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1
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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2
Variable step size least mean square optimization for motion artifact reduction: A review
Published 2019“…Therefore, we propose a research to formulate an improved motion artifact reduction approach using variable step-size least mean square (VSSLMS). …”
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Applying machine learning and particle swarm optimization for predictive modeling and cost optimization in construction project management
Published 2024“…Evaluation metrics such as Mean Squared Error, Root Mean Squared Error, Mean Absolute Error, and R-squared are commonly employed in the assessment of Machine Learning models' performance. …”
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4
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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5
Improved measurement of blood pressure by extraction of characteristic features from the cuff oscillometric waveform
Published 2015“…Substantial reduction in the mean and standard deviation of the blood pressure estimation errors were obtained upon artifact removal. …”
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6
Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things
Published 2022“…Furthermore, this was accomplished with only 25 neurons which means a reduction of the number of neurons by a percentage of 75%. …”
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7
Cleansing of inconsistent sample in linear regression model based on rough sets theory
Published 2023“…The linear regression model is one of the most common and easiest algorithms used in machine learning for predictive analysis purposes. …”
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8
Cleansing of inconsistent sample in linear regression model based on rough sets theory
Published 2023“…The linear regression model is one of the most common and easiest algorithms used in machine learning for predictive analysis purposes. …”
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9
Cleansing of inconsistent sample in linear regression model based on rough sets theory
Published 2023“…The linear regression model is one of the most common and easiest algorithms used in machine learning for predictive analysis purposes. …”
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10
Cleansing of inconsistent sample in linear regression model based on rough sets theory
Published 2023“…The linear regression model is one of the most common and easiest algorithms used in machine learning for predictive analysis purposes. …”
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11
Development of a phantom and metal artifact correction (MAC) algorithm for post-operative spine computed tomography (CT) imaging / Noor Diyana Osman
Published 2014“…The last part is the development of a metal artifact correction (MAC) algorithm and evaluation of the proposed algorithm in artifacts reduction in CT images. …”
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12
Cleansing of inconsistent sample in linear regression model based on rough sets theory
Published 2023“…The linear regression model is one of the most common and easiest algorithms used in machine learning for predictive analysis purposes. …”
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13
Cleansing of inconsistent sample in linear regression model based on rough sets theory
Published 2023“…The linear regression model is one of the most common and easiest algorithms used in machine learning for predictive analysis purposes. …”
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14
Cleansing of inconsistent sample in linear regression model based on rough sets theory
Published 2023“…The linear regression model is one of the most common and easiest algorithms used in machine learning for predictive analysis purposes. …”
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15
Cleansing of inconsistent sample in linear regression model based on rough sets theory
Published 2023“…The linear regression model is one of the most common and easiest algorithms used in machine learning for predictive analysis purposes. …”
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16
Cleansing of inconsistent sample in linear regression model based on rough sets theory
Published 2023“…The linear regression model is one of the most common and easiest algorithms used in machine learning for predictive analysis purposes. …”
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17
Comparative Analysis of Artificial Intelligence Methods for Streamflow Forecasting
Published 2024“…For this dataset, wavelet transformation significantly improves the resolution of lag noise when historical streamflow data are used as lagged input variables, producing a 6% reduction in the root-mean-square error. …”
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18
Chemometrics analysis for the detection of dental caries via ultraviolet absorption spectroscopy / Katrul Nadia Basri
Published 2023“…The best result of ANN model obtained were 0.85, 0.8, 0.57 and 0.92 for accuracy, precision, sensitivity and specificity. Dimension reduction algorithm such as LDA and CNN were applied on the spectra to reduce the number of variables to be trained. …”
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Optimal planning of photovoltaic distributed generation considering uncertainties using monte carlo pdf embedded MVMO-SH
Published 2021“…A hybrid population – based stochastic optimization method named MVMO-SH algorithm is proposed to optimize PVDG locations and sizes in the grid system network. …”
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