Search Results - (( problem solving svm algorithm ) OR ( java application optimization algorithm ))

Formulating new enhanced pattern classification algorithms based on ACO-SVM by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…This paper presents two algorithms that integrate new Ant Colony Optimization (ACO) variants which are Incremental Continuous Ant Colony Optimization (IACOR) and Incremental Mixed Variable Ant Colony Optimization (IACOMV) with Support Vector Machine (SVM) to enhance the performance of SVM.The first algorithm aims to solve SVM model selection problem. …”
Get full text
Get full text
Get full text

Feature selection and model selection algorithm using incremental mixed variable ant colony optimization for support vector machine classifier by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…In order to enhance SVM performance, these problems must be solved simultaneously because error produced from the feature subset selection phase will affect the values of the SVM parameters and resulted in low classification accuracy.Most approaches related with solving SVM model selection problem will discretize the continuous value of SVM parameters which will influence its performance.Incremental Mixed Variable Ant Colony Optimization (IACOMV) has the ability to solve SVM model selection problem without discretising the continuous values and simultaneously solve the two problems.This paper presents an algorithm that integrates IACOMV and SVM.Ten datasets from UCI were used to evaluate the performance of the proposed algorithm.Results showed that the proposed algorithm can enhance the classification accuracy with small number of features.…”
Get full text
Get full text
Get full text

Solving SVM model selection problem using ACOR and IACOR by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…Ant Colony Optimization (ACO) has been used to solve Support Vector Machine (SVM) model selection problem.ACO originally deals with discrete optimization problem. …”
Get full text
Get full text
Get full text

Integrated ACOR/IACOMV-R-SVM Algorithm by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…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. …”
Get full text
Get full text
Get full text

Hybrid ACO and SVM algorithm for pattern classification by Alwan, Hiba Basim

“…Ant Colony Optimization (ACO) is a metaheuristic algorithm that can be used to solve a variety of combinatorial optimization problems. …”
Get full text
Get full text
Get full text

Extending the decomposition algorithm for support vector machines training by Zaki, N,M., Deris, S., Chin, K.K.

“…Using a conventional optimizer to train SVM is not the ideal solution. One can design a dedicated optimizer that will take full advantage of the specific nature of the QP problem in SVM training. …”
Get full text
Get full text
Get full text

A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem by Mohd Pozi, Muhammad Syafiq

“…The SVGPM performance is compared against SVM and cost-sensitive SVM due to the superiority of SVM in dealing with imbalanced classification problem. …”
Get full text
Get full text
Get full text

Solving Support Vector Machine Model Selection Problem Using Continuous Ant Colony Optimization by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…Ant Colony Optimization has been used to solve Support Vector Machine model selection problem.Ant Colony Optimization originally deals with discrete optimization problem.In applying Ant Colony Optimization for optimizing Support Vector Machine parameters which are continuous variables, there is a need to discretize the continuously value into discrete value.This discretize process would result in loss of some information and hence affect the classification accuracy and seeking time.This study proposes an algorithm that can optimize Support Vector Machine parameters using Continuous Ant Colony Optimization without the need to discretize continuous value for Support Vector Machine parameters.Eight datasets from UCI were used to evaluate the credibility of the proposed hybrid algorithm in terms of classification accuracy and size of features subset.Promising results were obtained when compared to grid search technique, GA with feature chromosome-SVM, PSO-SVM, and GA-SVM.…”
Get full text
Get full text
Get full text

Face recognition using eigenfaces and smooth support vector machine by Mhd, Furqan

“…The Smooth Support Vector Machine (SSVM) is a further development of the SVM. Smoothing methods, extensively used for solving important mathematical programming problems and applications. …”
Get full text
Get full text

Face recognition using eigenfaces and smooth support vector machine by Mhd, Furqan

“…The Smooth Support Vector Machine (SSVM) is a further development of the SVM. Smoothing methods, extensively used for solving important mathematical programming problems and applications. …”
Get full text
Get full text

Anomaly behavior detection using flexible packet filtering and support vector machine algorithms by Abdul Wahid, Mohammed N.

“…Furthermore, Network traffic prediction algorithms based on SVM such as EaSVM have commented about the fundamental difficulties in achieving an accurate declaration that defines anomaly which suppose to solve the problem of the high rate of false positive alarm and finding excellent ways that guarantees to clear up pending issues of the network traffic normality such as the alluvial data noise of the TAaM method. …”
Get full text
Get full text
Get full text

An Arabic hadith text classification model using convolutional neural network and support vector machine / Mohd Irwan Mazlin by Mazlin, Mohd Irwan

“…Second, parameter tuning is conducted to find the best parameter for CNN-SVM. Third, the model (CNN-SVM, CNN and SVM) is monitored to see if their performance predicts unseen data. …”
Get full text
Get full text

Optimization of blood vessel detection in retina images using multithreading and native code for portable devices by Tran, Duc Ngoc, Hussin, Fawnizu Azmadi, Yusoff, Mohd Zuki

Get full text
Get full text

Performance evaluation of real-time multiprocessor scheduling algorithms by Alhussian, H., Zakaria, N., Abdulkadir, S.J., Fageeri, S.O.

“…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
Get full text
Get full text

SVM based sentiment analysis for online shopping reviews by Oad, Rajesh Kumar, Ghulamani, Sumbul, Ahmad, Umair Jamil, Shaikh, Amina, Shah, Asadullah

“…Therefore, this research intends to solve this problem through use of SVM classifier and proposes a system aimed to help the customer in their decision-making. …”
Get full text
Get full text
Get full text

Route Optimization System by Zulkifli, Abdul Hayy

“…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
Get full text
Get full text

Fuzzy support vector machine based fall detection method for traumatic brain injuries: A new systematic approach of combining fuzzy logic with support vector machine to achieve hig... by Harum, Norharyati, Khalil, Mohamad Kchouri, Obeid, Ali, Hazimeh, Hussein

“…One of the most commonly used algorithms is Support Vector Machine (SVM). However, classical SVM can neither use prior knowledge to process accurate classifications nor solve problems characterized by ambiguity. …”
Get full text
Get full text
Get full text

Detection of eye movements based on EEG signals and the SAX algorithm by Shanmuga, P. M. M., Lau, Sian Lun *, Jou, Chichang.

“…We would like to investigate another technique, namely the Symbolic Aggregate Approximation (SAX) algorithm, to find out its suitability and performance against known classification algorithms such as Support Vector Machine (SVM), k-Nearest Neighbour (KNN) and Decision Tree (DT).…”
Get full text
Get full text

Automatic Number Plate Recognition on android platform: With some Java code excerpts by ., Abdul Mutholib, Gunawan, Teddy Surya, Kartiwi, Mira

Get full text
Get full text
Get full text

Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

“…Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
Get full text
Get full text