Relevant bibliographies by topics / Grain China Forecasting

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  1. Journal articles
  2. Dissertations / Theses
  3. Conference papers

Academic literature on the topic 'Grain China Forecasting'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Grain China Forecasting"

1

TOYODA, Takashi, Jin CHEN, and Hidefumi IMURA. "An empirical analysis and forecasting of grain production in China." ENVIRONMENTAL SYSTEMS RESEARCH 25 (1997): 111–19. http://dx.doi.org/10.2208/proer1988.25.111.

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LIU, L., Y. WANG, J. WU, J. WANG, and C. XI. "New optimized grey derivative models for grain production forecasting in China." Journal of Agricultural Science 153, no. 2 (March 5, 2014): 257–69. http://dx.doi.org/10.1017/s002185961400001x.

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SUMMARYAlthough the grey forecasting model has been successfully employed in various fields and demonstrates promising results, the literature shows that its performance could still be improved. Therefore, the aim of the present study was to continue the investigation and derive three hybrid models to predict grain production in China by combining particle swarm optimization (PSO) with the grey linear power index model, the grey logarithm power model and the grey parabola power model. In grey modelling, the use of PSO had the ability to search optimum grey parameters to construct three improved derivative grey models. The results concluded that the improved optimization models with high precision were superior to the traditional models, and PSO contributed more to precision improvement of the three grey models. Furthermore, results from the experiments demonstrated that the optimized models were reliable and valid.
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Zeng, Bo, Hui Li, and Xin Ma. "A novel multi-variable grey forecasting model and its application in forecasting the grain production in China." Computers & Industrial Engineering 150 (December 2020): 106915. http://dx.doi.org/10.1016/j.cie.2020.106915.

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Wilson, William W., Won W. Koo, Richard Taylor, and Bruce Dahl. "Long-Term Forecasting of World Grain Trade and U.S. Gulf Exports." Transportation Research Record: Journal of the Transportation Research Board 1909, no. 1 (January 2005): 22–30. http://dx.doi.org/10.1177/0361198105190900104.

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Important changes occurring in the world grain trade will affect the spatial distribution of grain flows and affect large-scale transportation projects. Most important among these are developments in ethanol and in Brazil and China. This paper develops a spatial optimization model based on a long-term competitive equilibrium to make projections in the world grain trade and shipments from individual ports to 2025. Results indicate that world trade should increase by about 47%, with the fastest growth occurring in imports to China and Pakistan and the slowest growth in Japan and the European Union, traditionally large markets. Most increases in terms of volume are expected in soybeans (49%), followed by corn (26%). Most of the U.S. export growth is expected through the barge system to U.S. ports on the Gulf of Mexico, with negligible growth through the Pacific Northwest and lakes. Although a multitude of reasons explain this expected trend, one is the growth in ethanol concentrated in the western states, which will require shifting production to meet demand. As a result, the exportable surplus from these regions will decline, and much of the growth in exports will be through the U.S. Gulf and from Argentina and Brazil, particularly northern Brazil, through spatial competition. Reflecting the impacts of growth in demand as well as international and intermodal competition, these results provide insight for transport project planners about the long-term growth in exports from particular origins and routes.
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Zhao, Yue Ling, Hai Yan Han, Li Ying Cao, Li Ma, and Gui Fen Chen. "Study of Application of Time Series Model in Grain Yield Predition." Advanced Materials Research 1049-1050 (October 2014): 1392–95. http://dx.doi.org/10.4028/www.scientific.net/amr.1049-1050.1392.

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the food forecast is very important for grain production, adjusting the important theoretical basis for grain planting structure, making the food security and agricultural sustainable development strategy. In order to solve the insufficiency of the traditional model selection criteria in practical application, the relationship between the quantity of consumption and time, time series forecasting models of food grain consumption per capita in China. The results showed that, two timing the predictive fitting statistical index model is highly significant, by applying the model to the data of inside forecast more accurate prediction results, but because of many influence factors, its accuracy to be tested time and actual.
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Luo, Zhong Hui, Qi Jun Xiao, and Jun Lan Wu. "Research on the Multi-Parameter Modeling of Submarine Sediment Prediction." Applied Mechanics and Materials 462-463 (November 2013): 13–16. http://dx.doi.org/10.4028/www.scientific.net/amm.462-463.13.

