A system dynamics approach to urban water demand forecasting was developed based on the analysis of urban water resources system, which was characterized by multi-feedback and nonlinear interactions among sys-tem elem...A system dynamics approach to urban water demand forecasting was developed based on the analysis of urban water resources system, which was characterized by multi-feedback and nonlinear interactions among sys-tem elements. As an example, Tianjin water resources system dynamic model was set up to forecast water resources demand of the planning years. The practical verification showed that the relative error was lower than 10%. Fur-thermore, through the comparison and analysis of the simulation results under different development modes pre-sented in this paper, the forecasting results of the water resources demand of Tianjin was achieved based on sustain-able utilization strategy of water resources.展开更多
Short-term water demand forecasting provides guidance on real-time water allocation in the water supply network, which help water utilities reduce energy cost and avoid potential accidents. Although a variety of metho...Short-term water demand forecasting provides guidance on real-time water allocation in the water supply network, which help water utilities reduce energy cost and avoid potential accidents. Although a variety of methods have been proposed to improve forecast accuracy, it is still difficult for statistical models to learn the periodic patterns due to the chaotic nature of the water demand data with high temporal resolution. To overcome this issue from the perspective of improving data predictability, we proposed a hybrid Wavelet-CNN-LSTM model, that combines time-frequency decomposition characteristics of Wavelet Multi-Resolution Analysis (MRA) and implement it into an advanced deep learning model, CNN-LSTM. Four models - ANN, Conv1D, LSTM, GRUN - are used to compare with Wavelet-CNN-LSTM, and the results show that Wavelet-CNN-LSTM outperforms the other models both in single-step and multi-steps prediction. Besides, further mechanistic analysis revealed that MRA produce significant effect on improving model accuracy.展开更多
It is essential to establish the water resources exploitation and utiliz~~tion planning, which is mainly based on recognizing and forecasting the water consumed structure rationally and scientifically. During the past...It is essential to establish the water resources exploitation and utiliz~~tion planning, which is mainly based on recognizing and forecasting the water consumed structure rationally and scientifically. During the past 30 years （1980-2009）, mean annual precipil：ation and total water resource of Beijing have decreased by 6.89% and 31.37% compared with those per- ennial values, respectively, while total water consumption during the same [：period reached pinnacle historically. Accordingly, it is of great significance for the harmony between socio-economic development and environmental development. Based on analyzing total water consumption, agricultural, industrial, domestic and environmental water consumption, and evolution of water consumed structure, further driving forces of evolution of total water consumption and water consumed structure are revealed systematically. Prediction and dis- cussion are achieved for evolution of total water consumption, water consumed structure, and supply-demand situation of water resource in the near future of Beijing using Time Series Forecasting Method. The purpose of the endeavor of this paper is to provide scientific basis for the harmonious development between socio-economy and water resources, for the es- tablishment of rational strategic planning of water resources, and for the social sustainable development of Beijing with scientific bases.展开更多
The forecasting of the demand applied to water supply systems has been an important tool to realize time control. The use of the time series to do the forecasting of the demand is the main way that has been used by re...The forecasting of the demand applied to water supply systems has been an important tool to realize time control. The use of the time series to do the forecasting of the demand is the main way that has been used by researchers. By this way, the need of a complete time demand series increases. This work presents two ways to reconstruct the water demand time series synthetically, using the Average Reconstruction Method and Fourier Method. Both the methods were considered interesting to do the synthetic reconstruction and able to complete the time series, but the Fourier Method showed better results and a better fitness to approximation of the water consumption pattern.展开更多
基金Supported by National Natural Science Foundation of China (No.50578108)Doctoral Programs Foundation of Ministry of Education of China (No.20050056016)+3 种基金National Key Program for Basic Research ( "973" Program, No.2007CB407306-1)Science and Technology Development Foundation of Tianjin (No.033113811 and No.05YFSYSF032)Educational Commission of Hebei Province (No.2008324)Tianjin Social Key Foundation (No.tjyy08-01-078).
文摘A system dynamics approach to urban water demand forecasting was developed based on the analysis of urban water resources system, which was characterized by multi-feedback and nonlinear interactions among sys-tem elements. As an example, Tianjin water resources system dynamic model was set up to forecast water resources demand of the planning years. The practical verification showed that the relative error was lower than 10%. Fur-thermore, through the comparison and analysis of the simulation results under different development modes pre-sented in this paper, the forecasting results of the water resources demand of Tianjin was achieved based on sustain-able utilization strategy of water resources.
基金financially supported by the National Natural Science Foundation of China(No.51978494)the Science and Technology Innovation Program Project of Shanghai City Investment Co.,Ltd.(No.CTKY-ZDXM-2020-012).
文摘Short-term water demand forecasting provides guidance on real-time water allocation in the water supply network, which help water utilities reduce energy cost and avoid potential accidents. Although a variety of methods have been proposed to improve forecast accuracy, it is still difficult for statistical models to learn the periodic patterns due to the chaotic nature of the water demand data with high temporal resolution. To overcome this issue from the perspective of improving data predictability, we proposed a hybrid Wavelet-CNN-LSTM model, that combines time-frequency decomposition characteristics of Wavelet Multi-Resolution Analysis (MRA) and implement it into an advanced deep learning model, CNN-LSTM. Four models - ANN, Conv1D, LSTM, GRUN - are used to compare with Wavelet-CNN-LSTM, and the results show that Wavelet-CNN-LSTM outperforms the other models both in single-step and multi-steps prediction. Besides, further mechanistic analysis revealed that MRA produce significant effect on improving model accuracy.
基金Key Project of Science and Technology granted by Beijing Municipal Science & Technology Commission, No.D07050601510000
文摘It is essential to establish the water resources exploitation and utiliz~~tion planning, which is mainly based on recognizing and forecasting the water consumed structure rationally and scientifically. During the past 30 years （1980-2009）, mean annual precipil：ation and total water resource of Beijing have decreased by 6.89% and 31.37% compared with those per- ennial values, respectively, while total water consumption during the same [：period reached pinnacle historically. Accordingly, it is of great significance for the harmony between socio-economic development and environmental development. Based on analyzing total water consumption, agricultural, industrial, domestic and environmental water consumption, and evolution of water consumed structure, further driving forces of evolution of total water consumption and water consumed structure are revealed systematically. Prediction and dis- cussion are achieved for evolution of total water consumption, water consumed structure, and supply-demand situation of water resource in the near future of Beijing using Time Series Forecasting Method. The purpose of the endeavor of this paper is to provide scientific basis for the harmonious development between socio-economy and water resources, for the es- tablishment of rational strategic planning of water resources, and for the social sustainable development of Beijing with scientific bases.
文摘The forecasting of the demand applied to water supply systems has been an important tool to realize time control. The use of the time series to do the forecasting of the demand is the main way that has been used by researchers. By this way, the need of a complete time demand series increases. This work presents two ways to reconstruct the water demand time series synthetically, using the Average Reconstruction Method and Fourier Method. Both the methods were considered interesting to do the synthetic reconstruction and able to complete the time series, but the Fourier Method showed better results and a better fitness to approximation of the water consumption pattern.
