Search Results - (( data feature selection algorithm ) OR ( java implementation path algorithm ))

Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer by Ahmad Nezer, Nurul Aqilah

“…The development tools used in developing this project is NetBeans by using Java for the implementation of the coding. The methodology that used for developing this system is the Dijkstra’s algorithm. …”
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

“…BST inserts the nodes in the way that the Dijkstra’s can find the empty parking in fastest way. Dijkstra’s algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
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Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment by Shaliza Hayati A. Wahab, Nordin Saad, Azali Saudi, Ali Chekima

“…In this study, a fast iterative method known as Rotated Successive Over-Relaxation (RSOR) is introduced. The algorithm is implemented in a self-developed 2D Java tool, UAV Planner. …”
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Smart appointment organizer for mobile application / Mohd Syafiq Adam by Adam, Mohd Syafiq

“…The main component of this prototype is the use of Dijkstra algorithm to compute the shortest path from source of appointment to the 6 points of destinations within UiTM Shah Alam. …”
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Application of the bees algorithm to the selection features for manufacturing data by Pham, D.T, Mahmuddin, Massudi, Otri, S., Al-Jabbouli, H.

“…The Bees Algorithm is employed to select an optimal set of features for a particular pattern classification task. …”
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Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

“…Feature selection and classification are widely utilized for data analysis. …”
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Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

“…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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Feature selection for high dimensional data: An evolutionary filter approach. by Yahya, Anwar Ali, Osman, Addin, Ramli, Abdul Rahman, Balola, Adlan

“…Approach: In this study, we proposed an adapted version of genetic algorithm that can be applied for feature selection in high dimensional data. …”
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Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection by Tubishat, Mohammad, Idris, Norisma, Shuib, Liyana, Abushariah, Mohammad A.M., Mirjalili, Seyedali

“…Thus, to solve these problems, feature selection can be used to select optimal subset of features and reduce the data dimensionality. …”
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A partition based feature selection approach for mixed data clustering / Ashish Dutt by Ashish , Dutt

“…In this thesis, a novel weighted feature selection approach on nominal features is proposed, for a partition. clustering algorithm that can handle mixed data. …”
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Comparing the performance of FCBF, Chi-Square and relief-F filter feature selection algorithms in educational data mining by Zaffar, M., Hashmani, M.A., Savita, K.S.

“…It is very necessary to increase the quality of dataset as to get better prediction results. There are many feature selection algorithms, however three filter feature selection algorithms FCBF, Chi-Square, and ReliefF are selected due their better performance, and applied on three different studentâ��s data sets. …”
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Comparing the performance of FCBF, Chi-Square and relief-F filter feature selection algorithms in educational data mining by Zaffar, M., Hashmani, M.A., Savita, K.S.

“…It is very necessary to increase the quality of dataset as to get better prediction results. There are many feature selection algorithms, however three filter feature selection algorithms FCBF, Chi-Square, and ReliefF are selected due their better performance, and applied on three different studentâ��s data sets. …”
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Multiview Laplacian semisupervised feature selection by leveraging shared knowledge among multiple tasks by Krishnasamy, Ganesh, Paramesran, Raveendran

“…However, these semisupervised multitask selection feature algorithms are unable to naturally handle the multiview data since they are designed to deal single-view data. …”
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Performance analysis of feature selection algorithm for educational data mining by Zaffar, M., Hashmani, M.A., Savita, K.S.

“…This paper present an analysis of the performance of feature selection algorithms on student data set. …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

“…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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Whale optimization algorithm based on tent chaotic map for feature selection in soft sensors by AlRijeb, Mothena Fakhri Shaker, Othman, Mohammad Lutfi, Ishak, Aris, Hassan, Mohd Khair, Albaker, Baraa Munqith

“…Selecting the relevant features from the data leads to better classification results. …”
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Enhancement of bearing defect diagnosis via genetic algorithm optimized feature selection by Chia, Yee Shin

“…However this feature selection algorithm might be unstable due to the stochastic property of GA. …”
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Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi by Atefi, Kayvan

“…One of the main steps after the data collection stage of any method is selecting a subset of the features to be used for the feature selection process. …”
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Optimization of attribute selection model using bio-inspired algorithms by Basir, Mohammad Aizat, Yusof, Yuhanis, Hussin, Mohamed Saifullah

“…Attribute selection which is also known as feature selection is an essential process that is relevant to predictive analysis.To date, various feature selection algorithms have been introduced, nevertheless they all work independently. …”
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Naive bayes-guided bat algorithm for feature selection. by Taha, Ahmed Majid, Mustapha, Aida, Chen, Soong Der

“…The performance of the proposed feature selection algorithm was investigated using twelve benchmark datasets from different domains and was compared to three other well-known feature selection algorithms. …”
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