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69 results for “K-Nearest Neighbor”
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Research ArticleOpen accessPhrase in the titleA Reformed K-Nearest Neighbors Algorithm for Big Data SetsVo Ngoc Phu, Vo Thi Ngoc TranA Data Mining Has Already Had Many Algorithms Which A K-Nearest Neighbors Algorithm, K-NN, Is A Famous Algorithm For Researchers. K-NN Is Very Effective On Small Data Sets, However It Takes A Lot Of Time To Run On Big Datasets. Today, Data Sets Often Have Millions Of Data Records, Hence, It Is Difficult To Implement K-NN On Big Data. In … …Journal of Computer Science, Vol. 14, Issue 9 · 8 Mar 2018 · 7,473 accessesView PDFCite
Research ArticleOpen accessPhrase in the title3D Object Recognition using Multiclass Support Vector Machine-K-Nearest Neighbor Supported by Local and Global FeatureC. Chandrasekar, R. MuralidharanProblem statement: In this study, a new method has been proposed for the recognition of 3D objects based on the various views of the object. The proposed method is evolved from the two promising methods available for object recognition. Approach: The proposed method uses both the local and global features extracted from the images. For feature extraction, Hu’s Moment invariant … …Journal of Computer Science, Vol. 8, Issue 8 · 4 Aug 2012 · 7,285 accessesView PDFCite
Research ArticleOpen accessPhrase in the titlePerformance Prediction Model for Predictive Maintenance Based on K-Nearest Neighbor Method for Air Navigation Equipment FacilitiesRachmat Hidayat, Ditdit Nugeraha UtamaThe aging of air navigation facilities leads to a decline in equipment performance and reliability, posing significant challenges for aviation organizations in the large-scale replacement of outdated systems, as well as in managing budgets and resources. To address these issues, a performance prediction model for equipment was developed using the K-Nearest Neighbor (KNN) method, aimed at enhancing maintenance planning and … …Journal of Computer Science, Vol. 21, Issue 4 · 4 Mar 2025 · 5,653 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleSecond-Order Statistical Approach for Digital Modulation Scheme Classification in Cognitive Radio Using Support Vector Machine and K-Nearest Neighbor ClassifierS. Ravi, R. KannanCognitive radio systems require detection of different signals for communication. In this study, an approach for multiclass signal classification based on second-order statistical feature is proposed. The proposed system is designed to recognize three different digital modulation schemes such as PAM, 32QAM and 64QAM. The signal classification is achieved by extracting the 2nd order cumulants of the real and imaginary … …Journal of Computer Science, Vol. 9, Issue 2 · 11 Apr 2013 · 6,732 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleFINDING A RESIDENCE WITH ALL FACILITIES USING NEAREST NEIGHBOR SEARCHK. Padmapriya, Dr. S. SridharNearest neighbor search is one of the most widely-used techniques and its applications including mobile communication, Geographic information systems, bioinformatics, computer vision and marketing. For example, four friends want to rent an apartment which should be nearer to their working places. Our paper discussed about the problems on finding the most appropriate location among a set of available places. The … …Journal of Computer Science, Vol. 10, Issue 6 · 1 Feb 2014 · 6,803 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleAn Efficient Bayesian Nearest Neighbor Search Using Marginal Object Weight Ranking Scheme in Spatial DatabasesK. Balasaravanan, K. DuraiswamyProblem statement: A database that is optimized to store and query data that is related to objects in space, including points, lines and polygons is called spatial database. Identifying nearest neighbor object search is a vital part of spatial database. Many nearest neighbor search techniques such as Authenticated Multi-step NN (AMNN), Superseding Nearest Neighbor (SNN) search, Bayesian Nearest Neighbor (BNN) … …Journal of Computer Science, Vol. 8, Issue 8 · 30 Jul 2012 · 7,149 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleSelective Flooding Based on Relevant Nearest-Neighbor using Query Feedback and Similarity across Unstructured Peer-to-Peer NetworksIskandar Ishak, Naomie SalimProblem statement: Efficient searching is a fundamental problem for unstructured peer to peer networks. Flooding requires a lot of resources in the network and thus will increase the search cost. Searching approach that utilizes minimum network resources is required to produce efficient searching in the robust and dynamic peer-to-peer network. Approach: This study addressed the need for efficient flood-based searching … …Journal of Computer Science, Vol. 5, Issue 3 · 31 Mar 2009 · 7,696 accessesView PDFCite
Research ArticleOpen accessIn the keywordsPandemic Analysis and Preparedness Using a Three Layer Machine Learning ApproachArtika Singh, Manisha JailiaOutbreak analysis provides research-based information and data to enable scientific decision-making to manage an effective response to a pandemic. Pandemic analysis has its own set of challenges, such as limited data, the need for real time analysis, and the complexity of outbreak patterns. This study proposes a hybrid approach to manage such a spread through a 3-layer machine learning-based outbreak … …Journal of Computer Science, Vol. 22, Issue 11 · 15 Oct 2026 · 614 accessesView PDFCite
Research ArticleOpen accessIn the keywordsPredicting Financial Statement Failure of Listed Firms in Market for Alternative Investment (mai) using Machine LearningPattanapong Kumsin, Salakjit Ninlaphay, Anupong SukprasertThe purpose of this research is to investigate the financial ratios of companies listed on the Market for Alternative Investment (mai) in Thailand, as well as the likelihood of these companies' financial statement failure. It also intends to create a financial statement failure predicting model for companies listed on the mai and assess the performance of various forecasting models using … …Journal of Computer Science, Vol. 21, Issue 9 · 24 Nov 2025 · 2,240 accessesView PDFCite
Research ArticleOpen accessIn the keywordsOptimizing KNN for Face Recognition and Location Detection in Mobile Employee Attendance Systems Using Machine LearningPainem, Hari Soetanto, Achmad Solichin, Ibnu RamadhanEmployee attendance is critical to company operations, particularly for firms involved in ATM installations collaborating with banks. An effective attendance system enables bank vendors to verify the completion of ATM installations. The current attendance method employed by the company requires employees to send photos of themselves with the installed ATM, including the machine number and installation location. The company's admin … …Journal of Computer Science, Vol. 21, Issue 5 · 14 Apr 2025 · 5,989 accessesView PDFCite