|
|
|
|
|
Saeed Samadianfard, Salar Jarhan, Ely Salwana, Amir Mosavi, Shahaboddin Shamshirband and Shatirah Akib
Advancement in river flow prediction systems can greatly empower the operational river management to make better decisions, practices, and policies. Machine learning methods recently have shown promising results in building accurate models for river flow...
ver más
|
|
|
|
|
|
|
|
|
|
|
Jiajia Pan and Hung Tao Shen
A two-dimensional wave model coupled with ice dynamics is developed to evaluate ice effects on shallow water wave propagation on a beach and in a channel. The nonlinear Boussinesq equations with ice effects are derived and solved by the hybrid technique ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Igor Paz, Bernard Willinger, Auguste Gires, Bianca Alves de Souza, Laurent Monier, Hervé Cardinal, Bruno Tisserand, Ioulia Tchiguirinskaia and Daniel Schertzer
Recent studies have highlighted the need for high resolution rainfall measurements for better modelling of urban and peri-urban catchment responses. In this work, we used a fully-distributed model called ?Multi-Hydro? to study small-scale rainfall variab...
ver más
|
|
|
|
|
|
|
|
|
|
|
Zhiyang Li, Zhigang Nie and Guang Li
One of the crucial research areas in agricultural decision-making processes is crop yield prediction. This study leverages the advantages of hybrid models to address the complex interplay of genetic, environmental, and management factors to achieve more ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Jianlei Qiao, Yonglu Lv, Yucai Feng, Chang Liu, Yi Zhang, Jinying Li, Shuang Liu and Xiaohui Weng
At present, the electronic nose has became a new technology for the rapid detection of pesticides. However, the technique may misidentify them for samples that have not been involved in training. Therefore, a hybrid model based on unsupervised and superv...
ver más
|
|
|
|
|
|
|
|
|
|
|
Jennifer Coston-Guarini, François Charles and Jean-Marc Guarini
An outbreak species exhibits extreme, rapid population fluctuations that can be qualified as discrete events within a continuous dynamic. When outbreaks occur they may appear novel and disconcerting because the limiting factors of their dynamics are not ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Anik Baul, Gobinda Chandra Sarker, Prokash Sikder, Utpal Mozumder and Ahmed Abdelgawad
Short-term load forecasting (STLF) plays a crucial role in the planning, management, and stability of a country?s power system operation. In this study, we have developed a novel approach that can simultaneously predict the load demand of different regio...
ver más
|
|
|
|
|
|
|
|
|
|
|
Amr A. Abd El-Mageed, Ayoub Al-Hamadi, Samy Bakheet and Asmaa H. Abd El-Rahiem
It is difficult to determine unknown solar cell and photovoltaic (PV) module parameters owing to the nonlinearity of the characteristic current?voltage (I-V) curve. Despite this, precise parameter estimation is necessary due to the substantial effect par...
ver más
|
|
|
|
|
|
|
|
|
|
|
Lei Li, Xiaobao Zeng, Xinpeng Pan, Ling Peng, Yuyang Tan and Jianxin Liu
Microseismic monitoring plays an essential role for reservoir characterization and earthquake disaster monitoring and early warning. The accuracy of the subsurface velocity model directly affects the precision of event localization and subsequent process...
ver más
|
|
|
|
|
|
|
|
|
|
|
Anthony A. Amori, Olufemi P. Abimbola, Trenton E. Franz, Daran Rudnick, Javed Iqbal and Haishun Yang
Model calibration is essential for acceptable model performance and applications. The Hybrid-Maize model, developed at the University of Nebraska-Lincoln, is a process-based crop simulation model that simulates maize growth as a function of crop and fiel...
ver más
|
|
|
|
|
|