Search Results - (( probable distribution sensor algorithm ) OR ( probable distribution tree algorithm ))
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Winsorize tree algorithm for handling outliers in classification problem
Published 2016“…This study proposes a modified classification tree algorithm called Winsorize tree based on the distribution of classes in the training dataset. …”
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Energy Efficient LEACH (EE-LEACH) Routing Algorithm for Wireless Sensor Networks
Published 2019“…Therefore, this research work proposes an energy-efficient LEACH (EE-LEACH) algorithm to elect CHs based on residual energy, RSSI, and random probability to distribute the load evenly among the CHs. …”
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Energy efficient cluster head distribution in wireless sensor networks
Published 2013“…For network clustering, the distribution of CH selection directly influences the networks lifetime. …”
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Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari
Published 2015“…We first look at the concentration parameter of von Mises distribution. The von Mises distribution is the most commonly used probability distribution of a circular random variable, and the concentration of a circular data set is measured using the mean resultant length. …”
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Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…In comparison, WISDM utilizes an accelerometer sensor embedded in Android smartphone. Meanwhile, PAMAP2 utilizes an accelerometer sensor equipped with three Inertial Measurement Unit (IMU) devices attached to three different placements. …”
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EFFICIENT DYNAMIC ADDRESSING BASED ROUTING FOR UNDERWATER WIRELESS SENSOR NETWORKS
Published 2011“…Besides long propagation delays and high error probability, continuous node movement also makes it difficult to manage the routing information during the process of data forwarding. …”
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Prediction of rice biomass using machine learning algorithms
Published 2022“…The Q-TESI, C-TESI, and L-TESI overcame the LN-TESI in retaining the features’ original probability distribution, minimising the augmentation loss, reducing the VIF, increasing the rs, and decreasing the DNN under- and overfitting. …”
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