Search Results - (( parameter classification technique algorithm ) OR ( code classification using algorithm ))
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The development of virtual product life cycle design tool using artificial intelligence technique
Published 2008“…The generated features from code classification algorithm give the information of machining parameter through the mapping algorithm. …”
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Monograph -
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Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level
Published 2024thesis::doctoral thesis -
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Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool
Published 2018“…From the data analysis using WEKA software, the production rules classifier (PART) is found to be the most accurate classification algorithm in classifying the emotion which yields the highest precision percentage of 99.6% compared to J48 (99.5%) and Naïve Bayes (96.2%). …”
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Thesis -
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Enhancement Of Static Code Analysis Malware Detection Framework For Android Category-Based Application
Published 2021“…Four types of machine learning algorithm were tested with four different kind of splitting dataset techniques separately. …”
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Android Malware classification using static code analysis and Apriori algorithm improved with particle swarm optimization
Published 2014“…In this method, features were extracted from Android applications byte-code through static code analysis, selected and were used to train supervised classifiers. …”
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Proceeding Paper -
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Static code analysis of permission-based features for android malware classification using apriori algorithm with particle swarm optimization
Published 2015“…However, supervised learning technique has limitations for malware classification task. This paper presents a classification approach on android malware using candidate detectors generated from an unsupervised association rule of Apriori Algorithm. …”
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Incremental continuous ant colony optimization for tuning support vector machine’s parameters
Published 2013“…Support Vector Machines are considered to be excellent patterns classification techniques. The process of classifying a pattern with high classification accuracy counts mainly on tuning Support Vector Machine parameters which are the generalization error parameter and the kernel function parameter.Tuning these parameters is a complex process and Ant Colony Optimization can be used to overcome the difficulty. …”
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Hybrid ACO and SVM algorithm for pattern classification
Published 2013“…Hybridization algorithms between ACO and SVM techniques were proposed. …”
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Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak
Published 2019“…The third stage is to classify individual jammers according to the specific pattern and characteristics design as defined in jamming identification and classification parameters. It involves development of Max-Min Rule-Based Classification Algorithm. …”
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Optimizing support vector machine parameters using continuous ant colony optimization
Published 2012“…Hence, in applying Ant Colony Optimization for optimizing Support Vector Machine parameters, which are continuous parameters, there is a need to discretize the continuous value into a discrete value.This discretization process results in loss of some information and, hence, affects the classification accuracy and seek time.This study proposes an algorithm to optimize Support Vector Machine parameters using continuous Ant Colony Optimization without the need to discretize continuous values for Support Vector Machine parameters.Seven datasets from UCI were used to evaluate the performance of the proposed hybrid algorithm.The proposed algorithm demonstrates the credibility in terms of classification accuracy when compared to grid search techniques.Experimental results of the proposed algorithm also show promising performance in terms of computational speed.…”
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Classification of tropical rainforest using different classification algorithm based on remote sensing imagery: A study of Gunung Basor
Published 2019“…Remote sensing technologies are used globally to derive some of crucial spatial variable parameter such as vegetation cover. Three different classification algorithm, minimum distance classifier, Mahalanobis distance classifier and maximum likelihood algorithm was applied to classify the forest area in Gunung Basor. …”
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Undergraduate Final Project Report -
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An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani
Published 2015“…The improved algorithm is constructed by adding new parameter and classification rule to existing algorithm. …”
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Aco-based feature selection algorithm for classification
Published 2022“…The proposed EGCACO algorithm can be utilised for FS in DNA microarray classification tasks that involve large dataset size in various application domains.…”
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Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm
Published 2023Subjects:Conference Paper -
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Development of an intelligent prediction tool for rice yield based on machine learning techniques
Published 2006“…Support vector machine algorithm is developed for classification of rice plantation data. …”
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Integrated ACOR/IACOMV-R-SVM Algorithm
Published 2017“…The first algorithm, ACOR-SVM, will tune SVM parameters, while the second IACOMV-R-SVM algorithm will simultaneously tune SVM parameters and select the feature subset. …”
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Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification
Published 2020“…The overall objective of this study is to explore some factors affecting non- parametric LCM classification techniques in terms of accuracy assessment and to compare their performance with a well-established classification technique by implementing Landsat 8 and Sentinel satellites. …”
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First Semester Computer Science Students’ Academic Performances Analysis by Using Data Mining Classification Algorithms
Published 2014“…The comparative analysis is also conducted to discover the best classification model for prediction. 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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