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It is presented in this paper the technology of principal component analysis and analyze existing empirical equation and its calculation errors. A principle component model is then built up using the measurement data of sediments from the continental slope and shelf in southern South China Sea. It is also studied in theory how to exclude correlated parameters from a number of parameters that can affect the sound velocity and how to optimize a few parameters that are obviously related to sound velocity without cross-correlation. Using the optimal physical parameters, such as porosity n, median grain size Md (φ) and plastic limit Wp, a three-parameter forecasting equation of sound velocity is established for the continental shelf and slope in southern South China Sea.
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Zhuo, Wen, Jianxi Huang, Xinran Gao, Hongyuan Ma, Hai Huang, Wei Su, Jihua Meng, Ying Li, Huailiang Chen, and Dongqin Yin. "Prediction of Winter Wheat Maturity Dates through Assimilating Remotely Sensed Leaf Area Index into Crop Growth Model." Remote Sensing 12, no. 18 (September 7, 2020): 2896. http://dx.doi.org/10.3390/rs12182896.

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Predicting crop maturity dates is important for improving crop harvest planning and grain quality. The prediction of crop maturity dates by assimilating remote sensing information into crop growth model has not been fully explored. In this study, a data assimilation framework incorporating the leaf area index (LAI) product from Moderate Resolution Imaging Spectroradiometer (MODIS) into a World Food Studies (WOFOST) model was proposed to predict the maturity dates of winter wheat in Henan province, China. Minimization of normalized cost function was used to obtain the input parameters of the WOFOST model. The WOFOST model was run with the re-initialized parameter to forecast the maturity dates of winter wheat grid by grid, and THORPEX Interactive Grand Global Ensemble (TIGGE) was used as forecasting period weather input in the future 15 days (d) for the WOFOST model. The results demonstrated a promising regional maturity date prediction with determination coefficient (R2) of 0.94 and the root mean square error (RMSE) of 1.86 d. The outcomes also showed that the optimal forecasting starting time for Henan was 30 April, corresponding to a stage from anthesis to grain filling. Our study indicated great potential of using data assimilation approaches in winter wheat maturity date prediction.
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Wu, Xianghua, Jieqin Zhou, Huaying Yu, Duanyang Liu, Kang Xie, Yiqi Chen, Jingbiao Hu, Haiyan Sun, and Fengjuan Xing. "The Development of a Hybrid Wavelet-ARIMA-LSTM Model for Precipitation Amounts and Drought Analysis." Atmosphere 12, no. 1 (January 6, 2021): 74. http://dx.doi.org/10.3390/atmos12010074.

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Investigation of quantitative predictions of precipitation amounts and forecasts of drought events are conducive to facilitating early drought warnings. However, there has been limited research into or modern statistical analyses of precipitation and drought over Northeast China, one of the most important grain production regions. Therefore, a case study at three meteorological sites which represent three different climate types was explored, and we used time series analysis of monthly precipitation and the grey theory methods for annual precipitation during 1967–2017. Wavelet transformation (WT), autoregressive integrated moving average (ARIMA) and long short-term memory (LSTM) methods were utilized to depict the time series, and a new hybrid model wavelet-ARIMA-LSTM (W-AL) of monthly precipitation time series was developed. In addition, GM (1, 1) and DGM (1, 1) of the China Z-Index (CZI) based on annual precipitation were introduced to forecast drought events, because grey system theory specializes in a small sample and results in poor information. The results revealed that (1) W-AL exhibited higher prediction accuracy in monthly precipitation forecasting than ARIMA and LSTM; (2) CZI values calculated through annual precipitation suggested that more slight drought events occurred in Changchun while moderate drought occurred more frequently in Linjiang and Qian Gorlos; (3) GM (1, 1) performed better than DGM (1, 1) in drought event forecasting.
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Ge, Jun, Andrew J. Pitman, Weidong Guo, Beilei Zan, and Congbin Fu. "Impact of revegetation of the Loess Plateau of China on the regional growing season water balance." Hydrology and Earth System Sciences 24, no. 2 (February 4, 2020): 515–33. http://dx.doi.org/10.5194/hess-24-515-2020.

