstract In recent years, cloud computing has provided a Software As A Service (SaaS) platform where the software can be reused and applied to fulfill complicated user demands according to specific Quality of Services (QoS) constraints. The user requirements are formulated as a workflow consisting of a set of tasks. However, many services may satisfy the functionality of each task; thus, searching for the composition of the optimal service while maximizing the QoS is formulated as an NP-hard problem. This work will introduce a hybrid Artificial Bee Colony (ABC) with a Cuckoo Search (CS) algorithm to untangle service composition problem. The… More >

  • Open Access


    Face Mask and Social Distance Monitoring via Computer Vision and Deployable System Architecture

    Meherab Mamun Ratul, Kazi Ayesha Rahman, Javeria Fazal, Naimur Rahman Abanto, Riasat Khan*

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3641-3658, 2023, DOI:10.32604/iasc.2023.030638

    Abstract The coronavirus (COVID-19) is a lethal virus causing a rapidly infectious disease throughout the globe. Spreading awareness, taking preventive measures, imposing strict restrictions on public gatherings, wearing facial masks, and maintaining safe social distancing have become crucial factors in keeping the virus at bay. Even though the world has spent a whole year preventing and curing the disease caused by the COVID-19 virus, the statistics show that the virus can cause an outbreak at any time on a large scale if thorough preventive measures are not maintained accordingly. To fight the spread of this virus, technologically developed systems have become… More >

  • Open Access


    Arithmetic Optimization with Deep Learning Enabled Churn Prediction Model for Telecommunication Industries

    Vani Haridasan*, Kavitha Muthukumaran, K. Hariharanath

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3531-3544, 2023, DOI:10.32604/iasc.2023.030628

    Abstract Customer retention is one of the challenging issues in different business sectors, and various firms utilize customer churn prediction (CCP) process to retain existing customers. Because of the direct impact on the company revenues, particularly in the telecommunication sector, firms are needed to design effective CCP models. The recent advances in machine learning (ML) and deep learning (DL) models enable researchers to introduce accurate CCP models in the telecommunication sector. CCP can be considered as a classification problem, which aims to classify the customer into churners and non-churners. With this motivation, this article focuses on designing an arithmetic optimization algorithm… More >

  • Open Access


    Adaptive Fuzzy Logic Despeckling in Non-Subsampled Contourlet Transformed Ultrasound Pictures

    T. Manikandan1, S. Karthikeyan2,*, J. Jai Jaganath Babu3, G. Babu4

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 2755-2771, 2023, DOI:10.32604/iasc.2023.030497

    Abstract Signal to noise ratio in ultrasound medical images captured through the digital camera is poorer, resulting in an inaccurate diagnosis. As a result, it needs an efficient despeckling method for ultrasound images in clinical practice and telemedicine. This article proposes a novel adaptive fuzzy filter based on the directionality and translation invariant property of the Non-Sub sampled Contour-let Transform (NSCT). Since speckle-noise causes fuzziness in ultrasound images, fuzzy logic may be a straightforward technique to derive the output from the noisy images. This filtering method comprises detection and filtering stages. First, image regions classify at the detection stage by applying… More >

  • Open Access


    A Novel Approach for Improving the PQ in SPIM

    P. Jenitha Deepa*, H. Habeebullah Sait

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 2703-2715, 2023, DOI:10.32604/iasc.2023.030496

    Abstract Single Phase Induction Motor (SPIM) is widely used in industries at starting stage to provide high starting torque. The objective of the work is to develop a drive for Single Phase Induction Motor that does not use a start or run capacitor. In this work, the researchers present the details about Maximum Power Point Tracking using series-compensated Buck Boost Converter, resonant Direct Current (DC) to Alternate Current (AC) inverter and matrix converter-based drive. The proposed method provides a variable starting torque feature that can be adjusted depending upon machine load to ensure Power Quality (PQ). The system uses Series Compensated… More >

  • Open Access


    Deep Learning for Wind Speed Forecasting Using Bi-LSTM with Selected Features

    Siva Sankari Subbiah1, Senthil Kumar Paramasivan2,*, Karmel Arockiasamy3, Saminathan Senthivel4, Muthamilselvan Thangavel2

