中国农业科学 ›› 2020, Vol. 53 ›› Issue (14): 2859-2871.doi: 10.3864/j.issn.0578-1752.2020.14.010
收稿日期:
2020-06-03
接受日期:
2020-07-14
出版日期:
2020-07-16
发布日期:
2020-08-10
联系方式:
许世卫,E-mail:xushiwei@caas.cn
基金资助:
XU ShiWei(),DI JiaYing,LI GanQiong,ZHUANG JiaYu
Received:
2020-06-03
Accepted:
2020-07-14
Published:
2020-07-16
Online:
2020-08-10
摘要:
【目的】农产品供给与需求的准确分析测定,是农业监测预警能力提升的重要表现。构建产品多品种多环节模型集群理论方法,可高效解决单一环节或单一模型难以解决的分析技术难题。【方法】在农产品供需的重要要素即生产量、消费量、贸易量、价格等分析预测过程中,针对农产品品种间关联性强,自然、社会、经济诸多影响因素纠缠,模型多变量强耦合、非线性、参数时变的特点,提出多品种农产品“因素分类解耦、参数转用适配”方法,以构建多时空维度的监测预警模型集群。【结果】利用“因素分类解耦、参数转用适配”技术方法,研究构建了不同农产品的生产类、消费类、贸易类、价格类的模型集群。这些模型集群可用于对不同时空维度的水稻、玉米、小麦、肉类等主要农产品供需的长中短期的分析预测,支撑形成了农业展望中的主要农产品平衡表,其中主要农产品全国年度生产量6年平均预测精度高于97%。【结论】研究提出的农产品监测预警模型集群构建理论及其方法,有效提升了农产品多品种模型集群的求解效率和准确率,增强了农产品供需分析预测的系统性与智能性,为系统揭示农产品复杂的时空供需变化特征、促进农产品市场调控科学性和可预见性,提供了新技术方法。
许世卫, 邸佳颖, 李干琼, 庄家煜. 农产品监测预警模型集群构建理论方法与应用[J]. 中国农业科学, 2020, 53(14): 2859-2871.
XU ShiWei, DI JiaYing, LI GanQiong, ZHUANG JiaYu. The Methodology and Application of Agricultural Monitoring and Early Warning Model Cluster[J]. Scientia Agricultura Sinica, 2020, 53(14): 2859-2871.
表1
农产品监测预警模型集群构建需考虑的主要影响因素"
模型变量 Model variable f(x) | 影响因素Influence factor(xi) | ||
---|---|---|---|
生产量 Production quantity (QP) | 作物单产 Yield | 气象单产 Meteorological yield | 温度、日照时数、降水量等 Temperature, sunshine duration, precipitation, etc. |
投入单产 Input yield | 成本收益情况、费用和用工情况、化肥种子投入、科技等 Cost-benefit situation, expenses and employment situation, fertilizer and seed input, technology, etc. | ||
管理单产 Management yield | 投入政策、支持政策、保护政策、科技政策等 Input policy, support policy, protection policy, science and technology policy, etc. | ||
收获面积 Harvested area | 价格竞争面积 Price competition area | 上一期投入产出效益、其他竞争农产品上一期投入产出效益、上一期种植面积等 Input-output benefits of the previous period, input-output benefits of the previous period of other competitive agricultural products, planting area of the previous period, etc. | |
调查面积 Survey area | 调查问卷等 Questionnaire, etc. | ||
遥感面积 Remote sensing area | NVDI植被指数、物候期等 NVDI vegetation index, phenology, etc. | ||
畜禽产量 Livestock production | 生育期因素、效益成本、管理因素、调查因素等 Fertility factors, benefit costs, management factors, survey factors, etc. | ||
消费量 Consumption quantity (QC) | 食用(口粮)消费 Food use consumption | 人口数、人均收入、均衡价格等 Population, per capita income, equilibrium price, etc. | |
工业消费 Industrial consumption | 生产价格、人均国民生产总值和工业增长率等 Production prices, GDP per capita, industrial growth rate, etc. | ||
饲用消费 Feed consumption | 畜产品产量、料肉比、饲料价格、投入品和产出品的价格 Production of livestock products, feed-to-meat ratio, feed prices, prices of inputs and outputs | ||
种用消费 Seed consumption | 播种面积、每亩种子用量 Seeded area, seed per mu | ||
损耗 Wastage | 产量、损耗系数 Production, wastage factor | ||
贸易量 Trade (T) | 进出口量 Import and export | 国内外价差、关税、进出口配额、产需缺口和汇率等 Domestic and foreign price differences, tariffs, import and export quotas, production and demand gaps, exchange rates, etc. | |
价格 Price (P) | 均衡价格指数 Equilibrium price index | 生产因素、消费因素、政策因素、偶发因素等 Production factors, consumption factors, policy factors, incidental factors, etc. |
表2
模型集群生产、消费、价格和贸易通用模型形式及变量说明"
模型形式 Model form | 主要变量 Main variable | 主要参数 Main parameter | |
---|---|---|---|
