Search Results - (( pre optimization based algorithm ) OR ( data visualisation using algorithm ))
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High Rise Building Evacuation Route Model Using DIJKSTRA'S Algorithm
Published 2015“…The main algorithms involve is Dijkstra’s algorithm and then an Ant Colony Optimization algorithm is used as hybrid versions of Dijkstra’s algorithm. …”
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Multi-dimensional Data Visualisation using Mobile Augmented Reality
Published 2020“…Therefore, this algorithm uses AR to provide a multi-display solution for improved data visualisation after processing, summarising and classifying data. …”
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Effectiveness of silhouette rendering algorithms in terrain visualisation
Published 2002“…Silhouette Rendering Algorithms have been successfully used in various applications such as communicating shape and cartoon rendering.This paper explores how effective silhouette rendering algorithms could be used in terrain visualisation. …”
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Visualisation System of COVID-19 Data in Malaysia
Published 2021“…This study aims to provide a system, using COVID-19 data as a sample to visualise and analyse cases, deaths, discharged ICU cases updates in Malaysia as a whole state wise of COVID-19 daily statistics. …”
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3D terrain visualisation for GIS: A comparison of different techniques
Published 2011“…The results of this paper will be of help to the users in identifying the best technique of terrain visualisation suitable for GIS data.…”
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Visualisation System of COVID-19 Data in Malaysia
Published 2021“…This study aims to provide a system, using COVID-19 data as a sample to visualise and analyse cases, deaths, discharged ICU cases updates in Malaysia as a whole state wise of COVID-19 daily statistics. …”
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Optimizing Cloud Storage Costs: Introducing the Pre-Evaluation-Based Cost Optimization (PECSCO) Mechanism
Published 2025“…The core of the algorithm utilizes a Genetic Algorithm (GA) to find the optimal position for the first evaluator by minimizing the total distance between this evaluator and all CCTV nodes, aiming for surveillance efficiency. …”
Conference paper -
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A COMPARISON STUDY OF DATA CLUSTERING AND VISUALISATION TECHNIQUES WITH VARIOUS DATA TYPES
Published 2020“…Clustering is used to identify the intrinsic grouping of a set of unlabelled data. …”
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One day ahead daily peak hour load forecasting by using invasive weed optimization learning algorithm based Artificial Neural Network
Published 2012“…Hence, this indicates that Invasive Weed Optimization could be implemented as a new learning algorithm for an Artificial Neural Network.…”
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Effects of Different Superpixel Algorithms on Interactive Segmentations
Published 2022“…In this study, five different types of superpixels ranging from watershed, density, graph, clustering and energy optimization categories are evaluated. The superpixels generated by these five algorithms will be used on two interactive image segmentation algorithms: i) Maximal Similarity based Region Merging (MSRM) and ii) Graph-Based Manifold Ranking (GBMR) with single and multiple strokes on various images from the Berkeley image dataset. …”
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A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification
Published 2023“…Moreover, K-Nearest Neighbor (KNN) classifier was used to evaluate the effectiveness of the features identified by the proposed SCSO algorithm. The performance of the proposed SCSO algorithm was compared with six state-of-the-art and recent wrapper-based optimization algorithms using the validation metrics of classification accuracy, optimum feature size, and computational cost in seconds. …”
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A case study : 2D Vs 3D parallel differential equation toward tumor cell detection on multi-core parallel computing atmosphere
Published 2010“…In order to detect tumour cells, 2D and 3D Partial Differential Equations (PDE) are considered and compared by using Multi-Core parallel computing atmosphere with visualisation, communication and data analysis. …”
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Improved opposition-based particle swarm optimization algorithm for global optimization
Published 2021“…Particle Swarm Optimization (PSO) has been widely used to solve various types of optimization problems. …”
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Feature selection based on particle swarm optimization algorithm for sentiment analysis classification
Published 2021“…An improved approach was proposed to increase the sentiment analysis accuracy based on text pre-processing and Naïve Bayes Classifier algorithm hybrid with Particle Swarm Optimization (NBC-PSO). …”
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16
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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Dynamic modeling by usage data for personalization systems
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Effects of Different Superpixel Algorithms on Interactive Segmentations
Published 2022“…In this study, five different types of superpixels ranging from watershed, density, graph, clustering and energy optimization categories are evaluated. The superpixels generated by these five algorithms will be used on two interactive image segmentation algorithms: i) Maximal Similarity based Region Merging (MSRM) and ii) Graph-Based Manifold Ranking (GBMR) with single and multiple strokes on various images from the Berkeley image dataset. …”
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A New Pre-Processing Technique For Computational Of Stereo Matching Algorithm
Published 2021“…At the fourth stage; disparity optimization stage, the disparity map is optimized with a common local technique, Winner-Take-All (WTA). …”
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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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