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Forecasting of individual electricity consumption using Optimized Gradient Boosting Regression with Modified Particle Swarm Optimization.

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Temporal analysis of lung lesions through dynamic shape features., , , , and . Comput. Electr. Eng., (2019)Segmentation and quantification of COVID-19 infections in CT using pulmonary vessels extraction and deep learning., , , , , , , , , and 11 other author(s). Multim. Tools Appl., 80 (19): 29367-29399 (2021)Prediction of unregistered power consumption lawsuits and its correlated factors based on customer data using extreme gradient boosting model., , , , , , , , , and 3 other author(s). SMC, page 2059-2064. IEEE, (2019)Heart segmentation in planning CT using 2.5D U-Net++ with attention gate., , , , , , , , and . Comput. methods Biomech. Biomed. Eng. Imaging Vis., 11 (3): 317-325 (May 2023)Forecasting of individual electricity consumption using Optimized Gradient Boosting Regression with Modified Particle Swarm Optimization., , , , , , , , , and 7 other author(s). Eng. Appl. Artif. Intell., (2021)Practical Findings from Applying Quality Assurance Activities in the Development of Three Information Systems for Power Companies., , , , , , , , , and 1 other author(s). ICEIS (2), page 159-166. SCITEPRESS, (2022)