農(nóng)產(chǎn)品市場價格web信息分析方法研究
發(fā)布時間：2018-11-13 10:44
【摘要】：近年來,我國農(nóng)產(chǎn)品市場價格呈現(xiàn)的異常波動已成為社會關(guān)注的焦點。農(nóng)產(chǎn)品價格波動不僅會對農(nóng)民收入和農(nóng)民生產(chǎn)積極性產(chǎn)生直接影響,更關(guān)乎百姓的日常生活和切身利益。為保持經(jīng)濟平穩(wěn)健康發(fā)展、保障群眾生活,穩(wěn)定物價的宏觀調(diào)控尤為重要。價格監(jiān)測和預(yù)測是維持價格穩(wěn)定的一個重要環(huán)節(jié),精確地價格監(jiān)測和低誤預(yù)測是涉農(nóng)科研工作者的一個重要研究方向。我國農(nóng)產(chǎn)品市場價格Web信息分布廣、更新快,迫切需要建立一套垂直搜索引擎系統(tǒng)實現(xiàn)定期抓取網(wǎng)絡(luò)中農(nóng)產(chǎn)品價格數(shù)據(jù),迫切需要建立一個農(nóng)產(chǎn)品價格分析、預(yù)測和監(jiān)測平臺,提供全面、清晰的分析結(jié)果。為政府部門管理人員提供生產(chǎn)調(diào)控、決策分析的依據(jù),成為農(nóng)民種植植物的決策依據(jù),為農(nóng)產(chǎn)品市場價格穩(wěn)定做出積極的貢獻。 某些農(nóng)網(wǎng)等價格信息網(wǎng)提供的農(nóng)產(chǎn)品價格信息有數(shù)據(jù)單位不統(tǒng)一、產(chǎn)品名稱不規(guī)范等問題,經(jīng)過對分布在不同網(wǎng)站上的農(nóng)產(chǎn)品市場價格數(shù)據(jù)的分析和總結(jié),提出了規(guī)范產(chǎn)品名稱、規(guī)范市場名稱、初始化農(nóng)產(chǎn)品類別、初始化省市、規(guī)范數(shù)據(jù)單位、去重策略選擇和零價格數(shù)據(jù)處理7個數(shù)據(jù)規(guī)范化原則。研究了DOM樹方式、正則表達式、HTMLParser提取網(wǎng)頁文本信息,利用Heritrix等軟件搭建了農(nóng)產(chǎn)品市場價格垂直搜索引擎系統(tǒng)實現(xiàn)了抽取不同農(nóng)網(wǎng)上的價格信息,經(jīng)規(guī)范化后形成了統(tǒng)一、完整的SQL server農(nóng)產(chǎn)品價格數(shù)據(jù)庫。 為進一步提高農(nóng)產(chǎn)品市場價格預(yù)測精度,及時發(fā)現(xiàn)價格異常的農(nóng)產(chǎn)品,選取了山西晉城綠欣農(nóng)產(chǎn)品批發(fā)市場胡蘿卜、白蘿卜、大白菜、大蔥、豆角、黃瓜、尖椒、韭菜、茄子、青椒、土豆、西紅柿和油菜十三種農(nóng)產(chǎn)品進行預(yù)測算法對比研究。在加權(quán)算術(shù)平均預(yù)測法中對比分析了5種權(quán)數(shù)設(shè)置方法,實驗結(jié)果表明以當(dāng)年價格為權(quán)數(shù)誤差最低,優(yōu)于其它權(quán)數(shù)設(shè)置方法,在平均數(shù)預(yù)測法中優(yōu)于簡單算術(shù)平均法；對比分析了時間序列非季節(jié)11種預(yù)測方法,研究結(jié)果表明二次曲線趨勢延續(xù)法和龔伯茲曲線趨勢延續(xù)法不適用于農(nóng)產(chǎn)品價格預(yù)測,在簡單算術(shù)平均法、加權(quán)算術(shù)平均法、時間序列平均增長量預(yù)測法、時間序列幾何平均法、一次移動平均預(yù)測法、二次移動平均預(yù)測法、一次指數(shù)平滑法、二次指數(shù)平滑法和直線趨勢延續(xù)法9種預(yù)測方法中二次移動平均預(yù)測法和二次指數(shù)平滑法誤差低于其它預(yù)測方法,適用于農(nóng)產(chǎn)品價格預(yù)測,在此基礎(chǔ)上提出了一種改進的二次指數(shù)平滑預(yù)測法,二次指數(shù)平滑預(yù)測法中一次、二次平滑系數(shù)不同時,所有的誤差平方和都小于或等于一次和二次平滑系數(shù)相同時的誤差平方和。改進后的二次指數(shù)平滑預(yù)測法誤差最低,優(yōu)于末改進的二次指數(shù)平滑法,也優(yōu)于二次移動平均預(yù)測法；對比了時間序列季節(jié)指數(shù)水平法和季節(jié)指數(shù)趨勢法,從實驗結(jié)果中可以看出,大多數(shù)農(nóng)產(chǎn)品兩種預(yù)測方法誤差平方和相差很多,實際預(yù)測價格可以采用誤差平方低的預(yù)測值；在價格異常農(nóng)產(chǎn)品判定方面提出了從預(yù)測值與實際價格誤差平方和歷史誤差2種排名方式,確定當(dāng)月價格異常農(nóng)產(chǎn)品和確定去年價格異常,今年價格仍然異常的農(nóng)產(chǎn)品的判定方法。 目前與農(nóng)產(chǎn)品價格有關(guān)的信息網(wǎng)站大多只提供了原始價格信息顯示,針對規(guī)劃好的從不同網(wǎng)站抓取出的價格數(shù)據(jù)利用企業(yè)級工作平臺MyEclipse開發(fā)出了農(nóng)產(chǎn)品市場價格Web信息分析系統(tǒng),實現(xiàn)了價格查詢、價格分析、價格預(yù)測和價格監(jiān)測等功能,價格分析功能包括價格走勢、各省對比、品種對比、同比環(huán)比和市場對比,價格預(yù)測功能包括單值預(yù)測和趨勢預(yù)測,各省對比包括某一天對比和某一段時間對比等,分析結(jié)果以折線圖、柱形圖或地圖的形式顯示,界面美觀,功能實用�？蓾M足農(nóng)業(yè)管理部門、農(nóng)業(yè)企業(yè)、農(nóng)戶準(zhǔn)確掌握不同地區(qū)、不同農(nóng)產(chǎn)品價格的變化動態(tài)與走勢的需要。
[Abstract]:In recent years, the abnormal fluctuation of the market price of agricultural products in China has become the focus of social concern. The price fluctuation of agricultural products will not only have a direct impact on the farmers' income and the enthusiasm of the farmers, but also to the daily life and the vital interests of the people. In order to maintain the stable and healthy development of the economy, to guarantee the living of the masses, the macro-control of stable prices is particularly important. Price monitoring and forecasting are an important link in the maintenance of price stability. The market price of the agricultural products in China is wide, the update is fast, it is urgent to establish a set of vertical search engine system to realize the data of the price of the agricultural products in the network on a regular basis, and an analysis, prediction and monitoring platform for the price of agricultural products is urgently needed to provide a comprehensive and clear analysis result. To provide the basis of production and control and decision-making analysis for the management of government departments, to become the decision-making basis for farmers to plant the plant, and to make a positive contribution to the market price stability of the agricultural products. The price information of the agricultural products provided by the price information network such as the agricultural net is not uniform, the product name is not standardized, and the like, and the analysis and the summary of the price data of the agricultural products distributed on different websites are analyzed and summarized, and the product name, the product market and the like are put forward. Name, initialize the agricultural product category, initialize the provinces and cities, standardize the data units, go to the re-duplication policy selection and the zero-price data processing for 7 data standardization The principle is to study the DOM tree method, regular expression, HTMLParser to extract the text information of the web page, and set up the price vertical search engine system of the agricultural product market by using the software of Heritrix and so on. The price information of different non-agricultural products can be extracted by using the software of Heritrix and the like, and the price of the agricultural products of the whole SQL server is formed after the standardization. according