Search Results - (( developing classical selection algorithm ) OR ( java optimization method algorithm ))
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Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares
Published 2009“…We modified the classical bootstrapping algorithm by developing a mechanism based on the robust LTS method to detect the correct number of outliers in the each bootstrap sample. …”
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Thesis -
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Route Optimization System
Published 2005“…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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Final Year Project -
3
Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
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Fuzzy modeling using Bat Algorithm optimization for classification
Published 2018“…In order to solve it, Bat Algorithm method is implement in to optimization method in fuzzy modeling for classification. …”
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Undergraduates Project Papers -
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Optimal route checking using genetic algorithm for UiTM's bus services / Tengku Salman Fathi Tengku Jaafar
Published 2006“…This research study with the development of the Optimal Route Checking Using Genetic Algorithm system should solve this scenario. …”
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Thesis -
6
Optimize class time tabling by using genetic algorithm technique in UTHM
Published 2019“…This research used genetic algorithm (GA) that was applied to java programming languages with a goal of reducing conflict and optimizing the fitness. …”
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Thesis -
7
A comprehensive overview of classical and modern route planning algorithms for self-driving mobile robots
Published 2022“…Classical or traditional methods, such as Roadmaps (Visibility Graph and Voronoi Diagram), Potential Fields, and Cell Decomposition, and modern methodologies such as heuristic-based (Dijkstra Method, A* Algorithms, and D* Algorithms), metaheuristics algorithms (such as PSO, Bat Algorithm, ACO, and Genetic Algorithm), and neural systems such as fuzzy neural networks or fuzzy logic (FL) and Artificial Neural Networks (ANN) are described in this report. …”
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Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data
Published 2022“…However, in practice, high leverage points may lead to misleading results in solving variable selection problems. Therefore, a robust sure independence screening procedure based on the weighted correlation algorithm of MRFCH for high dimensional data is developed to address this problem. …”
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9
Input-output based relation combinatorial testing using whale optimization algorithm for generating near optimum number of test suite
Published 2025“…This study proposes a combinatorial testing method utilizing the Whale Optimization Algorithm (WOA). …”
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Features selection process can be considered a problem of global combinatorial optimization in machine learning. Genetic algorithm GA had been adopted to perform features selection method; however, this method could not deliver an acceptable detection rate, lower accuracy, and higher false alarm rates. …”
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Thesis -
11
Comparison of performances of Jaya Algorithm and Cuckoo Search algorithm using benchmark functions
Published 2022“…Metaheuristic algorithms have been used successfully for solving different optimization problems. …”
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Conference or Workshop Item -
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…Feature subset selection and classifier ensemble learning are familiar techniques with high ability to optimize above problems. Recently, various techniques based on different algorithms have been developed. …”
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Thesis -
13
Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System
Published 2020“…Many optimisation-based intrusion detection algorithms have been developed and are widely used for intrusion identification. …”
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Article -
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Kernel and multi-class classifiers for multi-floor wlan localisation
Published 2016“…For fingerprint database optimisation, novel access point (AP) selection algorithms which are based on variant AP selection are investigated to improve computational accuracy compared to existing AP selection algorithms such as Max-Mean and InfoGain. …”
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Thesis -
15
Hybrid Harmony Search Algorithm with Grey Wolf Optimizer and Modified Opposition-based Learning
Published 2019“…In this paper, a hybrid algorithm of HS with grey wolf optimizer (GWO) has been developed to solve the problem of HS parameter selection. …”
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Improvement of Neural Network performance by data selection using Radial Basis Function and Hybrid Multilayered Perceptron network / Ahmad Puad Ismail, Nazirah Mohamat Kasim and S...
Published 2008“…This thesis presents the implementation of Radial Basis Function (RBF) and Hybrid Multilayered Perceptron(HMLP) Neural Network for a classical controller modeling. The word modeling means to develop or to model the controller by using the RBF and HMLP Neural Network that has the ability to predict the output just like the classical controller. …”
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Research Reports -
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Optimal reactive power dispatch using multistage artificial immune system
Published 2023“…This process includes cloning and mutation as well as selection. These modifications also aid in the development of new and unique solutions, as opposed to the classical AIS optimization process. …”
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Cognitive selection mechanism performance in IEEE 802.11 WLAN
Published 2013“…The enhancement reaped from the developed selection algorithm is expected to bring benefit to different user at various places…”
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Article -
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Robust variable selection methods for large- scale data in the presence of multicollinearity, autocorrelated errors and outliers
Published 2016“…We develop Robust Forward Selection algorithm based on RFCH correlation coefficient (RFS.RFCH) because FS.Winso is not robust to multivariate outliers. …”
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