稻麦收获机型选型及其决策支持系统的研究
摘要
近年来，我国联合收获机的产销量迅速增加，目前我国联合收割机的保有量达到了30余万台，提高了稻麦的机收水平，改善了劳动条件，创造了显著的社会效益和经济效益，但是由于技术上的难点，标准化、通用化程度低以及经济问题等都制约着稻麦机收市场的发展，总体机收水平不高。再就是一直以来，对于稻麦收获机的选购，都是凭一些专家的主观评价和经验，缺乏可靠性。
目前，我国普遍存在的稻麦联合收获机械问题是收获作业成本较高、资金合理利用率差，在机务计划制定和机具优化配备方面，与发达国家相比有很大差距。针对这些问题，本文借鉴国内外的主要研究成果，结合江苏省农垦集团的实际情况，以农业智能系统为平台研究开发了稻麦收获机械选型的决策支持系统。该决策支持系统由五大部分组成，包括用户界面(人机会话系统)、智能决策模块、数据库及其管理系统、知识库及其管理系统和数据查询模块。
用户通过友好的用户界面，直接输入预计收获作物面积、收获作物类型、是否要秸秆还田、可靠性以及配件供应要求等决策参数，智能决策模块根据用户所提供的输入调用数据库中的数据(数据库存储收获机的型号、功率、实际生产率、平均油耗、购买价格、可靠性、配件供应、喂入形式、机手工资等最初数据)，并运用知识库中存放的专家经验知识综合考虑以上决策参数进行推理和解释，产生符合要求的稻麦联合收获机型号，然后计算出这些机型的收获作业成本，选取其中作业成本最低的收获机即为最佳收获机型号。该系统以农业智能系统开发平台PAID4.0(单机版)开发的，具有友好的用户界面，使一般没有计算机知识的农民用户也可方便地使用。一般用户的权限是进行数据的输入、决策和查询。
研究结果表明，该系统可有效地指导一般用户进行收获机选型，避免了传统的凭经验进行选型的片面性和盲目性，按作业成本最低的原则进行选型能够有效地提高资金的利用率，从而显著提高农业生产的经济效益。
In recent years, in our country the production and sale of combines have increased rapidly. At present, the combine's retained quantity of our country is about 300 thousand suits, which have improved the machinery harvesting level of rice and wheat, and improved the laboring conditions and created distinct social benefit and economic benefit. However, because of the technical difficulties, low standardization, low all-purpose capacity and economic problems etc., all of these factors restrict the development of the rice and wheat machinery harvesting market, and then the machinery harvesting level is still low. Another reason is that we always follow experts' subjective appraisements and experiences to select combines, but these experiences are lack of reliability sometimes.
At present, in our country the general existing problems on rice and wheat combines are high harvesting operation costs and low efficiency of fund using, and we are still lack of practicable way to make field planning and select combines compared with developed country. In order to solve these problems, this thesis, referring to domestic and foreign main research achievements and integrating the actual situation of Co., Ltd. of agriculture reclamation Group of Jiangsu province, developed Decision Support System (DSS) of rice and wheat combine selection by agricultural intelligent system as platform. This DSS is composed of five components, including user interface (person and computer dialoguing system), intelligent decision module, database and its management system, knowledge base and its management system and data-querying module (including fact-querying and result-querying).
By convenient user interface, user can directly input decision-making parameters such as prospective harvesting crop areas, harvesting crop type, conduction of straw return to fields or not, reliability and fittings provisions requirement and so on. Then the intelligent decision module uses data in the database (in the database storing initial data about combines' size, power, actual productivity, average fuel consumption, purchase price, reliability, fittings provision, feeding mode and operators' wage etc.) and exerts experts' experiences and knowledge stored in knowledge base to deduce and explain through considering all above decision parameters. In this process this system can suggest user some rice and wheat combine models (probably more than one) that satisfies the
requirement, and then this system calculates these combines' harvesting unit costs and selects the combine with minimum unit cost among these as the best combine. This system is developed by agricultural intelligent system developing platform PAID4.0 (stand-alone version), which has convenient user interface that makes farmers can easily use it without any computer knowledge. User only has the right to input data, make decision and query.
The research result shows that this system can be used to guide user to select combines effectively, whdch can avoid unilateralism and blindness of traditional selection through experience. Based on minimum unit cost to select combine, we can effectively improve the fund return rate, and then increase the economic benefit of agricultural production.
