Search Results - (( variable negative selection algorithm ) OR ( java application optimisation algorithm ))
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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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Artificial immune system based on real valued negative selection algorithms for anomaly detection
Published 2015“…In this research, the Real-Valued Negative Selection with fixed-sized detectors (RNSA) and Real-Valued Negative Selection with variable-sized detectors (V-Detector) were applied for classification and detection of anomalies. …”
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Thesis -
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Mixed-variable ant colony optimisation algorithm for feature subset selection and tuning support vector machine parameter
Published 2017“…ACOMV-SVM algorithm is able to simultaneously tune SVM parameters and feature subset selection. …”
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Hybrid ACO and SVM algorithm for pattern classification
Published 2013“…The first two algorithms, ACOR-SVM and IACOR-SVM, tune the SVM parameters while the second two algorithms, ACOMV-R-SVM and IACOMV-R-SVM, tune the SVM parameters and select the feature subset simultaneously. …”
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5
An improved negative selection algorithm based on the hybridization of cuckoo search and differential evolution for anomaly detection
Published 2018“…Since the emergence of AIS, it has proved itself as an area of computational intelligence. Real-Valued Negative Selection Algorithm with Variable-Sized Detectors (V-Detectors) is an offspring of AIS and demonstrated its potentials in the field of anomaly detection. …”
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6
Development Of Fall Risk Clustering Algorithm In Older People
Published 2020“…A total of 1279 subjects and 9 variables from dataset (1411 subjects and 139 variables) are selected for clustering. t-Distributed Stochastic Neighbour Embedding (t-SNE) for feature extraction and K-means clustering algorithm achieved the highest performance in clustering, which grouping the subjects into Low (13%), Intermediate A (19%), Intermediate B (21%) and High (31%) fall risk group. …”
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Final Year Project / Dissertation / Thesis -
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Web-based expert system for material selection of natural fiber- reinforced polymer composites
Published 2015“…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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Predicting crop yield and field energy output for oil palm using genetic algorithm and neural network models
Published 2019“…Finally, this research concluded that a genetic algorithm is useful for selecting input variables in oil palm production. …”
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9
Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms
Published 2024“…The feature extraction methods evaluated were Grayscale Pixel Values, Mean Pixel Value of Channels, and Extracting Edge Features. The classification algorithm used in this research is the Convolutional Neural Network (CNN) algorithm. …”
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Coronary artery stenosis detection and visualization / Tang Sze Ling
Published 2015“…The performance evaluation results show that the stenosis detection algorithm performs better average sensitivity than several state-of-the-art algorithms.…”
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Advanced fault detection in DC microgrid system using reinforcement learning
Published 2021“…The results showed that the improved Negative Selection Algorithm with variable sized detector has better performance than the general Negative Selection Algorithm with constant sized radius in detecting fault in DC microgrid system.…”
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Proceedings -
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Modelling and investigating the impacts of climatic variables on ozone concentration in Malaysia using correlation analysis with random forest, decision tree regression, linear reg...
Published 2022“…The four machine learning algorithms exhibit high predictive performances, generally ascertaining the predictive accuracy of the climatic variables. …”
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Modelling and investigating the impacts of climatic variables on ozone concentration in Malaysia using correlation analysis with random forest, decision tree regression, linear reg...
Published 2022“…The four machine learning algorithms exhibit high predictive performances, generally ascertaining the predictive accuracy of the climatic variables. …”
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Developing A Prediction Tool To Improve The Shading Efficiency Of The Pedestrian Zones
Published 2020“…The development of the prediction tool was conducted base on integrating three sequenced algorithms, which are sun position algorithm, shadow length and position algorithm, and expansion limit algorithm. …”
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Determining malaria risk factors in Abuja, Nigeria using various statistical approaches
Published 2018“…Thus, the BBNs represent the dependencies in the variables better than assuming independence of all the variables. …”
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Effect of business social responsibility (BSR) on performance of SMEs in Nigeria
Published 2014“…This study used purposive sampling for sample selection. Partial Least Squares (PLS) algorithm and bootstrap techniques were used to test the study‘s hypotheses. …”
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Modelling knowledge transfer of nursing students during clinical placement / Nor Azairiah Fatimah Othman
Published 2017“…The influence of the variables selected for this study was tested on two distinct samples of Lower Semester Group, LSG (semester 1- 3) and Higher Semester Group, HSG (semester 4-6) separately… The assessment and improvement of angle stability condition of the power system using particle swarm optimization (PSO) technique / Nor Azwan Mohamed Kamari This thesis presents the assessment and improvement of stability domains for the angle stability condition of the power system using particle swarm optimization (PSO) technique. …”
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Book Section -
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Risk perception modeling based on physiological and emotional responses / Ding Huizhe
Published 2024“…However, the performance of these algorithms in situations with closely comparable risk magnitudes remains uncertain. …”
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Thesis