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Abstract. To resolve a series of ecological and environmental problems over the Loess Plateau, the “Grain for Green Program” (GFGP) was initiated at the end of 1990s. Following the conversion of croplands and bare land on hillslopes to forests, the Loess Plateau has displayed a significant greening trend, which has resulted in soil erosion being reduced. However, the GFGP has also affected the hydrology of the Loess Plateau, which has raised questions regarding whether the GFGP should be continued in the future. We investigated the impact of revegetation on the hydrology of the Loess Plateau using relatively high-resolution simulations and multiple realizations with the Weather Research and Forecasting (WRF) model. Results suggest that revegetation since the launch of the GFGP has reduced runoff and soil moisture due to enhanced evapotranspiration. Further revegetation associated with the GFGP policy is likely to further increase evapotranspiration, and thereby reduce runoff and soil moisture. The increase in evapotranspiration is associated with biophysical changes, including deeper roots that deplete deep soil moisture stores. However, despite the increase in evapotranspiration, our results show no impact on rainfall. Our study cautions against further revegetation over the Loess Plateau given the reduction in water available for agriculture and human settlements and the lack of any significant compensation from rainfall.
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Li, Wei, Lu Li, Jie Chen, Qian Lin, and Hua Chen. "Impacts of land use and land cover change and reforestation on summer rainfall in the Yangtze River basin." Hydrology and Earth System Sciences 25, no. 8 (August 24, 2021): 4531–48. http://dx.doi.org/10.5194/hess-25-4531-2021.

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Abstract. Land use and cover have been significantly changed all around the world during the last decade. In particular, the Grain for Green (GG) program has resulted in significant changes in regional land use and cover, especially in China. Land use and cover change (LULCC) may lead to changes in regional climate. In this study, we take the Yangtze River basin as a case study and analyze the impacts of LULCC and reforestation on summer rainfall amounts and extremes based on the Weather Research and Forecasting model. Firstly, two observed land use and cover scenarios (1990 and 2010) were chosen to investigate the impacts of LULCC on summer rainfall during the last decade. Secondly, two hypothetical reforestation scenarios (i.e., scenarios of 20 % and 50 % cropland changed to forest) were taken based on the control year of 2010 to test the sensitivity of summer rainfall (amounts and extremes) to reforestation. The results showed that average summer rainfall and extreme summer daily rainfall decreased in the Yangtze River basin between 1990 and 2010 due to LULCC. Reforestation could increase summer rainfall amount and extremes, and the effects were more pronounced in populated areas than over the whole basin. Moreover, the effects of reforestation were influenced by the reforestation proportion. In addition, the summer rainfall increased less conversely, with the transform proportion of cropland to forest increased from 20 % to 50 %. By analyzing the changes in water vapor mixing ratio, upward moisture flux, and 10 m wind, it is suggested that this result might be caused by the horizontal transportation processes of moisture. Although a comprehensive assessment of the impacts of LULCC on summer rainfall amounts and extremes was conducted, further studies are needed to investigate the uncertainty better.
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Dissertations / Theses on the topic "Grain China Forecasting"

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Shea, Esther Yi Ping. "The political economy of China's grain policy reform." Title page, contents and abstract only, 2003. http://web4.library.adelaide.edu.au/theses/09PH/09phs5393.pdf.

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Includes bibliographical references (leaves 222-235) Develops a coherent theoretical framework to analyse the formulation of grain procurement policy for the entire history of the PRC. An optimization model is constructed to capture Chinese policy makers' preferences regarding the competing objectives of sectoral income distribition and food security, as well as the factors governing the trade-off between thes two objectives and the choice of policy instruments. Also analyses the impacts of China's accession to WTO on its grain sector. To explain the numerous failures of China's grain policy, studies the problems arising from policy formulation and implementation.
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Cheing, Mei, and 鄭玫. "Can China Feed Itself：A Study on China’s Grain Demand Forecasting." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/51755928425105050544.

