黑龙江省水稻决策支持系统总体设计及部分模块功能实现
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摘要
农业产业结构调整和我国入世后，农业对信息服务产生了很大的需求。2002年10月北京第三届亚洲农业信息技术大会(AFITA2002)上，专家们强调了21世纪农业信息的地位，并指出农业不全面实现信息化，其现代化是不可想象的，贫穷的标志首先是信息贫乏。农业的特点是时空差异和变异性大，生产稳定性和可控程度差。特别是我省地处高寒边远地区，农业交通和信息闭塞，这决定了我省农业信息服务的复杂性和实现农业信息的难度。用户普遍反映媒体中缺乏快捷、有效的实用信息，通过信息决策有不少难度。信息持有者和信息使用者存在巨大的信息鸿沟(Information Gap)，同时大量混乱的信息成为“信息垃圾”，影响着信息的使用。黑龙江省土地辽阔，是我国主要的粮食生产基地，水稻在粮食作物中的地位举足轻重。专家指出，中国加入WTO后，在黑龙江4大粮食作物玉米、小麦、大豆和水稻中，水稻最具有竞争优势。但黑龙江省的信息不发达，农业智能化水平不高，所以在市场经济下水稻的优势还没有全部发挥出来。根据党的十六大制定的发展农业信息化的方针和黑龙江省作出的推进智能化农业信息技术的精神，利用东北农业大学得天独厚的计算机和农业领域知识，根据黑龙江省主要水稻生产基地缺少农业专家的特点，开发出黑龙江省水稻决策支持系统。以先进的软件技术，多媒体技术和系统集成技术，将多名农业专家多年积累的经验、技术和方法以及大量的农业作物普遍性知识，综合黑龙江省地域等基本事实数据，经过分析、提炼、整理、结合形成知识库，利用推理机、模型库、方法库，最终集成为科学性、实用性、决策性的农业决策支持系统。针对农作物生产管理提出科学、合理的技术咨询与支持。
水稻决策支持系统设计遵循软件工程的生命周期法，分阶段设计开发，用结构化分析方法提出整个系统概要设计方案。在决策系统的设计与实现中，首先分析现行水稻栽培技术的流程，之后绘制了决策支持系统的数据流图，然后采用数据流分析法，提出子系统的功能结构表，最后利用VB、SQL、ACCESS数据库、多媒体技术等面向对象的编程工具实现水稻决策支持系统的功能。农业决策支持系统是农业专家系统的具体实现，而专家系统又是智能信息化的核心，只有以信息化的发展来带动农业现代化，才能使我省农业进一步发展，从而在未来的国际国内竞争中立于不败之地。该系统将计算机技术和农学知识有机结合，技术先进、功能全面、结构规范、界面友好、易学实用。对黑龙江省智能化农业信息技术的发展具有一定的理论和实用价值。
After agricultural industrial structure adjustment and our country enter the WTO , agriculture has produced very great demand for information service. The third Asia agricultural information technology conference of Beijing of October of 2002( AFTTA2002) is had, the experts emphasize the status of the agricultural information in the 21st century, And point out that agriculture does not realize the informationization all-sidedly, its modernization is unimaginable, The sign of the poverty is that the information is poor at first. The characteristic of agriculture is space-time the difference and variability are great, it is bad to produce the stability and controllable degree. Especially our province is located in the high and cold outlying district , the agricultural traffic and information are stopped up , This has determined complexity of agricultural information service of our province and realize the degree of difficulty of the agricultural information. Users generally reflect that lacks the swift, effective practical information in the media , Making policy through the information has much degree of difficulty. Information holder and information user have enormous information wide gaps ( InformationGap), a large amount of confused information becomes" information rubbish" at the same time, Influencing the use of the information. Whether unless Heilongjiang Province the vast in the lands, for our country main grain production base,rice on cereal crops it is the with a very important position. The expert points out , after China joins WTO, in Heilungkiang 4 big cereal crops maize, wheat, soybean and rice, The rice is the most competitive. But the information of Heilongjiang Prdvince is undeveloped, agriculture's intelligent 1 evel i s n ot h igh, s o has not a 11 b een b rought i nto play yet i n t he advantages o f making the rice of market economy. Spirit of the promotion intelligent agricultural information technology made according to the policy of 16 great development IT application to agriculture that make of the party and Heilongjiang Province, Utilize the computer richly endowed by nature of agricultural university of the Northeast and agriculture's domain knowledge, Lack the characteristic of the agricultural expert according to the main rice production base of Heilongjiang Province, Develop rice DSS of Heilongjiang Province. With advanced software engineering, multimedia technology and system integration technology, Many persons of agricultural experience, technology, method and agricultural crop general sex knowledge as much as a large amount of that expert accumulate for many years, Synthesize basic fact data, such as region of Heilongjiang Province,etc., through analysing, refine, put in order, combine and form the knowledge base, Utilize the reasoning machine, the model storehouse, method storehouse, integrate for science, practibility, policy-making agricultural DSS finally. Put forward science, rational technological consultation and supporting to the production management of the crops. Rice DSS design and follow life cycle law of soft project, Design and develop stage by stage, put forward the plan of design of the whole systematic outline with the analytical method of structure ization. In systematic design and in realizing, analyse
