Search Results - (( parallel optimization svm algorithm ) OR ( program implementation tree algorithm ))
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Intelligent classification algorithms in enhancing the performance of support vector machine
Published 2019“…This paper presents two intelligent algorithms that hybridized between ant colony optimization (ACO) and SVM for tuning SVM parameters and selecting feature subset without having to discretize the continuous values. …”
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Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems
Published 2022“…Meanwhile, an improved parallel Jaya (IPJAYA) algorithm was proposed for searching the best parameters (C, Gama) values of SVM. …”
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Optimizing tree planting areas through integer programming and improved genetic algorithm
Published 2012“…Therefore, a hybrid algorithm through an incorporation of Integer Programming and Improved Genetic Algorithm was proposed for planting lining design. …”
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Classification of Google Play application using decision tree algorithm on sentiment analysis of text reviews / Aqil Khairy Hamsani, Ummu Fatihah Mohd Bahrin and Wan Dorishah Wan A...
Published 2023“…To achieve these objectives, the methods employed involve data preprocessing and implementing the Decision Tree (DT) algorithm for classification. …”
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Comparison Of Phylogenetic Trees Using Difference Distance Function Method
Published 2005“…The pre-processing is implemented using the Microsoft Visual C++. The phylogenetic tree is build using the PHYLlP (the PHYlogeny Inference Package), a package of programs for inferring phylogenies (evolutionary trees). …”
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Predicting Student Performance in Object Oriented Programming Using Decision Tree : A Case at Kolej Poly-Tech Mara, Kuantan
Published 2013“…The objective was to identify and implement the most accurate algorithm for the KPTM dataset and to come up with a good prediction model using decision tree technique. …”
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Case Slicing Technique for Feature Selection
Published 2004“…The classification accuracy obtained from the CST method is compared to other selected classification methods such as Value Difference Metric (VDM), Pre-Category Feature Importance (PCF), Cross-Category Feature Importance (CCF), Instance-Based Algorithm (IB4), Decision Tree Algorithms such as Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5), Rough Set methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) and Neural Network methods such as the Multilayer method.…”
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Hybrid ANN and Artificial Cooperative Search Algorithm to Forecast Short-Term Electricity Price in De-Regulated Electricity Market
Published 2019“…Finally, the simulation results validated the premise of the proposed hybrid method through enhanced accuracy compared to the results acquired by implementing hybrid support vector machine (SVM) and hybrid ANN optimization methods. © 2013 IEEE.…”
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Rapid software framework for the implementation of machine learning classification models
Published 2021“…Additionally, this paper explains comparisons of results between two platforms of rapid software; the proposed software and Python program. The machine learning model in the two platforms were tested on breast cancer and tax avoidance datasets with Decision Tree algorithm. …”
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Lightning fault classification for transmission line using support vector machine
Published 2023“…The proposed method was implemented in the MATLAB/SIMULINK programming platform. …”
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Lightning Fault Classification for Transmission Line Using Support Vector Machine
Published 2024“…The proposed method was implemented in the MATLAB/SIMULINK programming platform. …”
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…The circuits have been designed by proteus, the microcontrollers have been programmed by micro C, and the Graphical User Interface (GUI) has been implemented in Java. …”
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Energy-aware task scheduling for streaming applications on NoC-based MPSoCs
Published 2024“…Our approach is supported by a set of novel techniques, which include constructing an initial schedule based on a list scheduling where the priority of each task is its approximate successor-tree-consistent deadline such that the workload across all the processors is balanced, a retiming heuristic to transform intraperiod dependencies into inter-period dependencies for enhancing parallelism, assigning an optimal discrete frequency for each task and each message using a Non-Linear Programming (NLP)-based algorithm and an Integer-Linear Programming (ILP)-based algorithm, and an incremental approach to reduce the memory usage of the retimed schedule in case of memory size violations. …”
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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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