Search Results - ((((cloud algorithm) OR (tree algorithm))) OR (_ algorithm))
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Individual-tree segmentation and extraction based on LiDAR point cloud data
Published 2024“…In the task of individual tree extraction, the point cloud distance discriminant clustering algorithm outperformed the watershed algorithm. …”
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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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Hardware development of autonomous mobile robot based on actuating lidar
Published 2022“…From here, the extracted values are implied on k-NN, Decision Tree and CNN training algorithm. The final result shows promising potential with 91% prediction when implemented on the Decision Tree algorithm based on our proposed system of a single actuating LiDAR sensor.…”
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Treemap algorithm for dynamic stormwater infiltration movement into soil surface
Published 2015“…Although most of the previous studies use Tree algorithm for 2D analysis, this study highlights the capability of the algorithm in 3D analysis by producing hierarchy for soil depth.…”
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Treemap algorithm for dynamic stormwater infiltration movement into soil surface
Published 2015“…Although most of the previous studies use Tree algorithm for 2D analysis, this study highlights the capability of the algorithm in 3D analysis by producing hierarchy for soil depth.…”
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Extracting crown morphology with a low-cost mobile LiDAR scanning system in the natural environment
Published 2021“…The system uses a LiDAR-IMU tight coupling odometry method to reconstruct a point cloud map of the area surveyed. After using the RANSAC algorithm to remove the map ground, the European clustering algorithm is used for point cloud segmentation. …”
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Oil palm mapping over Peninsular Malaysia using Google Earth Engine and machine learning algorithms
Published 2020“…In this study, 30 m Landsat 8 data were processed using a cloud computing platform of Google Earth Engine (GEE) in order to classify oil palm land cover using non-parametric machine learning algorithms such as Support Vector Machine (SVM), Classification and Regression Tree (CART) and Random Forest (RF) for the first time over Peninsular Malaysia. …”
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Detection of mature and immature oil palm from image Sentinel-2 using Google Earth Engine (GEE) / Nurul Ain Nabilah Sharuddin
Published 2022“…Four (4) machine learning algorithms are used in classification, such as Random Forest (RF), smile Classification and Regression Tree (smileCART), Gradient Tree Boost (GTB), and Minimum Distance (MD). …”
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Area-based vs tree-centric approaches to mapping forest carbon in Southeast Asian forests from airborne laser scanning data
Published 2017“…Tree-centric modelling is appealing because it is based on summing the biomass of individual trees, but until algorithms can detect understory trees reliably and estimate biomass from crown dimensions precisely, areas-based modelling will remain the method of choice.…”
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Performance-aware cost-effective brokering and load balancing algorithms for data center in large scale cloud computing
Published 2015“…Proposed cloud brokering algorithms works with different types of cloud provider and deal with various user requirements. …”
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Prediction of Oil Palm Yield Using Machine Learning in the Perspective of Fluctuating Weather and Soil Moisture Conditions: Evaluation of a Generic Workflow
Published 2023“…Selected regression models were compared with Random Forest, Gradient Boosting, Decision Tree, and other non-tree algorithms to prove the R2 driven performance superiority of tree-based ensemble models. …”
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Task scheduling in cloud computing environment using hybrid genetic algorithm and bat algorithm
Published 2022“…Furthermore, CloudSim simulator will be used to evaluate the performance of this algorithm. …”
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Locust- inspired meta-heuristic algorithm for optimising cloud computing performance
Published 2023Subjects: “…Heuristic algorithms…”
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Task scheduling in cloud computing environment using hybrid of genetic algorithm and naked mole rat algorithm (GA-NMRA)
Published 2022“…Task scheduling and resource allocation are essential aspects of cloud computing. This research proposes task scheduling in cloud computing using a hybrid genetic algorithm and naked mole rat algorithm to solve the task scheduling problem. …”
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A priority based job scheduling algorithm in cloud computing
Published 2012“…Job scheduling algorithms is one of the most challenging theoretical issues in the cloud computing area. …”
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System program management environment in cloud computing using hybrid Genetic Algorithm and Moth Flame Optimization (GA-MFO)
Published 2022“…In this project, Genetic Algorithms (GA) is combine Moth Flame Optimization (MFO) to improve the cloud computing environment. …”
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Tag clouds algorithm with the inclusion of personality traits
Published 2015“…Furthermore, the algorithm to generate tag cloud visualization based on personality traits has not been explored. …”
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Performance evaluation of load balancing algorithm for virtual machine in data centre in cloud computing
Published 2018“…Cloud computing has become biggest buzz in the computer era these days.It runs entire operating systems on the cloud and doeverything on cloud to store data off-site.Cloud computing is primarily based on grid computing, but it’s a new computational model.Cloud computing has emerged into a new opportunity to further enhance way of hosting data centre and provide services.The primary substance of cloud computing is to deal the computing power,storage,different sort of stages and services which assigned tothe external users on demand through the internet.Task scheduling in cloud computing is vital role optimisation and effective dynamic resource allocation for load balancing.In cloud, the issue focused is under utilisation and over utilisation of the resources to distribute workload of multiple network links for example,when cloud clients try to access and send request tothe same cloud server while the other cloud server remain idle at that moment, leads to the unbalanced of workload on cloud data centers.Thus, load balancing is to assign tasks to the individual cloud data centers of the shared system so that no single cloud data centers is overloaded or under loaded.A Hybrid approach of Honey Bee (HB) and Particle Swarm Optimisation (PSO) load balancing algorithm is combined in order to get effective response time.The proposed hybrid algorithm has been experimented by using CloudSim simulator.The result shows that the hybrid load balancing algorithm improves the cloud system performance by reducing the response time compared to the Honey Bee (HB) and Particle Swarm Optimisation (PSO) load balancing algorithm.…”
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Multi-objective algorithms for effective resource management in Edge-Fog-Cloud computing
Published 2023“…Simulations were conducted to evaluate the proposed algorithms compared to the PSO algorithm, Cloud-Fog Cooperation Scheduling algorithm, and Task offloading algorithm. …”
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