current rice procedure of cultivation technique at first of making policy, The dataflow of drawing DSS is pursued , then adopted the analytic approach of the dataflow, Put forward the function structure form of the subsystem, Utilize VB, SQL finally, ACCESS data base, multimedia technology,etc. facing target programming tool realize rice function of DSS. Agricultural DSS is the realizing concretly of agricultural expert system, and the expert system is the core of the intelligent informationization, Drive agricultural modernization only with informative development, could make the agriculture of our province develop further , Thus establish in an unassailable position in competing international and domestically in the future. This system combines the technolo
水稻决策支持系统设计遵循软件工程的生命周期法，分阶段设计开发，用结构化分析方法提出整个系统概要设计方案。在决策系统的设计与实现中，首先分析现行水稻栽培技术的流程，之后绘制了决策支持系统的数据流图，然后采用数据流分析法，提出子系统的功能结构表，最后利用VB、SQL、ACCESS数据库、多媒体技术等面向对象的编程工具实现水稻决策支持系统的功能。农业决策支持系统是农业专家系统的具体实现，而专家系统又是智能信息化的核心，只有以信息化的发展来带动农业现代化，才能使我省农业进一步发展，从而在未来的国际国内竞争中立于不败之地。该系统将计算机技术和农学知识有机结合，技术先进、功能全面、结构规范、界面友好、易学实用。对黑龙江省智能化农业信息技术的发展具有一定的理论和实用价值。
After agricultural industrial structure adjustment and our country enter the WTO , agriculture has produced very great demand for information service. The third Asia agricultural information technology conference of Beijing of October of 2002( AFTTA2002) is had, the experts emphasize the status of the agricultural information in the 21st century, And point out that agriculture does not realize the informationization all-sidedly, its modernization is unimaginable, The sign of the poverty is that the information is poor at first. The characteristic of agriculture is space-time the difference and variability are great, it is bad to produce the stability and controllable degree. Especially our province is located in the high and cold outlying district , the agricultural traffic and information are stopped up , This has determined complexity of agricultural information service of our province and realize the degree of difficulty of the agricultural information. Users generally reflect that lacks the swift, effective practical information in the media , Making policy through the information has much degree of difficulty. Information holder and information user have enormous information wide gaps ( InformationGap), a large amount of confused information becomes" information rubbish" at the same time, Influencing the use of the information. Whether unless Heilongjiang Province the vast in the lands, for our country main grain production base,rice on cereal crops it is the with a very important position. The expert points out , after China joins WTO, in Heilungkiang 4 big cereal crops maize, wheat, soybean and rice, The rice is the most competitive. But the information of Heilongjiang Prdvince is undeveloped, agriculture's intelligent 1 evel i s n ot h igh, s o has not a 11 b een b rought i nto play yet i n t he advantages o f making the rice of market economy. Spirit of the promotion intelligent agricultural information technology made according to the policy of 16 great development IT application to agriculture that make of the party and Heilongjiang Province, Utilize the computer richly endowed by nature of agricultural university of the Northeast and agriculture's domain knowledge, Lack the characteristic of the agricultural expert according to the main rice production base of Heilongjiang Province, Develop rice DSS of Heilongjiang Province. With advanced software engineering, multimedia technology and system integration technology, Many persons of agricultural experience, technology, method and agricultural crop general sex knowledge as much as a large amount of that expert accumulate for many years, Synthesize basic fact data, such as region of Heilongjiang Province,etc., through analysing, refine, put in order, combine and form the knowledge base, Utilize the reasoning machine, the model storehouse, method storehouse, integrate for science, practibility, policy-making agricultural DSS finally. Put forward science, rational technological consultation and supporting to the production management of the crops. Rice DSS design and follow life cycle law of soft project, Design and develop stage by stage, put forward the plan of design of the whole systematic outline with the analytical method of structure ization. In systematic design and in realizing, analyse
current rice procedure of cultivation technique at first of making policy, The dataflow of drawing DSS is pursued , then adopted the analytic approach of the dataflow, Put forward the function structure form of the subsystem, Utilize VB, SQL finally, ACCESS data base, multimedia technology,etc. facing target programming tool realize rice function of DSS. Agricultural DSS is the realizing concretly of agricultural expert system, and the expert system is the core of the intelligent informationization, Drive agricultural modernization only with informative development, could make the agriculture of our province develop further , Thus establish in an unassailable position in competing international and domestically in the future. This system combines the technolo
