Search Results - (( its application learning algorithm ) OR ( some applications cloud algorithm ))*
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Cloud-based lightweight detection of hardhat compliance based on YOLOv5 in power construction site
Published 2025“…Therefore, this thesis explores and studies public hardhat datasets, deep learning algorithms, power Internet of Things (PIoT), and edge computing to address the above issues. …”
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Thesis -
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A priority based job scheduling algorithm in cloud computing
Published 2012“…Nowadays cloud computing has become a popular platform for scientific applications. …”
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Conference or Workshop Item -
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Task scheduling in cloud computing using hybrid genetic algorithm and bald eagle search (GA-BES)
Published 2022“…Task scheduling and resource allocation are essential aspects of cloud computing. This Study proposes task scheduling in cloud computing using a hybrid genetic algorithm, and bald eagle search proposed to solve the task scheduling problem. …”
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Academic Exercise -
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Two objectives big data task scheduling using swarm intelligence in cloud computing
Published 2016“…In this direction, this paper first gives review of some previous scheduling algorithms used in cloud. …”
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Development of heuristic task scheduling algorithm in cloud computing
Published 2016“…To this direction, in this paper we make a summary of some scheduling algorithms and propose an Enhanced Greedy Heuristic Scheduling Algorithm (EGHSA) for task scheduling adapted for big data applications. …”
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Conceptual deployment models to secure cloud computing / Hajar Ziglari
Published 2012“…Objectives contain identifying data security attributes and threats for cloud, discovering some strategies to recover the cloud computing service delivery to business performance and customers and developing a new model to cover some security issues. …”
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Thesis -
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Load balancing and server consolidation in cloud computing environments: a meta-study
Published 2019“…The data-center is considered the heart of cloud computing. Recently, the growing demand for cloud computing services has caused a growing load on data centers. …”
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Efficient task scheduling strategies using symbiotic organisms search algorithm for cloud computing environment
Published 2022“…However, the efficiency of the clouds drops as the size of the search space gets larger, like in the case of most metaheuristic optimisation algorithms. …”
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Hardware development of autonomous mobile robot based on actuating lidar
Published 2022“…However, high-end LiDAR sensors are high in cost and require high computational costs. In some applications such as navigation for blind people, sparse LiDAR point cloud are more applicable as they can be quickly generated and processed. …”
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Critical insight for MAPReduce optimization in Hadoop
Published 2014“…Cloud applications such as data storage, data retrieval and data portability have become significant requirements for cloud computing. …”
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Cloud-Mobi Framework using hybrid AHP-ACO method for Social Interaction and Travel Planning
Published 2013“…The implementation has shown that the proposed Cloud-Mobi framework is promising for travel recommendation applications. …”
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Conference or Workshop Item -
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Effect of chaos noise on the learning ability of back propagation algorithm in feed forward neural network
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Working Paper -
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A modified generalized RBF model with EM-based learning algorithm for medical applications
Published 2006“…Radial Basis Function (RBF) has been widely used in different fields, due to its fast learning and interpretability of its solution. …”
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Proceeding Paper -
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SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA
Published 2012“…This thesis gives a systematic investigation of various MLP learning mainly Sliding Window (SW) learning mode which is treated as the adaptation of offline algorithms into online application Consequently this thesis reviews various offline algorithms including: batch backpropagation, nonlinear conjugate gradient, limited memory and full-memory Broyden, Fletcher, Goldfarb and Shanno algorithms and different forms of the latest proposed bimary ensemble learning. …”
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Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection
Published 2020“…Two main improvements were included into the original SSA algorithm to alleviate its drawbacks and adapt it for feature selection problems. …”
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