Search Results - (( variable section learning algorithm ) OR ( java application sensor algorithm ))
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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…The process begins through the monitoring of plants using sensors connected to the Arduino device. Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. …”
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Design Of Robot Motion Planning Algorithm For Wall Following Robot
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Human activity recognition via accelerometer and gyro sensors
Published 2023“…To implement the data engineering system proposed, two mobile applications, SensorData and SensorDataLogger with user-friendly interfaces and intuitive functionalities are developed using Java programming language and Android Studio. …”
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Crossover and mutation operators of genetic algorithms
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Crossover and mutation operators of genetic algorithms
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Development of an explainable machine learning model for predicting depression in adults with type 2 diabetes mellitus: a cross-sectional SHAP-based analysis of NHANES 2009-2023
Published 2026“…Five machine learning algorithms - random forest, extreme gradient boosting (XGBoost), multilayer perceptron, logistic regression, and support vector machine - were trained and evaluated using 5-fold cross-validation. …”
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Advance speech recognition / Mohammad Amarulhariz Mohd Fairuz … [et al.]
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Design & Development of a Robotic System Using LEGO Mindstorm
Published 2006“…Since the model is built using LEGO bricks, the model is fully customized, in term of its applications, to perform any relevant tasks. Ultimately, the algorithm development program designed earlier is linked up directly to the robotic model for program implementation and verification. …”
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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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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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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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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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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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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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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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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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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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Evaluation of arima and ann stream analytics for air quality monitoring system
Published 2021“…It is observed that the data in MySQL are successfully exported to the R query table based on the similar number of variables between those two tables. The data stored in the query table act as input to the analytics algorithm, which runs in R-server as well. …”
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