Search Results - (( using classification modeling algorithm ) OR ( program implementation path algorithm ))

Propositional satisfiability method in rough classification modeling for data mining by Abu Bakar, Azuraliza

“…The propositional satisfiability method in rough classification model is proposed in this thesis. Two models, Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) to represent the minimal reduct computation problem were proposed. …”
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Simulation of shortest path using a-star algorithm / Nurul Hani Nortaja by Nurul Hani , Nortaja

“…The steps to calculate a shortest path using A • algorithm is shown by using appropriate examples and related figures. …”
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Vision-based robot indoor navigation by Teo, Zhin Hang

“…A navigation robot is built to test the workability and efficiency of the algorithms. In general, the algorithm can provide the nearest path to navigate around the environment without manual assistance. …”
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Implementation of Autonomous Vehicle Navigation Algorithms Using Event-Driven Programming by Saman, Abu Bakar Sayuti, Sebastian , Patrick, Malek, Nadhira, Hasidin, Nurul Zahidah

“…By using FSM to describe the behaviour of a navigating mobile robot, an equivalent algorithm can be developed. The algorithm can be relatively easy translated to a suitable program with event-driven programming technique. …”
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Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms by Koh, Johnny Siaw Paw

“…This algorithm has been tested and implemented successfully via a dual beam optical scanning system.…”
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Implementation of an autonomous mobile robot navigation algorithm using C language by Subra Mullisi, Shafeq Marwan

“…The problem can basically be divided into positioning and path planning. This report basically discusses the study and also work that has been done from previous of the chosen topic, which is Implementation of an Autonomous Mobile Robot Navigation Algorithm using 'C' language. …”
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Implementation of autonomous vehicle navigation algorithms using event-driven programming by Saman, Abu Bakar Sayuti, Sebastian , Patrick, Malek, Nadhira, Hasidin, Nurul Zahidah

“…By using FSM to describe the behaviour of a navigating mobile robot, an equivalent algorithm can be developed. The algorithm can be relatively easy translated to a suitable program with event-driven programming technique. …”
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GPS boundary navigation of DrosoBots using MATLAB simulation by Zainal Abidin, Zulkifli, Ngah , Vmi Kalthum, Arshad, Mohd Rizal, Kok , Chee Hou

“…To implement this, region recognition and several path planning algorithms have been utilized. …”
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An improved algorithm in test case generation from UML activity diagram using activity path by Hashim, Nor Laily, Salman, Yasir D.

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A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network by Salari, Nader, Shohaimi, Shamarina, Najafi, Farid, Nallappan, Meenakshii, Karishnarajah, Isthrinayagy

“…In the present study, the results of the implementation of a novel hybrid feature selection-classification model using the above mentioned methods are presented. …”
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Railway shortest path planner application using ant colony optimization algorithm / Muhammad Hassan Firdaus Ruslan by Ruslan, Muhammad Hassan Firdaus

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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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Development of obstacle avoidance technique in web-based geographic information system for traffic management using open source software by Nik Yusoff, Nik Mohd Ramli, Mohd Shafri, Helmi Zulhaidi, Muniandy, Ratnasamy, Mohammad Wali, Islam

“…Pg Routing as an extension of Postgre SQL/Post GIS database is an open source library that implements the Dijkstra shortest path algorithm. However, the functionality to avoid obstacles in that analysis is still limited. …”
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Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model by Sulaiman, Md. Nasir, Mohamed, Raihani, Mustapha, Norwati, Zainudin, Muhammad Noorazlan Shah

“…EM and K-means clustering algorithms are used to cluster the multi-class classification attribute according to its relevance criteria and afterward, the clustered attributes are classified using an ensemble random forest classifier model. …”
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An adaptive ant colony optimization algorithm for rule-based classification by Al-Behadili, Hayder Naser Khraibet

“…Various classification algorithms have been developed to produce classification models with high accuracy. …”
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Development of Path Loss Models for Smooth and Convex Surfaces Terrains in Malaysian Environment by Wong, Peng Kiong

“…This program consists of four algorithms which are conversion formulas, smooth terrain, single convex surface terrain and double convex surfaces terrain.…”
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Predicting breast cancer using ant colony optimisation / Siti Sarah Aqilah Che Ani by Che Ani, Siti Sarah Aqilah

“…This study implements a machine learning algorithm called Ant Colony Optimization (ACO) algorithm to develop an accurate classification model for predicting breast cancer cells. …”
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Formulating new enhanced pattern classification algorithms based on ACO-SVM by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…ACO originally deals with discrete optimization problem.In applying ACO for solving SVM model selection problem which are continuous variables, there is a need to discretize the continuously value into discrete values.This discretization process would result in loss of some information and hence affects the classification accuracy and seeking time.In this algorithm we propose to solve SVM model selection problem using IACOR without the need to discretize continuous value for SVM.The second algorithm aims to simultaneously solve SVM model selection problem and selects a small number of features.SVM model selection and selection of suitable and small number of feature subsets must occur simultaneously because error produced from the feature subset selection phase will affect the values of SVM model selection and result in low classification accuracy.In this second algorithm we propose the use of IACOMV to simultaneously solve SVM model selection problem and features subset selection.Ten benchmark datasets were used to evaluate the proposed algorithms.Results showed that the proposed algorithms can enhance the classification accuracy with small size of features subset.…”
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Classification model for water quality using machine learning techniques by Azilawati, Rozaimee, Azrul Amri, Jamal, Azwa, Abdul Aziz

“…In assessing the result, the Lazy model using K Star algorithm was the best classification model among the five models had the most outstanding accuracy of 86.67%. …”
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Classification of Diabetes Mellitus (DM) using Machine Learning Algorithms by Sirajun Noor, Noor Azmiya

“…Whereas for the German Frankfurt dataset, best DM classification model was found using Random Forest algorithm with an accuracy of 98.77%.…”
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