to the invention, in order to further improve the forecasting precision of the market price of the agricultural products, the agricultural products with abnormal prices are found in time, and the carrot, the white radish, the Chinese cabbage, the scallion, the bean horn, the cucumber, the pepper, the leek and the eggplant are selected, Prediction of thirteen agricultural products of green pepper, potato, tomato and rape In the weighted arithmetic average prediction method, the method of five weights is compared and analyzed, and the experimental results show that the method is superior to the other weight setting method in the current year price, which is better than the simple method in the average prediction method. The results show that the trend continuation method of the quadratic curve and the trend continuation method of the time series are not applicable to the prediction of the price of the agricultural products. In the simple arithmetic mean method, the weighted arithmetic mean method and the time series average increase the long-volume prediction method, the time series geometric mean method, the one-time moving average prediction method, the secondary moving average prediction method, the primary index smoothing method, the quadratic exponential smoothing method and the straight-line trend continuation method The method is applicable to the prediction of the price of agricultural products, and on the basis of that, an improved quadratic exponential smoothing prediction method, a secondary exponential smoothing prediction method and a secondary exponential smoothing prediction method are provided, The error sum of the errors is the lowest, the improved quadratic exponential smoothing method is better than the last modified quadratic exponential smoothing method, which is superior to the quadratic moving average prediction method, and the time series seasonal index method and the seasonal index trend method are compared, and the experimental results are obtained. It can be seen from among the two prediction methods of the most agricultural products that the sum of the errors of the errors is much different, the actual predicted price can be the predicted value with low error square, and the historical error 2 from the predicted value and the actual price error is proposed in the aspect of the determination of the abnormal price of the price. In a way of ranking, it is determined that the price of the current month is abnormal and the prices are abnormal last year, and the prices at this year are still abnormal. At present, most of the information websites related to the price of the agricultural products only provide the original price information display, and the price data analysis system of the agricultural product market price is developed by using the enterprise-class work platform MyEclipse for the planned price data from different websites. The function of price query, price analysis, price forecast and price monitoring is realized. The price analysis function includes the price trend, the comparison of each province, the comparison of the varieties, the year-on-year link and the market comparison, the price prediction function includes single-value prediction and trend prediction, and the comparison between the provinces includes one day's comparison and the trend prediction. For a period of time, the results of the analysis are displayed in the form of a line chart, a bar graph, or a map, and the boundary The surface is beautiful, the function is practical, the agricultural management department, the agricultural enterprise and the farmer can accurately grasp the change of the price of different agricultural products
【學(xué)位授予單位】：沈陽農(nóng)業(yè)大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2013
【分類號】：TP391.3
本文編號：2328862
[Abstract]:In recent years, the abnormal fluctuation of the market price of agricultural products in China has become the focus of social concern. The price fluctuation of agricultural products will not only have a direct impact on the farmers' income and the enthusiasm of the farmers, but also to the daily life and the vital interests of the people. In order to maintain the stable and healthy development of the economy, to guarantee the living of the masses, the macro-control of stable prices is particularly important. Price monitoring and forecasting are an important link in the maintenance of price stability. The market price of the agricultural products in China is wide, the update is fast, it is urgent to establish a set of vertical search engine system to realize the data of the price of the agricultural products in the network on a regular basis, and an analysis, prediction and monitoring platform for the price of agricultural products is urgently needed to provide a comprehensive and clear analysis result. To provide the basis of production and control and decision-making analysis for the management of government departments, to become the decision-making basis for farmers to plant the plant, and to make a