Search Results - (( pre estimation clustering algorithm ) OR ( java implication based algorithm ))
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Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm
Published 2018“…The K-Means algorithm is the commonest and fast technique in partitional cluster algorithms, although with unnormalized datasets it can achieve local optimal. …”
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Parameter estimation of K-distributed sea clutter based on fuzzy inference and Gustafson-Kessel clustering
Published 2011“…This is achieved by a pre-estimation using fuzzy clustering that provides a prior knowledge and forms a rough model to be fine tuned using the least square method. …”
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An estimation algorithm for improved maritime obstacle detection
Published 2024“…Utilizing a pre-trained YOLOv8L model, the ZED2I camera identifies objects and estimates distances using RGB and depth data. …”
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An improved machine learning model of massive Floating Car Data (FCD) based on Fuzzy-MDL and LSTM-C for traffic speed estimation and prediction
Published 2023“…In this model, the Fuzzy-MDL is applied as the pre-processing step to estimate the missing traffic speeds. …”
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Prediction of breast cancer diagnosis using machine learning in Malaysian women
Published 2024“…The three frequently used ML algorithms were deep learning, support vector machine (SVM), and cluster analysis. …”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method
Published 2024thesis::doctoral thesis -
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Computerised Faculty Course Timetabling with Student Sectioning
Published 2016“…In this case study, course pre-registration is not a practice. Therefore, there is no precise estimation on course registration and causes faculty's experienced planners to arrange the timetable by curriculum-based. …”
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9
Precipitation trend analysis for The Langat River Basin, Selangor, Malaysia
Published 2014“…In order to identify the homogeneous regions respectively for the annual and seasonal scales, firstly, at- site mean total annual and separately at site mean total seasonal precipitation were spatialized into 5 km × 5 km grids using the inverse distance weighting (IDW) algorithm. Next, the optimum number of homogeneous regions (clusters) is computed using the Silhouette Coefficient approach. …”
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