引文
1 翟虎渠，范小建．加快信息化的建设AFITA，北京，2002中国科技出版社：1-5
2 刘爱民，封志明．现代精准农业及我国精准农业的发展方向．中国农业大学学报2000．5：1-3
3 陈文伟．决策支持系统及其开发．清华大学出版社，1994：29-59
4 高崇辉．黑龙江省调查报告．农业出版社．2001：2-10
5 黄梯云等．智能决策支持系统 清华大学出版社．1996：16-49
6 陈文伟等．决策支持系统新式结构体系．中国科技出版社，1998：120-145
7 高洪深．决策支持系统(DSS)理论·方法·案例．清华大学出版社，1996：77-113
8 许兆新，周双娥，郝燕玲．决策支持系统相关技术综述．计算机应用研究．2001，(2)：17-20
9 王永庆．人工智能原理与方法．西安：西安交通大学出版社，1988：53-119
10 耿刚勇，仲萃豪．采用软件构件技术开发领域应用软件．计算机科学，1997，2：134-142
11 刘有才，刘增良．模糊专家系统原理与设计．北京航空航天大学出版社，1995：144-257
12 何新贵．模糊知识处理的理论与技术 国防工业出版社，1994：46-65
13 吴泉源等．人工智能与专家系统，国防科技大学出版社，1995：17-86
14 张素萍．浅谈基于数据仓库的决策支持系统．计算机应用研究，1999，(5)：5-12
15 韩进欣等．基于机器学习理论的智能决策支持积模型操纵方法研究，决策与决策支持系统，1996，6(1)：112-145
16 刘根深等．红毛丹施肥专家系统．计算机与农业，2000，NO3：28—41
17 赵微平．土壤和植物养分的测定及施肥．化学工业出版社，1993：3-44
18 王孝通等．模型管理核心问题研究．决策与决策支持系统，1996，6(2)：21-77
19 曹文君．知识库系统原理及其应用．复旦大学出版社，1995：50-88
20 黄梯云，李一军．管理信息系统．高等教育出版社，1999．6：10-25
21 邵军力，张景等．人工智能基础．电子工业出版社，2000，3：21-217
22 刘晶珠．决策支持系统导论(2)．哈尔滨工业大学出版社，2002：27-45
23 朱海滨等．面向对象计算机研究中的几个问题．计算机工程，1991，5：16-29
24 萨师煊等．数据库系统概论．高等教育出版社，1995：12-134
25 尹朝庆，尹皓．人工智能与专家系统．中国水利水电出版社．2002：9-32
26 刘江宁．决策支持系统中证据的不确定性．1995：31-43
27 张宏林等．Visual Basic6.0编程疑难详解．人民邮电出版社，2000．1：7-42
28 棠葆林．面向对象的软件开发方法．小型微型计算机，1994，15(2)：38-41
29 Joseph Giarratano (美) . Expert Systems Principles and Programming 2000. 1:24-75
30 BrockschmidTK. Programing InsideOLE; 1994: Washington: 17-53
31 E. C. Payne, R. C. McArthur. Developing Expert System, New York, 1990:14-79
32 D. W. P. atterson, Introduction to Artificial Intelligenece and Expert System.
Prentice Hall, New Jersty ,1990:28-70
33 S. Horikawa. On Fuzzy Modelling Using furry neural networks with BP algorithm. IEEE Trans. Neural Networks, No. 2,1999:lO-82
34 Barr A, Feigenbaum E A. Handbook of Artificial Intelligence Vol. 3 William inc.1993:62-88
35 David Hausslaer, Quantifying Inductive Bias: Ai Learning Algorithms and Valiant's Learning Framework, Artificial Intelligence, 1988 Vol. 36:114-137
36 Eduard H. How, Automated Discourse Generation Using Discourse Structure Relations, Artificial Iintelligence 63, 1993:12-39
37 Zhangjing, Lirenhou, Neural Network Expert System and Their Application, Pacific-Asian Conference on Expert System, Proc. On PACES'95, 1995:28-45
38 D. A. Bell, From Data Properties to Evidence, IEEE Transactions on knowledge and data engineering, Vol. 5, 1993:121-45
39 Donald Michie, Turing's Test and Conscious Thought, Artificial Intelligence, Vol. 60, 1991:22-60
