Search Results - (( _ applications path algorithm ) OR ( its application bayes algorithm ))*
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Sentiment analysis regarding marital issues using Naive Bayes algorithm / Farah Nabila Mohd Razali
Published 2025“…This study explores the application of sentiment analysis using the Naive Bayes algorithm to understand public perceptions of marital issues, particularly factors contributing to the rising divorce rate. …”
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Text classification using Naive Bayes: An experiment to conference paper
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Classification and visualization on eligibility rate of applicant’s LinkedIn account using Naïve Bayes / Nurul Atirah Ahmad
Published 2023“…This project implements the Naive Bayes algorithm as the classification algorithm. …”
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IMPLEMENTATION OF GRAPH BASED PATH PLANNING ALGORITHMS FOR INDOOR NAVIGATION
Published 2018“…In which the obstacles, start node and target node will be known in advance of starting the path planning algorithms. Based on the results of MATLAB simulation, the A* algorithm is the best algorithm in finding the shortest path with the least time taken. …”
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An experiment on the performance of shortest path algorithm
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A generalized laser simulator algorithm for mobile robot path planning with obstacle avoidance
Published 2022“…With application of the all-direction border scan, it outperforms the A-star (A*) and PRM algorithms and provides safer and shorter paths. …”
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A Continuous Overlay Path Probing Algorithm For Overlay Networks
Published 2013“…Such an in-band probing algorithm reduces measurement overhead on the selected overlay path. …”
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Obstacle Avoidance System in Underwater Glider
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Comparison of path planning in simulated robot
Published 2020“…This is because each path planning algorithm has its own applicable domain, performance, advantages and disadvantages in various situations. …”
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A Proposed False Report Identification Algorithm for a Mobile Application in the IoT Environment
Published 2024Proceedings Paper -
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Dynamic path planning algorithm in mobile robot navigation
Published 2011“…The results obtained from both simulation and actual application confirmed the flexibility and robustness of the controllers designed in path planning.…”
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Mobile robot path planning using hybrid genetic algorithm and traversability vectors method
Published 2004“…Recent advances in robotics and machine intelligence have led to the application of modern optimization method such as the genetic algorithm (GA), to solve the path-planning problem. …”
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Classification and visualization on eligibility rate of applicant’s LinkedIn account using Naïve Bayes / Nurul Atirah Ahmad, Khyrina Airin Fariza Abu Samah and Nuwairah Aimi Ahmad...
Published 2023“…This project implements the Naive Bayes algorithm as the classification algorithm. …”
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Book Section -
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Modelling of multi-robot system for search and rescue
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Final Year Project / Dissertation / Thesis -
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MULTIPLE DRONES PATH OPTIMIZATION ALGORITHM FOR 3D SPACE PERFORMANCE USING CENTRALIZED VISUALIZATION PLATFORM
Published 2019“…Path planning algorithm of Unmanned Aerial Vehicle (UAV) subject to find an optimal and collision free path in 3D space. …”
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Final Year Project Report / IMRAD -
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Performance comparison of classification algorithms for EEG-based remote epileptic seizure detection in wireless sensor networks
Published 2014“…Identification of epileptic seizure remotely by analyzing the electroencephalography (EEG) signal is very important for scalable sensor-based health systems.Classification is the most important technique for wide-ranging applications to categorize the items according to its features with respect to predefined set of classes.In this paper, we conduct a performance evaluation based on the noiseless and noisy EEG-based epileptic seizure data using various classification algorithms including BayesNet, DecisionTable, IBK, J48/C4.5, and VFI.The reconstructed and noisy EEG data are decomposed with discrete cosine transform into several sub-bands.In addition, some of statistical features are extracted from the wavelet coefficients to represent the whole EEG data inputs into the classifiers.Benchmark on widely used dataset is utilized for automatic epileptic seizure detection including both normal and epileptic EEG datasets.The classification accuracy results confirm that the selected classifiers have greater potentiality to identify the noisy epileptic disorders.…”
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