Search Results - (( java application optimization algorithm ) OR ( pre optimization means algorithm ))
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Optimized clustering with modified K-means algorithm
Published 2021“…Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
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Thesis -
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Optimization of blood vessel detection in retina images using multithreading and native code for portable devices
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Performance evaluation of real-time multiprocessor scheduling algorithms
Published 2016“…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. …”
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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 -
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A Hybrid Least Squares Support Vector Machine with Bat and Cuckoo Search Algorithms for Time Series Forecasting
Published 2020“…However, its operation relies on two important parameters (regularization and kernel). Pre-determining the values of parameters will affect the results of the forecasting model; hence, to find the optimal value of these parameters, this study investigates the adaptation of Bat and Cuckoo Search algorithms to optimize LSSVM parameters. …”
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Discovering optimal clusters using firefly algorithm
Published 2016“…Existing conventional clustering techniques require a pre-determined number of clusters, unluckily; missing information about real world problem makes it a hard challenge.A new orientation in data clustering is to automatically cluster a given set of items by identifying the appropriate number of clusters and the optimal centre for each cluster.In this paper, we present the WFA_selection algorithm that originates from weight-based firefly algorithm.The newly proposed WFA_selection merges selected clusters in order to produce a better quality of clusters.Experiments utilising the WFA and WFA_selection algorithms were conducted on the 20Newsgroups and Reuters-21578 benchmark dataset and the output were compared against bisect K-means and general stochastic clustering method (GSCM).Results demonstrate that the WFA_selection generates a more robust and compact clusters as compared to the WFA, bisect K-means and GSCM.…”
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Effective k-Means Clustering in Greedy Prepruned Tree-based Classification for Obstructive Sleep Apnea
Published 2022“…GPrTC algorithm showed better classification accuracies than k-means clustering in almost all the assigned datasets. …”
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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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Document clustering for knowledge discovery using nature-inspired algorithm
Published 2014“…As the internet is overload with information, various knowledge based systems are now equipped with data analytics features that facilitate knowledge discovery.This includes the utilization of optimization algorithms that mimics the behavior of insects or animals.This paper presents an experiment on document clustering utilizing the Gravitation Firefly algorithm (GFA).The advantage of GFA is that clustering can be performed without a pre-defined value of k clusters.GFA determines the center of clusters by identifying documents with high force.Upon identification of the centers, clusters are created based on cosine similarity measurement.Experimental results demonstrated that GFA utilizing a random positioning of documents outperforms existing clustering algorithm such as Particles Swarm Optimization (PSO) and K-means.…”
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Ant colony optimization algorithm for load balancing in grid computing
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Monograph -
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Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm
Published 2018“…It is attained successfully by combining the mean in K-Means algorithm, minimum and maximum in K-Midranges algorithm and compute their average as mean cluster of Hybrid mean. …”
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Thesis -
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Optimization of Multilayer Perceptron (MLP) network training algorithms for agrwood oil quality separation / Noratikah Zawani Mahabob ... [et al.]
Published 2020“…As a part of on-going research in classifying the agarwood oil quality, this research presented the optimization of the Multilayer Perceptron (MLP) network with the three different training data network algorithms; Scaled-Conjugate Gradient (SCG), Levenberg Marquardt (LM), and Resilient-Backpropagation (RBP). …”
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Comparative analysis of K-Means and K-Medoids for clustering exam questions / Nurul Zafirah Mokhtar
Published 2016“…Determining the suitable algorithm which can bring the optimized group clusters could be an issue. …”
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A Modified Symbiotic Organism Search Algorithm with Lévy Flight for Software Module Clustering Problem
Published 2020“…To date, there are much increasing trends on adopting parameter free meta-heuristic algorithms for solving general optimization problems. …”
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Fireflyclust: an automated hierarchical text clustering approach
Published 2017“…Various clustering algorithms have been reported in the literature but most of them rely on a pre-defined value of the k clusters. …”
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Computer Lab Timetabling Using Genetic Algorithm Case Study - Unit ICT
Published 2006“…Genetic Algorithm is one of the most popular optimization solutions used in various applications such as scheduling. …”
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Noise Cancellation method in assistive listening system
Published 2020“…Those algorithms were Least Means Square, Normalize-Least Means Square, Recursive Least Square, Simple SetMembership Algorithm and Dynamic Set-Membership Affine Projection Algorithm. …”
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Undergraduates Project Papers
