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Estimating unknown parameters in differential equations with a reinforcement learning based PSO method

Autor: Sun, Wenkui, Fan, Xiaoya, Jia, Lijuan, Chu, Tinyi, Yau, Shing-Tung, Wu, Rongling, Wang, Zhong

Differential equations offer a foundational yet powerful framework for modeling interactions within complex dynamic systems and are widely applied across numerous scientific fields. One common challenge in this area is estimating the unknown paramete

Externí odkaz: http://arxiv.org/abs/2411.08651

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Akademický článek

Estimation and verification of autumn lettuce evapotranspiration in greenhouse based on single crop coefficient method

Autor: WU Jiale, LI Yinkun, ZHANG Zhonglili, LIU Meiying, LIU Shengyao, JIA Lijuan

Publikováno v: Guan'gai paishui xuebao, Vol 43, Iss 4, Pp 9-14 (2024)

【Objective】 The variation in evapotranspiration is an important parameter in irrigation design. In this paper, we propose and verify a modified single crop coefficient method to calculate the evapotranspiration of greenhouse lettuce. 【Method】

Externí odkaz: https://doaj.org/article/9bd201128c0147cfa307a072a6243f80

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Akademický článek

Multiscale feature-based robust secure diffusion estimation with noisy input over adversarial networks

Autor: Zhang, Zhanxi, Jia, Lijuan, Peng, Senran, Yang, Zi-Jiang, Tao, Ran

Publikováno v: In Digital Signal Processing December 2024 155

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Simple Contrastive Representation Adversarial Learning for NLP Tasks

Autor: Miao, Deshui, Zhang, Jiaqi, Xie, Wenbo, Song, Jian, Li, Xin, Jia, Lijuan, Guo, Ning

Self-supervised learning approach like contrastive learning is attached great attention in natural language processing. It uses pairs of training data augmentations to build a classification task for an encoder with well representation ability. Howev

Externí odkaz: http://arxiv.org/abs/2111.13301

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