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Full-Text Articles in Electrical and Computer Engineering
Wavelet-Coupled Machine Learning Methods For Drought Forecast Utilizing Hybrid Meteorological And Remotely-Sensed Data, R. Tan, Marek Perkowski
Wavelet-Coupled Machine Learning Methods For Drought Forecast Utilizing Hybrid Meteorological And Remotely-Sensed Data, R. Tan, Marek Perkowski
Electrical and Computer Engineering Faculty Publications and Presentations
In this study, a statistical drought early warning method is proposed using novel machine learning algorithms, with the inclusion of multiple drought-related attributes from precipitation, satellite-derived land cover vegetation indices, and surface discharge. The forecast is made for the long-term hydrological drought in the region of Central Valley, California. The wavelet transform analysis is employed in combination with support vector regression and artificial neural network algorithms for improving the drought prediction effectiveness. The performance of the drought prediction is evaluated using three statistical metrics: Coefficient of Determination (R2 ), Root-Mean-Square Error (RMSE), and Mean-Absolute-Error (MAE). The results clearly indicate that …
Functional Verification Of High Performance Adders In Coq, Qian Wang, Xiaoyu Song, Ming Gu, Jiaguang Sun
Functional Verification Of High Performance Adders In Coq, Qian Wang, Xiaoyu Song, Ming Gu, Jiaguang Sun
Electrical and Computer Engineering Faculty Publications and Presentations
Addition arithmetic design plays a crucial role in high performance digital systems. The paper proposes a systematic method to formalize and verify adders in a formal proof assistant COQ. The proposed approach succeeds in formalizing the gate-level implementations and verifying the functional correctness of the most important adders of interest in industry, in a faithful, scalable, and modularized way. The methodology can be extended to other adder architectures as well.