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Predicting minority class for suspended particulate matters level by extreme learning machine.

, , , and . Neurocomputing, (2014)

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Modelling and Prediction of Electronically Controlled Automotive Engine Power and Torque Using Support Vector Machines., , , and . LAPTEC, volume 132 of Frontiers in Artificial Intelligence and Applications, page 87-96. IOS Press, (2005)Inspection and control of vehicle emissions through Internet of Things and traffic lights., , , and . ICCVE, page 863-868. IEEE, (2013)Empirical kernel map-based multilayer extreme learning machines for representation learning., , and . Neurocomputing, (2018)Simultaneous faults diagnosis for automotive ignition patterns., , and . ICMLC, page 1324-1330. IEEE, (2011)Hybrid model predictive controller for engine air-ratio control., , , and . ICARCV, page 181-186. IEEE, (2014)Feature-Based Direct Tracking and Mapping for Real-Time Noise-Robust Outdoor 3D Reconstruction Using Quadcopters., , , and . IEEE Trans. Intell. Transp. Syst., 23 (11): 20489-20505 (2022)Predicting minority class for suspended particulate matters level by extreme learning machine., , , and . Neurocomputing, (2014)Post-boosting of classification boundary for imbalanced data using geometric mean., , , , and . Neural Networks, (2017)Prediction of automotive engine power and torque using least squares support vector machines and Bayesian inference., , and . Eng. Appl. Artif. Intell., 19 (3): 277-287 (2006)Efficient Outdoor 3D Point Cloud Semantic Segmentation for Critical Road Objects and Distributed Contexts., and . ECCV (27), volume 12372 of Lecture Notes in Computer Science, page 499-514. Springer, (2020)