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3829-3844, 2023, DOI:10.32604/iasc.2023.030480

    Abstract Wind speed forecasting is important for wind energy forecasting. In the modern era, the increase in energy demand can be managed effectively by forecasting the wind speed accurately. The main objective of this research is to improve the performance of wind speed forecasting by handling uncertainty, the curse of dimensionality, overfitting and non-linearity issues. The curse of dimensionality and overfitting issues are handled by using Boruta feature selection. The uncertainty and the non-linearity issues are addressed by using the deep learning based Bi-directional Long Short Term Memory (Bi-LSTM). In this paper, Bi-LSTM with Boruta feature selection named BFS-Bi-LSTM is proposed… More >

  • Open Access


    Prediction of Suitable Crops Using Stacked Scaling Conjugant Neural Classifier

    P. Nithya*, A. M. Kalpana

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3743-3755, 2023, DOI:10.32604/iasc.2023.030394

    Abstract Agriculture plays a vital role in economic development. The major problem faced by the farmers are the selection of suitable crops based on environmental conditions such as weather, soil nutrients, etc. The farmers were following ancestral patterns, which could sometimes lead to the wrong selection of crops. In this research work, the feature selection method is adopted to improve the performance of the classification. The most relevant features from the dataset are obtained using a Probabilistic Feature Selection (PFS) approach, and classification is done using a Neural Fuzzy Classifier (NFC). Scaling Conjugate Gradient (SCG) optimization method is used to update… More >

  • Open Access


    Content-Based Movie Recommendation System Using MBO with DBN

    S. Sridhar1,*, D. Dhanasekaran2, G. Charlyn Pushpa Latha3

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3241-3257, 2023, DOI:10.32604/iasc.2023.030361

    Abstract The content-based filtering technique has been used effectively in a variety of Recommender Systems (RS). The user explicitly or implicitly provides data in the Content-Based Recommender System. The system collects this data and creates a profile for all the users, and the recommendation is generated by the user profile. The recommendation generated via content-based filtering is provided by observing just a single user’s profile. The primary objective of this RS is to recommend a list of movies based on the user’s preferences. A content-based movie recommendation model is proposed in this research, which recommends movies based on the user’s profile… More >

  • Open Access


    Butterfly Optimized Feature Selection with Fuzzy C-Means Classifier for Thyroid Prediction

    S. J. K. Jagadeesh Kumar1, P. Parthasarathi2, Mehedi Masud3, Jehad F. Al-Amri4, Mohamed Abouhawwash5,6,*

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 2909-2924, 2023, DOI:10.32604/iasc.2023.030335

    Abstract The main task of thyroid hormones is controlling the metabolism rate of humans, the development of neurons, and the significant growth of reproductive activities. In medical science, thyroid disorder will lead to creating thyroiditis and thyroid cancer. The two main thyroid disorders are hyperthyroidism and hypothyroidism. Many research works focus on the prediction of thyroid disorder. To improve the accuracy in the classification of thyroid disorder this paper proposes optimization-based feature selection by using differential evolution with the Butterfly optimization algorithm (DE-BOA). For the classifier fuzzy C-means algorithm (FCM) is used. The proposed DEBOA-FCM is evaluated with parametric metric measures… More >

  • Open Access


    Robust Symmetry Prediction with Multi-Modal Feature Fusion for Partial Shapes

    Junhua Xi1, Kouquan Zheng1, Yifan Zhong2, Longjiang Li3, Zhiping Cai1,*, Jinjing Chen4

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3099-3111, 2023, DOI:10.32604/iasc.2023.030298

    Abstract In geometry processing, symmetry research benefits from global geometric features of complete shapes, but the shape of an object captured in real-world applications is often incomplete due to the limited sensor resolution, single viewpoint, and occlusion. Different from the existing works predicting symmetry from the complete shape, we propose a learning approach for symmetry prediction based on a single RGB-D image. Instead of directly predicting the symmetry from incomplete shapes, our method consists of two modules, i.e., the multi-modal feature fusion module and the detection-by-reconstruction module. Firstly, we build a channel-transformer network (CTN) to extract cross-fusion features from the RGB-D… More >

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