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Haibo Chu, Zhuoqi Wang and Chong Nie
Accurate and reliable monthly streamflow prediction plays a crucial role in the scientific allocation and efficient utilization of water resources. In this paper, we proposed a prediction framework that integrates the input variable selection method and ...
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Yin Tang, Lizhuo Zhang, Dan Huang, Sha Yang and Yingchun Kuang
In view of the current problems of complex models and insufficient data processing in ultra-short-term prediction of photovoltaic power generation, this paper proposes a photovoltaic power ultra-short-term prediction model named HPO-KNN-SRU, based on a S...
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Jiyuan Tan, Limin Zhang and Zhaogen Zhong
Aiming to solve the problem of the distinction of scrambled linear block codes, a method for identifying the scrambling types of linear block codes by combining correlation features and convolution long short-term memory neural networks is proposed in th...
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Bishwajit Roy, Maheshwari Prasad Singh, Mosbeh R. Kaloop, Deepak Kumar, Jong-Wan Hu, Radhikesh Kumar and Won-Sup Hwang
Rainfall-runoff (R-R) modelling is used to study the runoff generation of a catchment. The quantity or rate of change measure of the hydrological variable, called runoff, is important for environmental scientists to accomplish water-related planning and ...
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Rodgers Makwinja, Seyoum Mengistou, Emmanuel Kaunda, Tena Alemiew, Titus Bandulo Phiri, Ishmael Bobby Mphangwe Kosamu and Chikumbusko Chiziwa Kaonga
Forecasting, using time series data, has become the most relevant and effective tool for fisheries stock assessment. Autoregressive integrated moving average (ARIMA) modeling has been commonly used to predict the general trend for fish landings with incr...
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Due to the nonlinear and non-stationary characteristics of the carbon price, it is difficult to predict the carbon price accurately. This paper proposes a new novel hybrid model for carbon price prediction. The proposed model consists of an extreme-point...
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Korrakoch Taweesin, Uma Seeboonruang and Phayom Saraphirom
This research studies the relationship between the climate index and the groundwater level of the lower Chao Phraya basin, in order to forecast the groundwater level in the studied area by using Autoregressive Integrated Moving Average with Explanatory (...
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Tian Peng, Jianzhong Zhou, Chu Zhang and Wenlong Fu
Accurate and reliable streamflow forecasting plays an important role in various aspects of water resources management such as reservoir scheduling and water supply. This paper shows the development of a novel hybrid model for streamflow forecasting and d...
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Guoqiang Sun, Tong Chen, Zhinong Wei, Yonghui Sun, Haixiang Zang and Sheng Chen
Accurate forecasting of carbon price is important and fundamental for anticipating the changing trends of the energy market, and, thus, to provide a valid reference for establishing power industry policy. However, carbon price forecasting is complicated ...
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Bangzhu Zhu
Due to the movement and complexity of the carbon market, traditional monoscale forecasting approaches often fail to capture its nonstationary and nonlinear properties and accurately describe its moving tendencies. In this study, a multiscale ensemble for...
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