目前，我国普遍存在的稻麦联合收获机械问题是收获作业成本较高、资金合理利用率差，在机务计划制定和机具优化配备方面，与发达国家相比有很大差距。针对这些问题，本文借鉴国内外的主要研究成果，结合江苏省农垦集团的实际情况，以农业智能系统为平台研究开发了稻麦收获机械选型的决策支持系统。该决策支持系统由五大部分组成，包括用户界面(人机会话系统)、智能决策模块、数据库及其管理系统、知识库及其管理系统和数据查询模块。
用户通过友好的用户界面，直接输入预计收获作物面积、收获作物类型、是否要秸秆还田、可靠性以及配件供应要求等决策参数，智能决策模块根据用户所提供的输入调用数据库中的数据(数据库存储收获机的型号、功率、实际生产率、平均油耗、购买价格、可靠性、配件供应、喂入形式、机手工资等最初数据)，并运用知识库中存放的专家经验知识综合考虑以上决策参数进行推理和解释，产生符合要求的稻麦联合收获机型号，然后计算出这些机型的收获作业成本，选取其中作业成本最低的收获机即为最佳收获机型号。该系统以农业智能系统开发平台PAID4.0(单机版)开发的，具有友好的用户界面，使一般没有计算机知识的农民用户也可方便地使用。一般用户的权限是进行数据的输入、决策和查询。
研究结果表明，该系统可有效地指导一般用户进行收获机选型，避免了传统的凭经验进行选型的片面性和盲目性，按作业成本最低的原则进行选型能够有效地提高资金的利用率，从而显著提高农业生产的经济效益。
In recent years, in our country the production and sale of combines have increased rapidly. At present, the combine's retained quantity of our country is about 300 thousand suits, which have improved the machinery harvesting level of rice and wheat, and improved the laboring conditions and created distinct social benefit and economic benefit. However, because of the technical difficulties, low standardization, low all-purpose capacity and economic problems etc., all of these factors restrict the development of the rice and wheat machinery harvesting market, and then the machinery harvesting level is still low. Another reason is that we always follow experts' subjective appraisements and experiences to select combines, but these experiences are lack of reliability sometimes.
At present, in our country the general existing problems on rice and wheat combines are high harvesting operation costs and low efficiency of fund using, and we are still lack of practicable way to make field planning and select combines compared with developed country. In order to solve these problems, this thesis, referring to domestic and foreign main research achievements and integrating the actual situation of Co., Ltd. of agriculture reclamation Group of Jiangsu province, developed Decision Support System (DSS) of rice and wheat combine selection by agricultural intelligent system as platform. This DSS is composed of five components, including user interface (person and computer dialoguing system), intelligent decision module, database and its management system, knowledge base and its management system and data-querying module (including fact-querying and result-querying).
By convenient user interface, user can directly input decision-making parameters such as prospective harvesting crop areas, harvesting crop type, conduction of straw return to fields or not, reliability and fittings provisions requirement and so on. Then the intelligent decision module uses data in the database (in the database storing initial data about combines' size, power, actual productivity, average fuel consumption, purchase price, reliability, fittings provision, feeding mode and operators' wage etc.) and exerts experts' experiences and knowledge stored in knowledge base to deduce and explain through considering all above decision parameters. In this process this system can suggest user some rice and wheat combine models (probably more than one) that satisfies the
requirement, and then this system calculates these combines' harvesting unit costs and selects the combine with minimum unit cost among these as the best combine. This system is developed by agricultural intelligent system developing platform PAID4.0 (stand-alone version), which has convenient user interface that makes farmers can easily use it without any computer knowledge. User only has the right to input data, make decision and query.
The research result shows that this system can be used to guide user to select combines effectively, whdch can avoid unilateralism and blindness of traditional selection through experience. Based on minimum unit cost to select combine, we can effectively improve the fund return rate, and then increase the economic benefit of agricultural production.
引文
[1] Gajendra Singh, B K Pathak. A decision support system for mechanical harvesting and transportation of sugarcane in Thailand. Computers and Electronics in Agriculture, 1994(11)
[2] Kishor M Butani, Gajendra Singh. Decision support system for selection of agricultural machinery with a case study in India. Computers and Electronics in Agriculture, 1994(10): 91～104
[3] Massimo Lazzari, Fabrizio Mazzetto. A PC model for selecting multicropping farm machinery systems. Computers and Electronics in Agriculture. 1996(14): 43～59
[4] Nanseki-T, Operations of FAPS 97: A Decision Support System for Agricultural Technology and Farm Planning. Tohoku-Nogyo- Shikenjo-Kenkyu-Shiryo. 1998, No. 21
[5] H T Sogaard, C G Sorensen. A model for optimal selection of machinery sizes within the farm machinery system. Sixth International Conference on Computers in Agriculture, 588～596
[6] Hughes, H.A. and J.B.. Holtman. 1976. Machinery complement selection based on time constraints. Transactions of the ASAE 19(8): 812-814.
[7] Singh, Dvindar, and J.B. Holtman. 1979. A heuristic agricultural field machinery selection algorithm for multi-crop farms. Transactions of the ASAE 22(4): 763-770.
