Search Results - (( developing selected tree algorithm ) OR ( java optimization path algorithm ))

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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SecPath: Energy efficient path reconstruction in wireless sensor network using iterative smoothing by Abd, Wamidh Jwdat

“…This work uses iterative smoothing algorithm to find an alternative path with less distance and energy consumption. …”
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Energy efficient path reconstruction in wireless sensor network using iPath by Hasan, Sazlinah, Abd, Wamidh Jwdat, Ariffin, Ahmad Alauddin

“…This work uses iterative boosting algorithm to find an alternative path with less distance and energy consumption. …”
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Visdom: Smart guide robot for visually impaired people by Lee, Zhen Ting

“…Core functionalities such as path planning, autonomous movement, voice feedback, and app-to-robot communication have been thoroughly tested and optimized. …”
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Selection, generation and extraction of MCCTree using XMCCTree by Sazaly, Ummu Sulaim, Selamat, Mohd Hasan, Baharom, Salmi, A. Jabar, Marzanah

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A class skew-insensitive ACO-based decision tree algorithm for imbalanced data sets by Mohd Razali, Muhamad Hasbullah, Saian, Rizauddin, Yap, Bee Wah, Ku-Mahamud, Ku Ruhana

“…Ant-tree-miner (ATM) has an advantage over the conventional decision tree algorithm in terms of feature selection. …”
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Classification model for hotspot occurrences using spatial decision tree algorithm by Sitanggang, Imas Sukaesih, Yaakob, Razali, Mustapha, Norwati, Nuruddin, Ahmad Ainuddin

“…This study describes the application of data mining technique namely decision tree on forest fires data. We improved the ID3 decision tree algorithm such that it can be utilized on spatial data in order to develop a classification model for hotspots occurrence. …”
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Tree-based contrast subspace mining method by Florence Sia Fui Sze

“…The research works involve first preparing the real world numerical and categorical data sets. Then, the tree-based method, the genetic algorithm based parameter values identification of tree-based method, and followed by the genetic algorithm based tree-based method, for numerical data sets are developed and evaluated. …”
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Logic modeling and mathematical model in developing a tree species selection prototype by Kamarudin, Shafinaz, Sahari, Noraidah, Selamat, Mohd Hasan, Abdullah, Rusli, Sulaiman, Riza, Mohammad, Mohd Ikram

“…The article aims to explain the use of decision tables, structured English and mathematical model for the development of a tree species selection prototype for Malaysian forest plantation. …”
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State of charge estimation for lithium-ion battery based on random forests technique with gravitational search algorithm by Lipu M.S.H., Ayob A., Saad M.H.M., Hussain A., Hannan M.A., Faisal M.

E2IDS: an enhanced intelligent intrusion detection system based on decision tree algorithm by Bouke, Mohamed Aly, Abdullah, Azizol, ALshatebi, Sameer Hamoud, Abdullah, Mohd Taufik

“…The model design is Decision Tree (DT) algorithm-based, with an approach to data balancing since the data set used is highly unbalanced and one more approach for feature selection. …”
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A study of graduate on time (GOT) for Ph.D students using decision tree model by Chin, Wan Yung, Ch’ng, Chee Keong, Mohd Jamil, Jastini

“…Therefore, this study aims to classify the Ph.D students into the group of “GOT achiever” and “non-GOT achiever” by using decision tree models. Historical data that related to all Ph.D students in a public university in Malaysia has been obtained directly from the database of Graduate Academic Information System (GAIS) in order to develop and compare the performance of decision tree models (Chi-square algorithm, Gini index algorithm, Entropy algorithm and an interactive decision tree). …”
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Comparison of malware detection model using supervised machine learning algorithms / Syamir Mohd Shahirudin by Mohd Shahirudin, Syamir

“…The objective of this project is to develop the Windows malware detection model using supervised machine learning in Decision Tree, K-NN and Naïve Bayes, to evaluate the performance of malware detection in term of testing and training of the features selection and to compare the accuracy detection model in all three machine learning algorithms. …”
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Enhance efficiency of answering XML keyword query using incompact structure of MCCTree by Sazaly, Ummu Sulaim

“…MCCTreeGenerator used CGTree to select subtree called Maximal Compact Connected Tree (MCCTree) as query result based on MCLCA notion. …”
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Streamflow Prediction Utilizing Deep Learning and Machine Learning Algorithms for Sustainable Water Supply Management by Latif S.D., Ahmed A.N.

First Semester Computer Science Students’ Academic Performances Analysis by Using Data Mining Classification Algorithms by Azwa, Abdul Aziz, Fadhilah, Ahmad

“…From the experiment, the models develop using Rule Based and Decision Tree algorithm shows the best result compared to the model develop from the Naïve Bayes algorithm. …”
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Intersection Features For Android Botnet Classification by Ismail, Najiahtul Syafiqah, Yusof, Robiah, Saad, Halizah, Abdollah, Mohd Faizal, Yusof, Robiah

“…The Chi Square was used to select the most significant permissions, then the classification algorithms like Naïve Bayes and Decision Tree were used to classify the Android apps as botnet or benign apps. …”
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An object-based approach to detect tree stumps in a selective logging area using Unmanned Aerial Vehicle imagery by Aisyah Marliza Muhmad Kamarulzaman, Wan Shafrina Wan Mohd Jaafar, Siti Nor Maizah Saad, Hamdan Omar, Mohd. Rizaludin Mahmud

“…Unmanned Aerial Vehicles (UAVs) have been widely used as a tool for analyzing selective logging impacts in forest area sites. One of the potential use of UAV imagery data for analyzing the impact of selective logging is by obtaining tree stump information. …”
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Improved random forest for feature selection in writer identification by Sukor, Nooraziera Akmal

“…An algorithm and framework of Improved Random Forest (IRF) tree was applied for feature selection process. …”
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Prediction of Oil Palm Yield Using Machine Learning in the Perspective of Fluctuating Weather and Soil Moisture Conditions: Evaluation of a Generic Workflow by Khan N., Kamaruddin M.A., Ullah Sheikh U., Zawawi M.H., Yusup Y., Bakht M.P., Mohamed Noor N.

“…The prediction was followed by data preprocessing and feature selection. Selected regression models were compared with Random Forest, Gradient Boosting, Decision Tree, and other non-tree algorithms to prove the R2 driven performance superiority of tree-based ensemble models. …”