Search Results - probable distribution ((clustering algorithm) OR (learning algorithm))
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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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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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Parameter estimation of K-distributed sea clutter based on fuzzy inference and Gustafson-Kessel clustering
Published 2011“…The algorithm also improves the calculations of shape and width of membership functions by means of clustering in order to improve the accuracy. …”
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Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari
Published 2015“…Here, we introduce a measure of similarity based on the circular distance and obtain a cluster tree using the single linkage clustering algorithm. …”
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Enhanced Q-Learning algorithm for potential actions selection in automated graphical user interface testing
Published 2023“…To overcome this limitation, the Q-Learning algorithm was proposed by several researchers to minimise randomness. …”
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Improving the exploration strategy of an automated android GUI testing tool based on the Q-Learning algorithm by selecting potential actions
Published 2022“…Furthermore, the proposed techniques based on the Q-Learning algorithm do not consider context-based actions. …”
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Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets
Published 2019“…The proposed algorithm is grounded on the two famous metaheuristic algorithms: cuckoo search (CS) and covariance matrix adaptation evolution strategy (CMA-es). …”
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Ab-initio calculations of the structural, electronic and optical properties of (CdSe)2 clusters
Published 2020“…The results show that the obtained absorption spectra peaks’ values (nm) are smaller compared to CdSe experimental results. (CdSe)2 clusters are very active that they straightforwardly react to produce larger clusters. …”
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Ab-initio Calculations of the Structural, Electronic and Optical Properties of (CdSe)2 Clusters
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Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…These kind of activities highly sparsely distributed in the input space which is problematic to be distinguish using traditional classifier model. …”
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Development of a multi criteria decision support system using convolutional neural network and jaya algorithm for water resources management / Chong Kai Lun
Published 2021“…The results indicated that the hydropower generated by the proposed algorithm could produce an evenly distributed high amount of energy increases the reliability of the reservoir system. …”
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Predictive Framework for Imbalance Dataset
Published 2012“…Experimental results suggested that the class probability distribution function of a prediction model has to be closer to a training dataset; less skewed environment enable learning schemes to discover better function F in a bigger Fall space within a higher dimensional feature space, data sampling and partition size is appear to proportionally improve the precision and recall if class distribution ratios are balanced. …”
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Comparative Analysis of Artificial Intelligence Methods for Streamflow Forecasting
Published 2024“…Deep learning excels at managing spatial and temporal time series with variable patterns for streamflow forecasting, but traditional machine learning algorithms may struggle with complicated data, including non-linear and multidimensional complexity. …”
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Population genetic structure of Malayan Tapir (Tapirus indicus Desmarest) in Peninsular Malaysia
Published 2019“…Eight polymorphic markers were successfully developed and used in the population genetic structure analysis. Using K-means clustering algorithm, five clusters were inferred among the wild samples (N = 57), which showed a complex population structure probably comprising multiple continuous populations that also experiencing considerably restricted gene flow due to isolation by geographical barriers especially mountain ranges. …”
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Prediction of rice biomass using machine learning algorithms
Published 2022“…Unmanned aerial vehicles (UAVs) may address these issues. Machine learning algorithms (MLs) can predict rice biomass from UAV-based vegetation indices (VIs). …”
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Incremental learning for large-scale stream data and its application to cybersecurity
Published 2015“…To process large-scale data sequences, it is important to choose a suitable learning algorithm that is capable to learn in real time. …”
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