Search Results - optical ((((svm algorithm) OR (bat algorithm))) OR (tree algorithm))
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Comparative analysis on the deployment of machine learning algorithms in the distributed brillouin optical time domain analysis (BOTDA) fiber sensor
Published 2023“…The algorithms analyzed were generalized linear model (GLM), deep learning (DL), random forest (RF), gradient boosted trees (GBT), and support vector machine (SVM). …”
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Translating conventional wisdom on chicken comb color into automated monitoring of disease-infected chicken using chromaticity-based machine learning models
Published 2024“…The development of the algorithms shows that Logistic Regression, SVM with Linear and Polynomial kernels performed the best with 95% accuracy, followed by SVM-RBF kernel, and KNN with 93% accuracy, Decision Tree with 90% accuracy, and lastly, SVM-Sigmoidal kernel with 83% accuracy. …”
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Translating conventional wisdom on chicken comb color into automated monitoring of disease-infected chicken using chromaticity-based machine learning models
Published 2023“…The development of the algorithms shows that Logistic Regression, SVM with Linear and Polynomial kernels performed the best with 95 accuracy, followed by SVM-RBF kernel, and KNN with 93 accuracy, Decision Tree with 90 accuracy, and lastly, SVM-Sigmoidal kernel with 83 accuracy. …”
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Optimized techniques for landslide detection and characteristics using LiDAR data
Published 2018“…The locations of landslides were detected accurately by employing two Machine learning classifiers, namely, SVM and RF, decision rule and hierarchal rules sets were developed by applying decision tree (DT) algorithm to provide improved landslide inventory. …”
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Accounting Information Systems Genetic Algorithms for All-Optical Shared Fiber-Delay-Line Packet Switches
Published 2009“…In the first algorithm, packet scheduling is formulated as a tree-searching problem. …”
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Assessing Bat Roosts Using the LiDAR System at Wind Cave Nature Reserve in Sarawak, Malaysian Borneo
Published 2017“…Bats that roost in large clusters, specifically Penthetor lucasi were determined through automated counting using connected components labelling, a graph theory algorithm mostly used in image analysis applications. …”
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Simultaneous measurement of multiple soil properties through proximal sensor data fusion: a case study
Published 2019“…After choosing the optimal sensor combination for each soil property, the predictive capability was compared using different data mining algorithms, including support vector machines (SVM), random forest (RF), multivariate adaptive regression splines (MARS), and regression trees (CART). …”
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Seeing trees from space: above-ground biomass estimates of intact and degraded montane rainforests from high-resolution optical imagery
Published 2017“…We used the dimensions of tree crowns detected in the imagery to estimate above-ground biomasses (AGBs) of individual trees and plots. …”
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QoS Forwarding on the Optical Internet Backbone Area Using R-IWDMTC Protocol
Published 2006“…(Extended via Multi-protocol Label Switching (MPLS)) provides connection-oriented setup and multicast tree construction control for Optical Internet data forwarding in the network backbone area. …”
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Design Of A Predictive Model For TCM Pulse Diagnosis In Malaysia Using Machine Learning
Published 2020“…The machine learning algorithms applied in this project are k-nearest neighbors (KNN), naïve Bayes, random forest, gradient boosting and support vector machine (SVM). …”
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The formulation of a transfer learning pipeline for the classification of the wafer defects
Published 2023“…Thus, this study will aim to explore 17 types of TL models, and classify the features extracted using 3 different ML algorithms, namely Support Vector Machine (SVM), k-Nearest Neighbor (kNN) and Random Forest (RF). …”
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A preliminary lightweight random forest approach-based image classification for plant disease detection
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Delineating mangrove forest zone using spectral reflectance
Published 2020“…To identify individual mangrove species, in-situ measurement was conducted using handheld optical sensors of spectroradiometer to examine the most effective wave bands and spectral regions for discriminating mangrove tree species. …”
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