生产量 Production quantity (QP) | QPcrop = f (Ym, Yi, Yma, HA) | QPcrop:作物产量;Ym:气象单产;Yi:投入单产;Yma:管理单产;As:收获面积 QPcrop: Production quantity of crop; Ym: Meteorological yield; Yi: Input yield; Yma: Management yield; HA: Harvested area | |
Ym=δ(T, S, P) | T:温度;S:日照时间;P:降水量 T: Temperature; S: Sunshine duration; P: Precipitation. | δ:气象因子系数 δ: Meteorological factor coefficient | |
Yi=θ(CE, FE, FI) | CE:成本收益因子;FE:费用和用工因素;FI:肥料投入因素 CE: Cost-benefit factors; FE: Cost and employment factors; FI: Fertilizer input factors | θ:投入因子弹性系数 θ: Input factor elastic coefficient | |
Yma =μ(Pol, Man) | Pol:政策指数;Man:政策因素 Pol: Policy indexs; Man: Policy factors | μ:政策系数 μ: Policy coefficient | |
HA=ε(P, Psubs) | P:作物价格指数;Psubs:竞争作物价格指数 P: Crop price index; Psubs: Competitive crop price index | ε:竞品价格指数系数 ε: Competitive price index coefficient | |
QPanimal = f(YLD × SL × CR) | YLD:单只动物出栏活重;SL:动物出栏数量;CR:动物出栏率 YLD: Single animal slaughter live weight; SL: Number of animals slaughtered; CR: Animal slaughter rate | 畜禽产量系数 Livestock production coefficient | |
消费量Consumption quantity (QC) | QC = g(FC, IC, FEC, SEC, W) | FC:食用(口粮)消费;IC:工业消费;FEC:饲用消费;SEC:种用消费;W:损耗 FC: Food use consumption; IC: Industrial consumption; FEC: Feed use consumption; SEC: Seed use consumption; W: Wastage | 各消费细项系数 Coefficients of various consumption items |
贸易量 Trade (T) | IM = h(QP, QC) EX = f( QP, QC) | QP:产量;QC:消费量 QP: Production quantity; QC: Consumption quantity | 产量、消费量、价格影响系数 Coefficient of influence of production, consumption, prices |
价格 Price (P) | $\left\{ \overrightarrow{P}\left| \forall {{S}_{i}}(\overrightarrow{P}) \right.-{{D}_{i}}(\overrightarrow{P})=0 \right\}$ | $\overrightarrow{P}$:均衡价格向量;Si:供给端价格向量;Di:需求端价格向量 $\overrightarrow{P}$: Equilibrium price vector; Si: Supply price vector; Di: Demand price vector | 多产品均衡价格指数 Multi-product equilibrium price Index |
表3
利用多因素分类解耦技术构建的小麦监测预警模型集群方程形式"
预测变量 Predicted variable | 模型方程形式 Model equation form | 变量说明 Variable description |
---|---|---|
供需平衡 Supply- demand balance | SWT,t = DWT,t | SWT:小麦总供给量 The total supply of wheat in the current period DWT:小麦总需求量 The total demand of wheat in the current period |
总供给 Supply (S) | SWT,t = QPWT,t + IMWT,t + OSWT,t | QPWT:小麦生产量 Current production of wheat IMWT:小麦进口量 Current import of wheat OSWT:小麦期初库存 Opening stock of wheat |
生产量 Production quantity (QP) | QPWT,t = YLDWT,t × HAWT,t | YLDWT:小麦单产 Wheat yield HAWT:小麦收获面积 Wheat harvested area |
单产 Yield (YLD) | YLDWT, t = w1Ym, WT, t +w2Yi, WT, t + w3Yma, WT, t | Ym, WT、Yi, WT、Yma, WT:小麦气象单产、投入单产和管理单产 Current wheat meteorological yield, input yield and management yield w1、w2、w3:小麦Ym、Yi、Yma单产对应的赋值系数 Corresponding value coefficients of Ym、Yi、Yma of wheat |
气象单产 Meteorological yield (Ym) | Ym, WT, t = w1YTm, WT, t + w2YSm, WT, t+ w3YPm, WT, t | YTm, WT、w2YSm, WT、w3YPm, WT:小麦温度单因素气象单产、日照单因素气象单产以及降水量单因素气象单产 Current wheat temperature single factor meteorological yield, sunshine single factor meteorological yield and precipitation single factor meteorological yield w1、w2、w3:小麦3个气象单因素模型对应的赋值系数 Corresponding value coefficients of each meteorological yield model |