positive contribution to the market price stability of the agricultural products. The price information of the agricultural products provided by the price information network such as the agricultural net is not uniform, the product name is not standardized, and the like, and the analysis and the summary of the price data of the agricultural products distributed on different websites are analyzed and summarized, and the product name, the product market and the like are put forward. Name, initialize the agricultural product category, initialize the provinces and cities, standardize the data units, go to the re-duplication policy selection and the zero-price data processing for 7 data standardization The principle is to study the DOM tree method, regular expression, HTMLParser to extract the text information of the web page, and set up the price vertical search engine system of the agricultural product market by using the software of Heritrix and so on. The price information of different non-agricultural products can be extracted by using the software of Heritrix and the like, and the price of the agricultural products of the whole SQL server is formed after the standardization. according to the invention, in order to further improve the forecasting precision of the market price of the agricultural products, the agricultural products with abnormal prices are found in time, and the carrot, the white radish, the Chinese cabbage, the scallion, the bean horn, the cucumber, the pepper, the leek and the eggplant are selected, Prediction of thirteen agricultural products of green pepper, potato, tomato and rape In the weighted arithmetic average prediction method, the method of five weights is compared and analyzed, and the experimental results show that the method is superior to the other weight setting method in the current year price, which is better than the simple method in the average prediction method. The results show that the trend continuation method of the quadratic curve and the trend continuation method of the time series are not applicable to the prediction of the price of the agricultural products. In the simple arithmetic mean method, the weighted arithmetic mean method and the time series average increase the long-volume prediction method, the time series geometric mean method, the one-time moving average prediction method, the secondary moving average prediction method, the primary index smoothing method, the quadratic exponential smoothing method and the straight-line trend continuation method The method is applicable to the prediction of the price of agricultural products, and on the basis of that, an improved quadratic exponential smoothing prediction method, a secondary exponential smoothing prediction method and a secondary exponential smoothing prediction method are provided, The error sum of the errors is the lowest, the improved quadratic exponential smoothing method is better than the last modified quadratic exponential smoothing method, which is superior to the quadratic moving average prediction method, and the time series seasonal index method and the seasonal index trend method are compared, and the experimental results are obtained. It can be seen from among the two prediction methods of the most agricultural products that the sum of the errors of the errors is much different, the actual predicted price can be the predicted value with low error square, and the historical error 2 from the predicted value and the actual price error is proposed in the aspect of the determination of the abnormal price of the price. In a way of ranking, it is determined that the price of the current month is abnormal and the prices are abnormal last year, and the prices at this year are still abnormal. At present, most of the information websites related to the price of the agricultural products only provide the original price information display, and the price data analysis system of the agricultural product market price is developed by using the enterprise-class work platform MyEclipse for the planned price data from different websites. The function of price query, price analysis, price forecast and price monitoring is realized. The price analysis function includes the price trend, the comparison of each province, the comparison of the varieties, the year-on-year link and the market comparison, the price prediction function includes single-value prediction and trend prediction, and the comparison between the provinces includes one day's comparison and the trend prediction. For a period of time, the results of the analysis are displayed in the form of a line chart, a bar graph, or a map, and the boundary The surface is beautiful, the function is practical, the agricultural management department, the agricultural enterprise and the farmer can accurately grasp the change of the price of different agricultural products
【學(xué)位授予單位】：沈陽農(nóng)業(yè)大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2013
【分類號】：TP391.3
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