40 Grossbery Edited. Neural networks and natural intelligence, The MIT Press, 1988:19.
41 Richard P. Lippmann, Introduction to Computing With Neural Nets. IEEE ASSP Magazine, 1987:11-42
42 Elaine Rich &Kevin Knight, Artificial Intelligence, Second Edition, McGraw-Hall, inc, 2001:134-156
43 Eugene Chamik, Introduction to Artificial Intelligence, Addison-Wesley Publishing Company Inc. 1985:12-44
44 Eugene Charniak, Artificial Intelligence Programming, Second Edition, Lawrence Erlbaum Associates Publishers, 1997:44-75
45 George F.Luger William a. Stubblefield, Artificial Intelligence Third Edithion, Addison Wesley Longman, Inc. 1998:27-48
46 Frederick Hayes. et all Edited, Builing Expert ystem, ddison-Wesley, 1997:7-34.
47 Larry R. Medsker. Hybrid Intelligent System. Kluwer Academic Publishers. 1995:7-9.
48 Paul Dagum, Approximating Probabilistic Inference in Bayesian Belief network is NP-hard, Artificial Intelligence Vol. 60. 1993:13-30.
49 Granino A. Kom, Neural Network Experiments on Personal Computers and Workstations, The MIT Press, 1991:112-135
50 S Subrahmanian, S. Jajodia. Data base system of multimedia. 1998.8:35-47
51 Ralph E Sprague. A Framework for the development of recusoon support systems MIS Quarterly, 1980:33-67
2 刘爱民，封志明．现代精准农业及我国精准农业的发展方向．中国农业大学学报2000．5：1-3
3 陈文伟．决策支持系统及其开发．清华大学出版社，1994：29-59
4 高崇辉．黑龙江省调查报告．农业出版社．2001：2-10
5 黄梯云等．智能决策支持系统 清华大学出版社．1996：16-49
6 陈文伟等．决策支持系统新式结构体系．中国科技出版社，1998：120-145
7 高洪深．决策支持系统(DSS)理论·方法·案例．清华大学出版社，1996：77-113
8 许兆新，周双娥，郝燕玲．决策支持系统相关技术综述．计算机应用研究．2001，(2)：17-20
9 王永庆．人工智能原理与方法．西安：西安交通大学出版社，1988：53-119
10 耿刚勇，仲萃豪．采用软件构件技术开发领域应用软件．计算机科学，1997，2：134-142
11 刘有才，刘增良．模糊专家系统原理与设计．北京航空航天大学出版社，1995：144-257
12 何新贵．模糊知识处理的理论与技术 国防工业出版社，1994：46-65
13 吴泉源等．人工智能与专家系统，国防科技大学出版社，1995：17-86
14 张素萍．浅谈基于数据仓库的决策支持系统．计算机应用研究，1999，(5)：5-12
15 韩进欣等．基于机器学习理论的智能决策支持积模型操纵方法研究，决策与决策支持系统，1996，6(1)：112-145
16 刘根深等．红毛丹施肥专家系统．计算机与农业，2000，NO3：28—41
17 赵微平．土壤和植物养分的测定及施肥．化学工业出版社，1993：3-44
18 王孝通等．模型管理核心问题研究．决策与决策支持系统，1996，6(2)：21-77
19 曹文君．知识库系统原理及其应用．复旦大学出版社，1995：50-88
20 黄梯云，李一军．管理信息系统．高等教育出版社，1999．6：10-25
21 邵军力，张景等．人工智能基础．电子工业出版社，2000，3：21-217
22 刘晶珠．决策支持系统导论(2)．哈尔滨工业大学出版社，2002：27-45
23 朱海滨等．面向对象计算机研究中的几个问题．计算机工程，1991，5：16-29
24 萨师煊等．数据库系统概论．高等教育出版社，1995：12-134
25 尹朝庆，尹皓．人工智能与专家系统．中国水利水电出版社．2002：9-32
26 刘江宁．决策支持系统中证据的不确定性．1995：31-43
27 张宏林等．Visual Basic6.0编程疑难详解．人民邮电出版社，2000．1：7-42
28 棠葆林．面向对象的软件开发方法．小型微型计算机，1994，15(2)：38-41
29 Joseph Giarratano (美) . Expert Systems Principles and Programming 2000. 1:24-75