[8] 陈建，陈忠慧，农场作物及机器设备选择系统的研究，农业机械学报，1997，28(3)：65-70
[9] 郭凤祥，河套平原农业机器系统的优化配备 全国农机运用与管理学科第七次研讨会论文集，1994．8
[10] 郭凤祥，段俊平，呼盟岭北国营农场农业机器系统的配备计算 内蒙古农牧学院学报，1991,12(2)：82～92
[11] 张东兴，江苏省国营机械化小农场机器系统优化[学位论文]北京农业工程大学，1988
[12] 王福林，黑龙江省国营农场麦豆收获的机械化系统分析 [硕士学位论文] 东北农学院，1988
[13] He Ruiyin, Liu Deying. A Model for Selecting Farm Machinery Based on Crop Production. 2001, Promoting Global Innovation of Agricultural Science & Sustainable Agricultural Development. International Conference on Agricultural Science and Technology, Session 6
[14] 曾涛，决策支持系统的应用研究[硕士学位论文]南开大学，1998．5
[15] 俞文彬，基于数据仓库和数据挖掘的DSS研究[硕士学位论文]上海交通大学
[16] 姚岚，基于“四库”的决策支持系统——方法库、数据库及其管理系统[硕士学位论文]东
北工学院，1989．12
[17] 梁红卫，决策支持系统的用户界面研究 [硕士学位论文] 中国科学院自动化研究所，1996．6
[18] 蒋爱军，数据仓库和智能查询研究 [硕士学位论文] 中山大学，1998．5
[19] 王莹，决策支持系统及其最新发展，科技导报，1998．1
[20] 曾庆伟，现代管理信息系统，武汉：湖北科学技术出版社，2002．12
[21] 刘耀，论决策支持系统的应用现状和发展前景，计算机与应用，2000．2
[22] 吉浩人，基于数据仓库技术的决策支持系统之方案研究[硕士学位论文]
[23] 李小明，决策支持系统的研究现状及发展趋势，河南电大1998．1
[24] 薛华成，管理信息系统，北京：清华大学出版社，1999．5
[25] 宋远方，成栋，管理信息系统，北京：中国人民大学出版社，1999．12
[26] 刘振营等，透视小麦、水稻联合收割机，农业机械，2004．2
[27] 刘志渝，浅谈我国联合收割机的发展，农机质量与监督，1997．5
[28] 魏忠勇，国外联合收割机的发展趋势，新疆农机化，1999．5
[29] 熊元芳，水稻联合收割机的选购与使用，广东农机，1999．2
[30] 蒋亦元，水稻联合收获机性能分析与选型，中国农机化，2000．3
[31] 王巽怀，谈联合收获机的合理选择，中国农机化，1997．4
[32] 王志，阎楚良，牟仁生，李志庆，胡发臣，联合收割机可靠性评价方法的探讨，农业机械学报，2002．9
[33] 张春平，联合收割机跨区作业经济效益降低的原因，农业装备技术，2003．5
[34] 陈永柱，跨区作业是提高农民收入的重要手段，江苏农机化，2003．5
[35] 张缔庆，陈济勤，农业机器运用管理学，西安：西安交通大学出版社，1988
[36] 林兴军，陈华，农业机械作业经济效益评价方法的研究，农机化研究，1998．11
[37] 吴忠平，联合收割机作业成本分析，农机化研究，2003．10(第4期)
[38] Wendell Bowers, MACHINERY MANAGEMENT, Farm Business Management, 1992
[39] 张广成，水稻联合收割机的选购与使用，广西农业机械化，2001．3
[40] 农业机械作业经济效果的评价方法，中华人民共和国农业部标准(NY170-89)，1989
[41] 廉师友，人工智能技术导论，西安：西安电子科技大学出版社，2002
[42] 尹朝庆，尹皓，人工智能与专家系统，北京：中国水利水电出版社，2001
[43] 王志，联合收割机可靠性问题的研究，农业机械学报，2002．3
[44] 付强，杨广林，金菊良，基于PPC模型的农机选型与优序关系研究，农业机械学报，2003．1
[45] 张志涌 等编著，精通MATLAB6．5版，北京：北京航天航空大学出版社，2003
[2] Kishor M Butani, Gajendra Singh. Decision support system for selection of agricultural machinery with a case study in India. Computers and Electronics in Agriculture, 1994(10): 91～104
[3] Massimo Lazzari, Fabrizio Mazzetto. A PC model for selecting multicropping farm machinery systems. Computers and Electronics in Agriculture. 1996(14): 43～59
[4] Nanseki-T, Operations of FAPS 97: A Decision Support System for Agricultural Technology and Farm Planning. Tohoku-Nogyo- Shikenjo-Kenkyu-Shiryo. 1998, No. 21
[5] H T Sogaard, C G Sorensen. A model for optimal selection of machinery sizes within the farm machinery system. Sixth International Conference on Computers in Agriculture, 588～596
[6] Hughes, H.A. and J.B.. Holtman. 1976. Machinery complement selection based on time constraints. Transactions of the ASAE 19(8): 812-814.
