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44 results for “vector evaluated”

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Research ArticleOpen accessIn the abstractMoney Laundering Detection in Financial Institutions Using Machine LearningNoor Samer Masood, Rasha Hassan Sakr, Amal Abou EleneenThis research aims to develop a system based on machine learning techniques for the accurate detection and classification of money laundering transactions. This system utilizes real and synthetic financial data, including the IBM AML dataset and synthetic financial databases. The methodology included data collection and cleaning, feature extraction from transaction behavior, and training several classification algorithms, including Random Forest, Support … …Journal of Computer Science, Vol. 22, Issue 4 · 16 Apr 2026 · 2,325 accessesView PDFCite
Research ArticleOpen accessIn the abstractTwitter Sentiment Analysis Using Machine Learning and Deep Learning TechniquesSafa Khalid Al Sarayrah, Noor Mahmoud Alkudah, Hesham Yousef Al-kharabshehThis research investigates the use of Machine Learning (ML) and Deep Learning, including BiLSTM approaches, for Sentiment Analysis (SA) of consumer reviews on social media sites. Businesses are increasingly depending on online reviews to determine customer satisfaction due to social media's explosive growth. We used three classification models, the assessment of these attitudes uses Naive Bayes (NB), Support Vector Machine … …Journal of Computer Science, Vol. 21, Issue 8 · 1 Sep 2025 · 6,813 accessesView PDFCite
Research ArticleOpen accessIn the abstractEcological Function Evaluation of Soil and Water Conservation Measures for Power Transmission and Transformation Project Construction Based on Remote Sensing and it’s Improvement PathYang Han, Songsong Wang, Yanhui Yang et al.Assessing ecological functions is critical for determining the efficacy of soil and water conservation measures, especially during the development of power transmission and transformation projects. Efficient conservation practices are essential for reducing ecological effects and guaranteeing sustainable development. This research aims to create a resilient model, Ecological Function Prediction for Conservation Effectiveness (EFP-CE) that will classify conservation effectiveness as either … …American Journal of Engineering and Applied Sciences, Vol. 18, Issue 1 · 17 Mar 2025 · 7,725 accessesView PDFCite
Research ArticleOpen accessIn the abstractSupervised Machine Learning Model-Based Approach for Performance Prediction of StudentsAbdul Razaque, Abrar M. AlajlanPredicting students’ performance is one of the crucial issue for learning contexts, since it helps to develop alternative recommendation systems for academically weak students. Thus, several methods and practices have been applied for educational improvement. However, most of the existing methods do not determine the performance of the students. In this study, we have studied the execution of six machine … …Journal of Computer Science, Vol. 16, Issue 8 · 28 Aug 2020 · 7,082 accessesView PDFCite
Research ArticleOpen accessIn the abstractStudy and Analysis of Prediction Model for Heart Disease Data Using Machine Learning TechniquesB. Santhi, K. RenukaHeart disease is the number one cause of death for all communities of individuals in advanced countries and a major problem for emerging nations too. Doctors’ availability to care for the general population could not catch up with the present demand for healthcare. So, there is a severe need for a support system to assist save individuals. With novel ML … …Journal of Computer Science, Vol. 16, Issue 3 · 26 Mar 2020 · 7,784 accessesView PDFCite
Research ArticleOpen accessIn the abstractOnline Handwritten Physics Expression Recognition Using a CRNN-LSTM ApproachUjwala Pritam Kolte, Sachin Arun NaikOptical Character Recognition (OCR) is crucial for identifying and extracting information from scientific documents. However, recognizing online handwritten physics expressions remains a relatively unexplored area of research. In the existing literature, most of the researchers worked on CNN classification to identify mathematical expressions. The traditional Convolution Neural Network (CNN) has limitations for extracting sequential data. This study proposes a CRNN … …Journal of Computer Science, Vol. 21, Issue 2 · 31 Dec 2024 · 4,812 accessesView PDFCite
Research ArticleOpen accessIn the abstractEscalating SVM-Efficiency by Sequential QP LP and Slack Variable AnalysisAmit Kumar Kundu, Rezaul Karim, Ali Ahmed AveSupport Vector Machine (SVM) is a highly attractive algorithm among many machine learning models due to its generalization power and classification performance based on sound mathematical formulation being convex that offers global minimum. However, despite being sparse, its high classification cost from kernel execution with Support Vectors (SVs) reduces the user's interest when there are hard computational constraints in the … …Journal of Computer Science, Vol. 19, Issue 10 · 6 Sep 2023 · 5,913 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparison Between Selective Sampling and Random Undersampling for Classification of Customer Defection Using Support Vector MachineHeri Kuswanto, Yogi Sarumaha, Hayato OhwadaQuality of a product determines the customer loyalty and it can be measured by conducting a survey. Company ‘X’ that sells three kinds of product (low, medium and high price) collected very large dataset through an online survey and recorded customer defection and their characteristic. The measured variables are Update Accumulation, Product Price, Customer Type, Delivery Status and Customer Defection. … …Journal of Computer Science, Vol. 13, Issue 8 · 16 Aug 2017 · 7,263 accessesView PDFCite
Research ArticleOpen accessIn the abstractMulti-Phase Support Vector Regression Soft Sensor for Online Product Quality Prediction in Glutamate Fermentation ProcessRongjian Zheng, Feng PanGlutamate fermentation is inherently nonlinear, multi-phase and an aerobic fermentation process. As long measurement delays and expensive apparatus cost, on-line measurement of the product concentration is not necessarily available. The present fermentation process monitoring and quality prediction involve manual interpretation of highly informative, however, the concentrations of substrates, biomass and products are only low frequency off-line measurements. In this paper, … …American Journal of Biochemistry and Biotechnology, Vol. 13, Issue 2 · 6 Jun 2017 · 8,067 accessesView PDFCite
Research ArticleOpen accessIn the abstractClassification of Breast Tumor in Mammogram Images Using Unsupervised Feature LearningAidarus M. Ibrahim, Baharum Baharudin, Abas Md Said, P. N. HashimahIn this study, we propose a learning-based approach using feature learning to minimize the manual effort required to extract features. Firstly, we extracted features from equally spaced sub-patches covering the input Region of Interest (ROI). The dimensionality of the extracted features is reduced using max-pooling. Furthermore, spherical k-means clustering coupled with max pooling (k-means-max pooling) is compared with well-known feature … …American Journal of Applied Sciences, Vol. 13, Issue 5 · 13 May 2016 · 7,497 accessesView PDFCite