30 BrockschmidTK. Programing InsideOLE; 1994: Washington: 17-53
31 E. C. Payne, R. C. McArthur. Developing Expert System, New York, 1990:14-79
32 D. W. P. atterson, Introduction to Artificial Intelligenece and Expert System.
Prentice Hall, New Jersty ,1990:28-70
33 S. Horikawa. On Fuzzy Modelling Using furry neural networks with BP algorithm. IEEE Trans. Neural Networks, No. 2,1999:lO-82
34 Barr A, Feigenbaum E A. Handbook of Artificial Intelligence Vol. 3 William inc.1993:62-88
35 David Hausslaer, Quantifying Inductive Bias: Ai Learning Algorithms and Valiant's Learning Framework, Artificial Intelligence, 1988 Vol. 36:114-137
36 Eduard H. How, Automated Discourse Generation Using Discourse Structure Relations, Artificial Iintelligence 63, 1993:12-39
37 Zhangjing, Lirenhou, Neural Network Expert System and Their Application, Pacific-Asian Conference on Expert System, Proc. On PACES'95, 1995:28-45
38 D. A. Bell, From Data Properties to Evidence, IEEE Transactions on knowledge and data engineering, Vol. 5, 1993:121-45
39 Donald Michie, Turing's Test and Conscious Thought, Artificial Intelligence, Vol. 60, 1991:22-60
40 Grossbery Edited. Neural networks and natural intelligence, The MIT Press, 1988:19.
41 Richard P. Lippmann, Introduction to Computing With Neural Nets. IEEE ASSP Magazine, 1987:11-42
42 Elaine Rich &Kevin Knight, Artificial Intelligence, Second Edition, McGraw-Hall, inc, 2001:134-156
43 Eugene Chamik, Introduction to Artificial Intelligence, Addison-Wesley Publishing Company Inc. 1985:12-44
44 Eugene Charniak, Artificial Intelligence Programming, Second Edition, Lawrence Erlbaum Associates Publishers, 1997:44-75
45 George F.Luger William a. Stubblefield, Artificial Intelligence Third Edithion, Addison Wesley Longman, Inc. 1998:27-48
46 Frederick Hayes. et all Edited, Builing Expert ystem, ddison-Wesley, 1997:7-34.
47 Larry R. Medsker. Hybrid Intelligent System. Kluwer Academic Publishers. 1995:7-9.
48 Paul Dagum, Approximating Probabilistic Inference in Bayesian Belief network is NP-hard, Artificial Intelligence Vol. 60. 1993:13-30.
49 Granino A. Kom, Neural Network Experiments on Personal Computers and Workstations, The MIT Press, 1991:112-135
50 S Subrahmanian, S. Jajodia. Data base system of multimedia. 1998.8:35-47
51 Ralph E Sprague. A Framework for the development of recusoon support systems MIS Quarterly, 1980:33-67
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