[7] Singh, Dvindar, and J.B. Holtman. 1979. A heuristic agricultural field machinery selection algorithm for multi-crop farms. Transactions of the ASAE 22(4): 763-770.
[8] 陈建，陈忠慧，农场作物及机器设备选择系统的研究，农业机械学报，1997，28(3)：65-70
[9] 郭凤祥，河套平原农业机器系统的优化配备 全国农机运用与管理学科第七次研讨会论文集，1994．8
[10] 郭凤祥，段俊平，呼盟岭北国营农场农业机器系统的配备计算 内蒙古农牧学院学报，1991,12(2)：82～92
[11] 张东兴，江苏省国营机械化小农场机器系统优化[学位论文]北京农业工程大学，1988
[12] 王福林，黑龙江省国营农场麦豆收获的机械化系统分析 [硕士学位论文] 东北农学院，1988
[13] He Ruiyin, Liu Deying. A Model for Selecting Farm Machinery Based on Crop Production. 2001, Promoting Global Innovation of Agricultural Science & Sustainable Agricultural Development. International Conference on Agricultural Science and Technology, Session 6
[14] 曾涛，决策支持系统的应用研究[硕士学位论文]南开大学，1998．5
[15] 俞文彬，基于数据仓库和数据挖掘的DSS研究[硕士学位论文]上海交通大学
[16] 姚岚，基于“四库”的决策支持系统——方法库、数据库及其管理系统[硕士学位论文]东
北工学院，1989．12
[17] 梁红卫，决策支持系统的用户界面研究 [硕士学位论文] 中国科学院自动化研究所，1996．6
[18] 蒋爱军，数据仓库和智能查询研究 [硕士学位论文] 中山大学，1998．5
[19] 王莹，决策支持系统及其最新发展，科技导报，1998．1
[20] 曾庆伟，现代管理信息系统，武汉：湖北科学技术出版社，2002．12
[21] 刘耀，论决策支持系统的应用现状和发展前景，计算机与应用，2000．2
[22] 吉浩人，基于数据仓库技术的决策支持系统之方案研究[硕士学位论文]
[23] 李小明，决策支持系统的研究现状及发展趋势，河南电大1998．1
[24] 薛华成，管理信息系统，北京：清华大学出版社，1999．5
[25] 宋远方，成栋，管理信息系统，北京：中国人民大学出版社，1999．12
[26] 刘振营等，透视小麦、水稻联合收割机，农业机械，2004．2
[27] 刘志渝，浅谈我国联合收割机的发展，农机质量与监督，1997．5
[28] 魏忠勇，国外联合收割机的发展趋势，新疆农机化，1999．5
[29] 熊元芳，水稻联合收割机的选购与使用，广东农机，1999．2
[30] 蒋亦元，水稻联合收获机性能分析与选型，中国农机化，2000．3
[31] 王巽怀，谈联合收获机的合理选择，中国农机化，1997．4
[32] 王志，阎楚良，牟仁生，李志庆，胡发臣，联合收割机可靠性评价方法的探讨，农业机械学报，2002．9
[33] 张春平，联合收割机跨区作业经济效益降低的原因，农业装备技术，2003．5
[34] 陈永柱，跨区作业是提高农民收入的重要手段，江苏农机化，2003．5
[35] 张缔庆，陈济勤，农业机器运用管理学，西安：西安交通大学出版社，1988
[36] 林兴军，陈华，农业机械作业经济效益评价方法的研究，农机化研究，1998．11
[37] 吴忠平，联合收割机作业成本分析，农机化研究，2003．10(第4期)
[38] Wendell Bowers, MACHINERY MANAGEMENT, Farm Business Management, 1992
[39] 张广成，水稻联合收割机的选购与使用，广西农业机械化，2001．3
[40] 农业机械作业经济效果的评价方法，中华人民共和国农业部标准(NY170-89)，1989
[41] 廉师友，人工智能技术导论，西安：西安电子科技大学出版社，2002
[42] 尹朝庆，尹皓，人工智能与专家系统，北京：中国水利水电出版社，2001
[43] 王志，联合收割机可靠性问题的研究，农业机械学报，2002．3
[44] 付强，杨广林，金菊良，基于PPC模型的农机选型与优序关系研究，农业机械学报，2003．1
[45] 张志涌 等编著，精通MATLAB6．5版，北京：北京航天航空大学出版社，2003