Search Results - (( java segmentation using algorithm ) OR ( knowledge set implementation algorithm ))
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1
Image clustering comparison of two color segmentation techniques
Published 2010“…Finally, the algorithm found, which would solve the image segmentation problem.…”
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Thesis -
2
Automatic Number Plate Recognition on android platform: With some Java code excerpts
Published 2016“…On the other hand, the traditional algorithm using template matching only obtained 83.65% recognition rate with 0.97 second processing time. …”
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Development of seven segment display recognition using TensorFlow on Raspberry Pi
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Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof
Published 2019“…In the algorithm development a step-by-step example of the algorithm implementation is presented and then successfully implemented in Lego Mindstorm obstacle avoiding mobile robot as a proof of concept implementation of the hybrid AI algorithm. …”
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5
Discovering decision algorithm of distance protective relay based on rough set theory and rule quality measure
Published 2011“…Thus, this thesis addresses these issues with the objective of intelligently divulging the knowledge hidden in the recorded event report at a relay device level using a data mining strategy based on Rough Set Theory, Genetic Algorithm and Rule Quality Measure under supervised learning within the framework of Knowledge Discovery in Database (KDD) in order to discover the relay’s decision algorithm (prediction rules) and, subsequently, the association rule. …”
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Discovering association rules for mining images datasets: a proposal
Published 2005“…A synthetic image set containing geometric shapes will generate to test the initial algorithm implementation. …”
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Conference or Workshop Item -
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Green building valuation based on machine learning algorithms / Thuraiya Mohd ... [et al.]
Published 2021“…This experiment used five common machine learning algorithms namely 1) Linear Regressor, 2) Decision Tree Regressor, 3) Random Forest Regressor, 4) Ridge Regressor and 5) Lasso Regressor tested on a real estate data-set of covering Kuala Lumpur District, Malaysia. 3 set of experiments was conducted based on the different feature selections and purposes The results show that the implementation of 16 variables based on Experiment 2 has given a promising effect on the model compare the other experiment, and the Random Forest Regressor by using the Split approach for training and validating data-set outperformed other algorithms compared to Cross-Validation approach. …”
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9
Implementing BiSM and CCL algorithm for managing audio storage
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10
Bayesian Network Classifiers for Damage Detection in Engineering Material
Published 2007“…The methodology used in the thesis to implement the Bayesian network for the damage detection provides a preliminary analysis used in proposing a novel fea- ture extraction algorithm (f-FFE: the f-folds feature extraction algorithm). …”
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11
Discovering decision algorithm from a distance relay event report
Published 2009“…In this study rough-set-based data mining strategy was formulated to discover distance relay decision algorithm from its resident event report. …”
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Comparative study of apriori-variant algorithms
Published 2016“…However, the algorithm suffers from scanning time problem while generating candidates of frequent itemsets.This study presents a comparative study between several Apriori-variant algorithms and examines their scanning time.We performed experiments using several sets of different transactional data.The result shows that the improved Apriori algorithm manage to produce itemsets faster than the original Apriori algorithm.…”
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Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…The rest sets of experiments carried out to evaluate the proposed algorithms. …”
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14
Rough-Set-and-Genetic-Algorithm based data mining and Rule Quality Measure to hypothesize distance protective relay operation characteristics from relay event report
Published 2011“…Firstly, the data mining approach of the integrated-Rough-Set-and-Genetic-Algorithm is used to discover the relay CD-decision algorithm. …”
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A case study on quality of sleep and health using Bayesian networks
Published 2012“…There are several phases involved including implementation of the learning algorithms, integration of prior knowledge through the whitelist argument and arc setting to form directed acyclic graphs. …”
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Development of a modified adaptive protection scheme using machine learning technique for fault classification in renewable energy penetrated transmission line
Published 2020“…The high-cost of implementations, cyber-attack, and latency concerns from the adopted communication channels for the standard APS relay characteristic setting and selection is another drawback identified. …”
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17
Comparing the knowledge quality in rough classifier and decision tree classifier
Published 2008“…Theoretically, different classifiers will generate different sets of rules via knowledge even though they are implemented to the same classification problem.Hence, the aim of this paper is to investigate the quality of knowledge produced by Rc and DTc when similar problems are presented to them.In this case, four important performance metrics are used as comparison, the accuracy of classification, rules quantity, rules length and rules coverage.Five dataset from UCI Machine Learning are chosen and then mined using Rc toolkit namely ROSETTA while C4.5 algorithm in WEKA application is chosen as DTc rule generator. …”
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Recursive least squares-based adaptive control of a biodiesel transesterification reactor
Published 2010“…The results attained in this work demonstrate that a good adaptive control scheme can be implemented for the biodiesel transesterification reactors with minimal knowledge about the process model.…”
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19
Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
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