Search Results - (( based optimization based algorithm ) OR ( problem implementation tree algorithm ))
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Optimized routing algorithm for mobile multicast source in Wireless Mesh Networks
Published 2015“…Thus this paper proposes a Differential Evolution based optimized mobile multicast routing algorithm for the shared tree architecture. …”
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Proceeding Paper -
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Some greedy based algorithms for multi periods degree constrained minimum spanning tree problem
Published 2015“…We implemented our algorithms on 300 generated problems with vertex order ranging from 10 to 100, and compared them with those that were already in the literature. …”
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Synthesis of transistor-chaining algorithm for CMOS cell layout using bipartite graph / Azizi Misnan
Published 1997“…This bound enables us to prune the search tree efficiently. The algorithm will be implemented and tested in this project using C language. …”
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Optimizing tree planting areas through integer programming and improved genetic algorithm
Published 2012“…In conclusion, the hybrid algorithm based solution strategies improved efficiency with convincing results, therefore, this will assist planners for better decision making to optimize area to achieve more trees to be planted. …”
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5
Disparity map algorithm using hierarchical of bitwise pixel differences and segment-tree from stereo image
Published 2024“…This thesis presents a local-based stereo matching algorithm to increase the accuracy on complex regions. …”
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A safe overtaking control scheme for autonomous vehicles using rapid-exploration random tree
Published 2022“…Firstly, the kinematics and dynamic model of the vehicle are implemented. Secondly, the RRT algorithm and the A-star algorithm are expounded, and the idea of the A-star algorithm is applied to the RRT algorithm for improvement. …”
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Proceedings -
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Performance evaluation of intrusion detection system using selected features and machine learning classifiers
Published 2021“…These evolutionary-based algorithms are known to be effective in solving optimization problems. …”
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Article -
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Edge assisted crime prediction and evaluation framework for machine learning algorithms
Published 2022“…The growing global populations, particularly in major cities, have created new problems, notably in terms of public safety regulation and optimization. …”
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Conference or Workshop Item -
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Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals
Published 2020“…The first method is the Binary Tree Growth Algorithm (BTGA), which implements a hyperbolic tangent function to convert the Tree Growth Algorithm into the binary version. …”
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Algorithm optimization and low cost bit-serial architecture design for integer-pixel and sub-pixel motion estimation in H.264/AVC / Mohammad Reza Hosseiny Fatemi
Published 2012“…To address the computational complexity and memory bandwidth requirement problems of interpolate and search method in the SME of H.264/AVC, we introduce a low complexity algorithm and its hardware architecture for SME with quarter-pixel accuracy that is based on parabolic interpolation free algorithms. …”
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Disparity map algorithm for stereo matching process using local based method
Published 2022“…Hence, this thesis proposes a local-based SVDM algorithm that increases the accuracy on the complex scenes. …”
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Optimal load management strategy for enhanced time of use (ETOU) electricity tariff in Peninsular Malaysia / Mohamad Fani Sulaima
Published 2020“…Based on the output of the controlled load assessment, the optimal weightage of LM was identified. …”
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Energy-aware task scheduling for streaming applications on NoC-based MPSoCs
Published 2024“…We propose a novel unified approach that integrates task-level software pipelining with Dynamic Voltage and Frequency Scaling (DVFS) to solve the problem. 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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Article -
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Fraud detection in shipping industry based on location using machine learning comparison techniques
Published 2023“…A number of popular existing algorithms were used to execute the model developed in Rapid tool such as Naïve Bayes , Neural Net , Deep Learning, Decision Tree, Logistic Regression, SVM and k-NN. …”
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Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach
Published 2025“…The descriptive analysis examines purchasing behavior through correlation and regression analyses, while the predictive model uses decision trees (J48, Random Tree, REPTree), rule-based algorithms (JRip, OneR, PART), and clustering (K-Means) to identify patterns and predict trends. …”
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Attribute related methods for improvement of ID3 Algorithm in classification of data: A review
Published 2020“…There are several learning algorithms to implement the decision tree but the most commonly-used is ID3 algorithm. …”
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A quantum algorithm for minimal spanning tree
Published 2008“…Classical algorithms involve searching over some space for finding the minimal spanning tree problem in a graph. …”
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Conference or Workshop Item -
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Comparisons of automated machine learning (AutoML) in predicting whistleblowing of academic dishonesty with demographic and theory of planned behavior
Published 2023“…Focused on Python and RapidMiner rapid modeling tools, Tree-based Pipeline Optimization Tool (TPOT) and AutoModel were used. …”
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Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd
Published 2022“…The bagging method was then applied to the FID3-DBD algorithm to overcome overfitting problems and high variance in decision trees. …”
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