Search Results - (( data motion learning algorithm ) OR ( java simulation optimization algorithm ))
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Fish Motion Trajectories Detection Algorithm Based on Spiking Neural Network (S/O: 12893)
Published 2017“…In the most predictive application, Backpropagation (BP) has been used to learn the behavioural motion pattern. In terms of plausibility, BP has several drawbacks due to the lack in functionalities in complex data (e.g. spatio-temporal data). …”
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Study of machine learning in computer vision using Raspberry Pi
Published 2024text::Final Year Project -
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…The simulation is implemented with iFogSim and java programming language. …”
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Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing
Published 2011“…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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Ant colony optimization algorithm for load balancing in grid computing
Published 2012“…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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Monograph -
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Motion learning using spatio-temporal neural network
Published 2020“…In this study, learning is implemented on a reward basis without the need for learning targets.The algorithm has shown good potential in learning motion trajectory particularly in noisy and dynamic settings. …”
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OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT
Published 2023“…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. …”
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
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9
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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10
Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy
Published 2019“…As for classification, researchers have used semi-supervised learning for extreme learning machine (ELM), where they have exploited both the labeled and unlabeled data in order to boost the learning performances. …”
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Resource management in grid computing using ant colony optimization
Published 2011“…Resources with high pheromone value are selected to process the submitted jobs.Global pheromone update is performed after completion processing the jobs in order to reduce the pheromone value of resources.A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against other ant based algorithm, in terms of resource utilization.Experimental results show that EACO produced better grid resource management solution.…”
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Monograph -
12
Fuzzy-based classifier design for determining the eye movement data as an input reference in wheelchair motion control
Published 2015“…In this paper, the fuzzy-based classifiers were designed in order to determine the eye movement data. These data were used as an input reference in wheelchair motion control. …”
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Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter
Published 2019“…Cloudsim is used as Discrete Event Simulation tool and Java as coding language to evaluate LACE algorithm. …”
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Multi-sensor fusion and deep learning framework for automatic human activity detection and health monitoring using motion sensor data / Henry Friday Nweke
Published 2019“…Third, to propose orientation invariant based deep spare autoencoder methods for automatic complex activity identification to minimize orientation inconsistencies and learn adequate data patterns. Furthermore, to confirm the performances of the proposed multi-sensor fusion methods using challenging motion sensor data generated using smartphones and wearable sensors. …”
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15
Identification and control of a small-scale helicopter
Published 2010“…This identification process is based on the well-known gradient descent learning algorithm. As a case study, the multiple-input multiple-output (MIMO) model predictive control (MPC) is applied to control the pitch motion of the helicopter. …”
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Immersive AR pet game with hand motion
Published 2023“…Unity provides a cross-platform development environment for AR applications that run on different devices with varying capabilities. ManoMotion is a hand-tracking software that uses machine learning algorithms to track and recognise hand movements in real-time. …”
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A Novel Path Prediction Strategy for Tracking Intelligent Travelers
Published 2009“…It is proposed and shown that route-like intelligent motion is based on a combination of decisional and kinematical factors. …”
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An enhanced version of black hole algorithm via levy flight for optimization and data lustering problems
Published 2019“…Additionally, LBH is then tested using six real datasets available from UCI machine learning laboratory. The experimental outcomes obtained indicated the designed algorithm’s suitability for data clustering, displaying effectiveness and robustness.…”
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Revolutionizing Perimeter Intrusion Detection: A Machine Learning-Driven Approach with Curated Dataset Generation for Enhanced Security
Published 2023“…To solve the above problem, we designed a prototype for PIDS using a DHT22 temperature and humidity sensor, vibration sensor SW- 420 Module Pinout, Mini PIR motion sensor, and Arduino UNO. After collecting the data from above mentioned sensors we applied machine learning algorithms DBSCAN to cluster the data points and K-NN classification to classify those clusters in one-dimensional data, but the results were not much satisfying. …”
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