投入单产 Input yield (Yi) | ${{Y}_{i,WT,t}}=\log ({{\alpha }^{Yi}}+\beta _{1}^{{{Y}_{i}}}\ln {{P}_{t-1}}+\beta _{2}^{{{Y}_{i}}}\times $ $\ln CE_{t}^{\varepsilon }+\beta _{3}^{{{Y}_{i}}}\ln FE_{t}^{\varepsilon }+\beta _{4}^{{{Y}_{i}}}\ln FI_{t}^{\varepsilon })$ | Pt-1:小麦上一期价格 Wheat price in the previous year CEεt:成本收益情况因素向量 Cost-benefit factor vector FEεt:费用和用工情况因素向量 Cost and employment factor vector FIεt:肥料投入因素向量 Fertilizer input factor vector |
管理单产 Management yield (Yma) | Yma,WT,t=(1+γt)×YLD′WT,t | YLD′WT:小麦基础单产 Wheat basic yield γ:管理因子赋值系数 Management factor assignment coefficient |
面积 Harvested area (HA) | HAWT,t=(w1HAcompetition,t+w2HAsurvey,t+ w3HArs,t)-kADt | HAcompetition:小麦价格竞争面积 Price competition area of wheat HAsurvey:小麦调查面积 Survey area of wheat HArs:小麦遥感面积 Remote sensing area of wheat w1、w2、w3:小麦三种预测面积对应的权重系数 Corresponding value coefficients of each harvested area model AD:小麦的成灾面积 Disaster area of current wheat k:灾情指数,在0—1之间的一个数值,越大表示灾情越严 Disaster index, a value between 0—1, the greater the severity of the disaster |
价格竞争面积 Price competition area(HAcompetition) | lnHA competition, t= α+β1lnHAcompetition,t-1+ β2lnPt-1+β3lnPsubs,t-1 | HAcompetition,t-1:小麦上一期播种面积 Wheat harvested area in the previous year Pt-1:小麦上一期价格 Wheat price in the previous year Psubs,t-1:竞争相关性作物的上一期价格 Price of competitively related crops in the previous year |
调查面积 Survey area (HAsurvey) | $H{{A}_{survey,t}}=(\sum\limits_{i=1}^{n}{{{w}_{i}}\times H{{A}_{i,survey,t}}})\times k\times \frac{1}{r}$ | HAsurvey:调查得出的某地区小麦面积 Surveyed area of wheat in a certain area HAi,survey:某地区第i个村的小麦调查面积 Surveyed area of wheat in the i-th village in a certain area wi:第i个村的权重 Weight of the i-th village k:某地区调查县所有村数量与抽样框包含的所有村数量的比值 The ratio of the number of all villages in a survey county to the number of all villages included in the sampling frame in a certain area r:国家调查县小麦面积占全省所有县小麦面积的比率 The ratio of the area of counties under national survey to the area of all counties in the province |
预测变量 Predicted variable | 模型方程形式 Model equation form | 变量说明 Variable description |
进口量 Import (IM) | lnIMWT,t=αWT,IM+β1WT,IMlnQPWT,t+ β2WT,IMlnPWT,IM,t+β3WT,IMlnXRt | IMWT:小麦进口量 Wheat import QPWT:小麦生产总量 Total wheat production PWT,IM :以当地货币计价的小麦进口价格 Import prices of wheat in local currency XR:人民币对美元汇率 RMB against the U.S. dollar αWT,IM:小麦进口量误差项 Errors of wheat import |
期初库存 Opening stock (OS) | OSWT,t= ESWT,t-1 | ESWT,t-1:上一期小麦期末库存 The ending stock of wheat in the previous period |
总需求 Demand (D) | DWT, t = QCWT, t + EXWT, t + ESWT, t | QCWT:小麦消费量 Wheat consumption EXWT:小麦出口量 Wheat export ESWT:小麦期末库存 Ending stock of wheat |
消费量Consumption quantity(QC) | QCWT, t = FCWT, t + ICWT, t + FECWT, t + SECWT, t + WWT, t | FCWT:小麦口量消费量 Food use consumption of wheat ICWT:小麦工业消费量 Industrial consumption of wheat FECWT:小麦饲用消费量 Feed use consumption of wheat SECWT:小麦种用消费量 Seed use consumption of wheat WWT:小麦损耗 Wastage of wheat |
口粮消费量 Food use consumption (FC) | FCWT, t = PCWT, rural, t × POPWT ,rural, t + PCWT, urban, t × POPWT, urban, t | PCWT, rural :农村人均小麦口量消费量 Rural per capita FC of wheat POPWT, rural:农村总人口数 Total rural population PCWT, urban:城镇人均口量消费量 Urban per capita FC of wheat POPWT, urban:城镇总人口数 Total urban population |
