N. Vanitha^1,*, C. R. Rene Robin¹, D. Doreen Hephzibah Miriam²

Computer Systems Science and Engineering, Vol.44, No.3, pp. 2323-2336, 2023, DOI:10.32604/csse.2023.028309

Abstract Abstract: Tropical cyclones (TC) are often associated with severe weather conditions which cause great losses to lives and property. The precise classification of cyclone tracks is significantly important in the field of weather forecasting. In this paper we propose a novel hybrid model that integrates ontology and Support Vector Machine (SVM) to classify the tropical cyclone tracks into four types of classes namely straight, quasi-straight, curving and sinuous based on the track shape. Tropical Cyclone TRacks Ontology (TCTRO) described in this paper is a knowledge base which comprises of classes, objects and data properties that represent the interaction among the… More >

R. Sujitha^*, B. Paramasivan

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1557-1572, 2022, DOI:10.32604/cmc.2022.019323

Abstract With the modernization of machine learning techniques in healthcare, different innovations including support vector machine (SVM) have predominantly played a major role in classifying lung cancer, predicting coronavirus disease 2019, and other diseases. In particular, our algorithm focuses on integrated datasets as compared with other existing works. In this study, parallel-based SVM (P-SVM) and multiclass-based multiple submodels (MMSM-SVM) were used to analyze the optimal classification of lung diseases. This analysis aimed to find the optimal classification of lung diseases with id and stages, such as key-value pairs in MapReduce combined with P-SVM and MMSVM for binary and multiclasses, respectively. For… More >

Jie Liu^a,b,c,d, Xiaodong Fu^d, Jin Liu^a,b,c, Yunchuan Sun^a,e

Intelligent Automation & Soft Computing, Vol.24, No.1, pp. 73-80, 2018, DOI:10.1080/10798587.2016.1267244

Abstract Reviews are contents written by users to express opinions on products or services. The information contained in reviews is valuable to users who are going to make decisions on products or services. However, there are numbers of reviews for popular products, and the quality of reviews is not always good. It’s necessary to pick out reviews, which are in high quality from numbers of reviews to assist user in making decision. In this paper, we collected 21,501 reviews flagged as good from 499,253 products on JD.com. We observed the level of users is an important factor affects the quality of… More >