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碩士
國立臺灣大學
國家發展研究所
95
As the coming of the 21st centuries, China is becoming a dominating country in the world; hence, there are many predictions about China''s future--"the collapsing of China", "the threatening of China" and "the rising of China". China-related issues have been closely studied worldwide. All kinds of reports provided by different Officials, institutes and private researches can be found. Some of them are predicting that the increase of Chinese population may destroy its ecological equilibrium and China will suffer from famine. as a result, the whole world will be affected. According to China''s history, the ample staple food supply has a significant political implication－it is a necessity to governing the country well. If the providing of staple food is well secured, a basis for a prosperous China is promised. This study focuses on observing the trend of China’s staple food demand, and further offer to a reasonable prediction. The models used are：GARCH model, Co-integration model, and forecasting process. The Co-integration model may have a non-linear effect； hence, this study uses both Linear and Non-linear approaches in the Co－integration models. The data used in the study are from the Food and Agriculture Organization (U.N.), 1961－2004. The variables are：Average consumer quantity of major grain, average price of grain, and average income. The empirical results are summarized as follow： Firstly, in the first two periods, the declining of consuming quantity on grain will cause the increase of grain price. The farmer could even hold down his sales. This is due to the commodity price a rise but the grain price doesn''t go up as well. Since the price of grain keeps unchanged, the costs on equipment and labor are increasing. Secondly, in this study, China''s staple food demand is offered to have both long-term and short-term stability, and it fits the "best linear unbiased estimator (BLUE)", goodness of fit , hence it is predictable and has long-term developing co-relation--the rise of food consumption causes the rise of food price and the increase of food consumption stimulate the increase of income. Third, many studies on this topic have been made from the supply-side. Most of the investigated periods are within 5-20. However, the Chinese data before China''s "reform" are usually fragmentary, inconsistent and incompleteness. This study overcomes many limitations and obstacles, probe into this topic from the demand-side, in an effort to make it a rare one. Fourth, China''s data of the earlier years'' can be obtained from database of FAOSTAT. Obviously, it has better credibility and is more comprehensive. It''s a pity that it only represents the country''s total supply, but the differences between rural vs. urban, poor vs. well-off are not included. What we can conclude from the data is：Over the years, the Chinese'' dietary habit has changed significantly. Fifth, according to this investigation, all the indexes are aiming to the same direction：China is having a good opportunity, and is not "developing to perishing". However, this topic deserves follow up and further investigation. Finally, this study investigates the sensitiveness of China''s staple food demand and observes the price of World staple food as well, then, examines Taiwan agriculture''s developing opportunities and provides some recommendations.
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Conference papers on the topic "Grain China Forecasting"

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Hu, Hai-Qing, Dan Zhang, and Qiu-Ping Wang. "Application of trigonometric grey prediction approach to forecasting China grain yield." In 2009 IEEE International Conference on Grey Systems and Intelligent Services (GSIS 2009). IEEE, 2009. http://dx.doi.org/10.1109/gsis.2009.5408255.

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Gao, Mingjie, Qiyou Luo, Yang Liu, and Jian Mi. "Grain consumption forecasting in China for 2030 and 2050: Volume and varieties." In 2014 Third International Conference on Agro-Geoinformatics. IEEE, 2014. http://dx.doi.org/10.1109/agro-geoinformatics.2014.6910669.

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Duan, Shanshan, Weidong Yang, Xuyu Wang, Shiwen Mao, and Yuan Zhang. "Grain Pile Temperature Forecasting from Weather Factors: A Support Vector Regression Approach." In 2019 IEEE/CIC International Conference on Communications in China (ICCC). IEEE, 2019. http://dx.doi.org/10.1109/iccchina.2019.8855910.

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Wen, Jian, and Lijuan Lei. "A Combined Forecasting Method of Grain Yield in China Based on GM(1,1) and BP Network." In 2010 Third International Conference on Information and Computing Science (ICIC). IEEE, 2010. http://dx.doi.org/10.1109/icic.2010.289.

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