Search Results - optimal ((((((graph algorithm) OR (svm algorithm))) OR (tree algorithm))) OR (_ algorithm))
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A comparative analysis of Prim, Kruskal, and Reverse-Delete algorithms in optimizing routes within Terengganu’s and Pahang’s attraction road network / Munashahira Mohammad Zahid
Published 2024“…The Reverse-Delete algorithm works in reverse; it starts with the full graph and iteratively removes the largest edges, ensuring that the graph remains connected. …”
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Synthesis of transistor-chaining algorithm for CMOS cell layout using bipartite graph / Azizi Misnan
Published 1997“…Searching for possible abutment between the transistor pairs are modelled as a bipartite graph. A depth - first search algorithm is used to search for optimal chaining. …”
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Intrusion Detection Systems, Issues, Challenges, and Needs
Published 2021“…Optimization algorithms such as genetic algorithm (GA), particle swarm optimization (PSO) algorithm , ant colony algorithm, and many other algorithms are used along with classifiers to improve the work of these classifiers in detecting intrusion and to increase the performance of these classifiers. …”
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Guidance system based on Dijkstra-ant colony algorithm with binary search tree for indoor parking system
Published 2021“…This solution depending on applying the optimization on an optimal path while the traditional ACO is optimizing the random path based on the greedy algorithm hence we get the most optimal path. …”
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Waste management using machine learning and deep learning algorithms
Published 2020“…For our research we did the comparisons between three Machine Learning algorithms, namely Support Vector Machine (SVM), Random Forest, and Decision Tree, and one Deep Learning algorithm called Convolutional Neural Network (CNN), to find the optimal algorithm that best fits for the waste classification solution. …”
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Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves
Published 2024“…In the next phase, the datasets are optimized using the Salp Swarm Algorithm (SSA), which improves classification accuracy. …”
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Support Vector Machines (SVM) in Test Extraction
Published 2006“…There exist numerous algorithms to address the need of text categorization including Naive Bayes, k-nearest-neighbor classifier, and decision trees. …”
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Support Vector Machines (SVM) in Test Extraction
Published 2006“…There exist numerous algorithms to address the need of text categorization including Naive Bayes, k-nearest-neighbor classifier, and decision trees. …”
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A case study of microarray breast cancer classification using machine learning algorithms with grid search cross validation
Published 2023“…The study involved three machine learning algorithms, random forest (RF), extra tree (ET), and support vector machine (SVM). …”
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Implication of image processing algorithm in remote sensing and GIS applications
Published 2011“…Minimum Spanning Tree (MST), the most functional algorithm, described exclusively by the undirected graph in which all nodes are connected. …”
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Modeling of static and dynamic components of bio-nanorobotic systems
Published 2012“…In addition, a graph algorithm based on greedy methods is employed to compute a new set of optimal weighted electronic properties of the fullerenes via computing their Minimum Weight Spanning Trees (MWSTs). …”
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A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem
Published 2016“…The main keys of the new classifier are based on the new kernel method, new learning metric and a new optimization algorithm in order to optimize the SVM decision function. …”
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A matrix approach for minimum spanning tree in neutrosophic and application in medical waste management / Nur Haifa Ahmad Hayazim, Siti Nurain Zulkifli and Siti Nurhidayah Yaacob
Published 2022“…The problem of finding the minimum spanning tree (MST) is one of the most extensively studied and significant combinatorial optimization problems in graph theory. …”
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Ozone Concentration Forecasting Based on Artificial Intelligence Techniques: A Systematic Review
Published 2023“…Decision trees; Forecasting; Multilayer neural networks; Ozone; Predictive analytics; Support vector machines; Artificial intelligence techniques; Machine learning techniques; Multi layer perceptron; Optimization approach; Ozone concentration forecasting; Prediction accuracy; Stand-alone algorithm; Tropospheric ozone concentration; Learning systems; ozone; air quality; algorithm; concentration (composition); machine learning; optimization; ozone; prediction; theoretical study; air pollutant; air quality; artificial intelligence; artificial neural network; concentration (parameter); decision tree; feed forward neural network; forecasting; fuzzy system; human; measurement accuracy; multilayer perceptron; prediction; random forest; recurrent neural network; Review; support vector machine; systematic review…”
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Artificial intelligence to predict pre-clinical dental student academic performance based on pre-university results: a preliminary study
Published 2024“…RF was the most precise algorithm for predicting grades A, B, and C, followed by LR, DT, and SVM. …”
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Improvement on rooftop classification of worldview-3 imagery using object-based image analysis
Published 2019“…Then, the classifier (support vector machine (SVM) and data mining (DM) algorithm, decision tree (DT) were applied on each fusion image and their accuracy were evaluated. …”
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Activity recognition using optimized reduced kernel extreme learning machine (OPT-RKELM) / Yang Dong Rui
Published 2019“…One of the major research problems is the computation resources required by machine learning algorithm used for classification for HAR. Numerous researchers have tried different methods to enhance the algorithm to improve performance, some of these methods include Support Vector Machine (SVM), Decision Trees, Extreme Learning Machine (ELM), Kernel Extreme Learning Machine (KELM), and Deng’s Reduced Kernel Extreme Learning Machine (RKELM). …”
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Classification with degree of importance of attributes for stock market data mining
Published 2004“…The experimental results show that predictive FDT algorithm can generate a relatively optimal tree without much computation effort (comprehensibility), and WFPRs have a better predictive accuracy of stock market time series data. …”
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