农村人均口粮消费量 Rural per capita consumption (PCrural) | PCWT,rural,t=exp(α1lnDPIWT,rural,t+ α2lnPRT, t+α3lnPWT, t+α4lnPMA,t+ α5lnPSB, t+b) | DPIWT, rural:农村人均可支配收入 Rural per capita disposable income PRI:稻米均衡价格 Rice equilibrium price PWT:小麦均衡价格 Wheat equilibrium price PMA:玉米均衡价格 Corn equilibrium price PSB:大豆均衡价格 Soybean equilibrium price |
城市人均口粮消费量Urban per capita consumption (PCurban) | PCWT, urban,t=exp(α1lnDPIWT,urban,t+ α2lnPRT, t+α3lnPWT, t+α4lnPMA,t+ α5lnPSB, t+b) | DPIWT, urban:城镇人均可支配收入 Urban disposable income per capita |
饲用消费量 Feed use consumption (FEC) | FECWT, t = FERWT, 1×(QPPK, t + QPBV, t + QPMU, t) +FERWT, 2×QPPT, t + b | QPPK:猪肉产量 Pork production QPBV:牛肉产量 Beef production QPMU:羊肉产量 Mutton production QPPC:禽肉产量 Poultry production |
工业消费量 Industrial consumption (IC) | ICWT,t = exp (alnGDP + b) | GDP:国内生产总值 Gross Domestic Product |
种用消费量 Seed use consumption (SEC) | SECWT, t = SPMWT, t × HAWT, t | SPMWT:每亩小麦种子用量 Wheat seed dosage per acre |
损耗 Wastage (W) | WWT, t = KLWWT, t ×QPWT, t | KLWWT:小麦损耗率 Wheat loss rate |
出口量 Export (EX) | lnEXCHN,WT,t=α1WT,EX+β1WT,EX× lnEXCHN,WT,t-1 +β2WT,EX× ln FOBCHN,WT,t | EXCHN,WT,t:全国小麦出口量 National wheat export EXCHN,WT,t-1:上一期全国小麦出口量 National wheat exports in the previous period FOBCHN,WT,t:以当地货币计价的小麦离岸价格 FOB price of wheat in local currency |
表4
模型集群的主要变量参数及求解"
模型主要变量 Model variable f(x) | 模型方程变量系数的求解方法 Method for solving variable coefficients of model equation | ||
---|---|---|---|
产量 Production quantity (QP) | 作物单产 Yield | 气象单产 Meteorological yield | 历史数据建立回归方程求解各系数 Use historical data to establish regression equations to solve coefficients |
投入单产 Input yield | 历史数据建立回归方程求解各系数 Use historical data to establish regression equations to solve coefficients | ||
管理单产 Management yield | 历史数据、专家经验确定各系数 Historical data and expert experience determine the coefficients | ||
综合单产 Comprehensive yield | 专家人工设置和智能训练赋值各单产权重 Expert manual setting and intelligent training assign the weight of each yield | ||
收获面积 Harvested area | 价格竞争面积 Price competition area | 历史数据建立回归方程求解各系数 Use historical data to establish regression equations to solve coefficients | |
调查面积 Survey area | 调查数据 survey data | ||
遥感面积 Remote sensing area | 监测数据 Monitoring data | ||
综合面积 Comprehensive area | 专家人工设置和智能训练赋值各面积权重 Expert manual setting and intelligent training assign the weight of each area | ||
畜禽产量 Livestock production | 历史数据建立回归方程求解各系数 Use historical data to establish regression equations to solve coefficients | ||
消费量 Consumption quantity (QC) | 食用(口粮)消费 Food use consumption | 历史数据建立回归方程求解各系数 Use historical data to establish regression equations to solve coefficients | |
工业消费 Industrial consumption | 历史数据建立回归方程求解各系数 Use historical data to establish regression equations to solve coefficients | ||
饲用消费 Feed use consumption | 历史数据建立回归方程求解各系数 Use historical data to establish regression equations to solve coefficients | ||
种用消费 Seed use consumption | 历史数据建立回归方程求解各系数 Use historical data to establish regression equations to solve coefficients | ||
损耗 Loss | 历史数据建立回归方程求解各系数 Use historical data to establish regression equations to solve coefficients | ||
贸易量 Trade( T ) | 进出口量 Import and export | 历史数据及专家预测 Historical data and expert forecasts | |
价格 Price( P ) | 均衡价格指数 Equilibrium price index | 局部均衡模型求解 Local equilibrium model solution |
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