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 >

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 >

T. Manikandan¹, S. Karthikeyan^2,*, 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 >

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 >

Siva Sankari Subbiah¹, Senthil Kumar Paramasivan^2,*, 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 >

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 >

S. Sridhar^1,*, 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 >

S. J. K. Jagadeesh Kumar¹, P. Parthasarathi², Mehedi Masud³, Jehad F. Al-Amri⁴, Mohamed Abouhawwash^5,6,*

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 >

Junhua Xi¹, Kouquan Zheng¹, Yifan Zhong², Longjiang Li³, Zhiping Cai^1,*, 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 >

Jazem Mutared Alanazi, Ahmad Ali AlZubi^*

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3693-3712, 2023, DOI:10.32604/iasc.2023.030287

Abstract Technological advancement has made a significant contribution to the change of the economy and the advancement of humanity. Because it is changing how economic transactions are carried out, the blockchain is one of the technical developments that has a lot of promise for this progress. The public record of the Bitcoin blockchain provides dispersed users with evidence of transaction ownership by publishing all transaction data from block reward transactions to unspent transaction outputs. Attacks on the public ledger, on the other hand, are a result of the fact that all transaction information are exposed. De-anonymization attacks allow users to link… More >