Search Results - (( developing fire learning algorithm ) OR ( java implementation mining algorithm ))
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Direct approach for mining association rules from structured XML data
Published 2012“…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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Thesis -
2
Study and Implementation of Data Mining in Urban Gardening
Published 2019“…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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Scalable approach for mining association rules from structured XML data
Published 2009“…Many techniques have been proposed to tackle the problem of mining XML data we study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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4
Mining association rules from structured XML data
Published 2009“…Many techniques have been proposed to tackle the problem of mining XML data. We study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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5
A web-based implementation of k-means algorithms
Published 2022“…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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6
Image clustering comparison of two color segmentation techniques
Published 2010“…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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7
Development of IoT-based automated dynamic emergency response system against fire incidents in academic building
Published 2023“…The proposed system leverages IoT technology, wireless and bluetooth sensor networks to gather real-time data from various sensors and devices installed in the site and uses machine learning algorithms to predict and prevent potential fire incidents. …”
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8
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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Density based subspace clustering: a case study on perception of the required skill
Published 2014“…This research aims to develop an improved model for subspace clustering based on density connection. …”
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11
Density subspace clustering: a case study on perception of the required skill
Published 2014“…This research aims to develop an improved model for subspace clustering based on density connection. …”
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12
Development of a smart edge device for fire detection
Published 2023“…This project proposes a smart edge fire detection system that overcomes the limitations of conventional fire warning systems by utilizing deep learning models and edge computing. …”
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CFD modeling on coal properties towards the burnout efficiency
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Development and application of an enhanced ART-Based neural network
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Working Paper -
15
Multi sensor network system for early detection and prediction of forest fires in southeast asia
Published 2023“…The collected data is then processed and analyzed using machine learning algorithms to identify fire patterns and predict the likelihood of fire outbreaks. …”
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16
The development of a tracking algorithm for ambulance detection using squaring of RGB and HSV color processing techniques
Published 2016“…In this study, a tracking algorithm is developed by means of image processing technique in detecting ambulance. …”
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ReSTiNet: An efficient deep learning approach to improve human detection accuracy
Published 2023“…ReSTiNet is a novel small convolutional neural network that overcomes the problems of network size, detection speed, and accuracy. The developed ReSTiNet contains fire modules by evaluating their number and position in the network to minimize the model parameters and network size. …”
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ReSTiNet: An Efficient Deep Learning Approach to Improve Human Detection Accuracy
Published 2023“…ReSTiNet is a novel small convolutional neural network that overcomes the problems of network size, detection speed, and accuracy. The developed ReSTiNet contains fire modules by evaluating their number and position in the network to minimize the model parameters and network size. …”
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20
ReSTiNet : An efficient deep learning approach to improve human detection accuracy
Published 2023“…ReSTiNet is a novel small convolutional neural network that overcomes the problems of network size, detection speed, and accuracy. The developed ReSTiNet contains fire modules by evaluating their number and position in the network to minimize the model parameters and network size. …”
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