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Advances in Modeling Agricultural Systems

:	Panos M. Pardalos, Petraq J. Papajorgji
:	Petraq J. Papajorgji, Panos M. Pardalos
:	Advances in Modeling Agricultural Systems
:	Springer-Verlag
:	9780387751818
:	1
:	CHF 115.70
:

:	Allgemeines, Lexika
:	English

:	522
:	Wasserzeichen/DRM
:	PC/MAC/eReader/Tablet
:	PDF

Agriculture has experienced a dramatic change during the past decades. The change has been structural and technological. Structural changes can be seen in the size of current farms; not long ago, agricultural production was organized around small farms, whereas nowadays the agricultural landscape is dominated by large farms. Large farms have better means of applying new technologies, and therefore technological advances have been a driving force in changing the farming structure. New technologies continue to emerge, and their mastery and use in requires that farmers gather more information and make more complex technological choices. In particular, the advent of the Internet has opened vast opportunities for communication and business opportunities within the agricultural com- nity. But at the same time, it has created another class of complex issues that need to be addressed sooner rather than later. Farmers and agricultural researchers are faced with an overwhelming amount of information they need to analyze and synthesize to successfully manage all the facets of agricultural production. This daunting challenge requires new and complex approaches to farm management. A new type of agricultural management system requires active cooperation among multidisciplinary and multi-institutional teams and ref- ing of existing and creation of new analytical theories with potential use in agriculture. Therefore, new management agricultural systems must combine the newest achievements in many scientific domains such as agronomy, economics, mathematics, and computer science, to name a few.

	Preface	7
	Contents	9
	Contributors	12
	The Model Driven Architecture Approach: A Framework for Developing Complex Agricultural Systems	18
	1 Introduction	19
	2 MDA and Unified Modeling Language	20
	3 Modeling Behavior	23
	3.1 The Object Constraint Language	23
	3.2 The Action Language	24
	4 Modeling a Crop Simulation	25
	4.1 The Conceptual Model, or PIM	25
	4.2 Providing Objects with Behavior	27
	4.3 Data Requirements	30
	4.4 Code Generation	31
	4.5 Results	31
	5 Conclusions	32
	References	34
	A New Methodology to Automate the Transformation of GIS Models in an Iterative Development Process	36
	1 Introduction	37
	2 The Software DevelopmentProcess	38
	3 The Model Driven Architecture	41
	4 The New Interactive Development Method	42
	4.1 The Principle of the Continuous Integration Unified Process Method	42
	4.2 The Software Development Process Approach: A Generalization of the MDA Approach	45
	4.3 The Software Development Process Model: A Modeling Artifact for Knowledge Capitalization	45
	4.4 The Complete Set of Transformations Enabling a Full MDA Process for Databases	46
	4.4.1 Diffusion Transformation and Management of the Software Development Process Model	47
	4.4.2 The GIS Transformations	47
	The GIS Design Pattern Generation Transformation	47
	The Pictogram Translation Transformation	48
	4.4.3 The SQL Transformation	50
	5 Conclusions	51
	References	52
	Application of a Model Transformation Paradigm in Agriculture: A Simple Environmental System Case Study	54
	1 Introduction	54
	2 The Continuous Integration Unified Process	56
	3 Transformations of the Continuous Integration Unified Process in Action	57
	3.1 Construction of the Software Development Process Model	59
	3.2 First Iteration	60
	3.3 Second Iteration	65
	4 Conclusions	69
	References	70
	Constraints Modeling in Agricultural Databases	72
	1 Introduction	72
	2 The Object Constraint Language	73
	3 Example of a Tool Supporting OCL: The Dresden OCL Toolkit	77
	4 Extending OCL for Spatial Objects	79
	5 Conclusions	81
	References	81
	Design of a Model-Driven Web Decision Support System in Agriculture: From Scientific Models to the Final Software	83
	1 Introduction	83
	1.2 General Points	83
	1.2 Generic Design of Decision Support Systems	85
	1.2 Development of DSS Software for Phytosanitary Plant Protection	86
	2 Design of the Scientific Model	88
	2.1 Description of the Plant-Parasite-Phytosanitary Protection System	88
	2.2 The Plant Model	90
	2.3 Parasite Model	93
	2.4 The Phytosanitary Protection Model	96
	3 The Scientific Model s Set Up and Validation	97
	3.1 Principle	97
	3.2 Methods Used for Sensitivity Analysis, Calibration, and Validation	98
	3.3 The Choice of Modeling and Validation Tools	99
	4 Software Architecture of the Scientific Model	100
	4.1 Class Diagram of the Plant-Parasite-Phytosanitary Protection System	101
	4.2 The Plant Model	104
	4.3 The Parasite Model	109
	5 The Application s Architecture	110
	5.1 The Three-Tier Architecture and the Design Pattern Strategy	110
	5.2 The Three-Tier Architecture Layers and the Technologies Used	112
	5.2.1 The Presentation Layer and Client-Server Communication	112
	5.2.2 The Business Layer and the Dependency Injection Design Pattern	113
	5.2.3 The DAO Layer and Hibernate	114
	6 Conclusions	115
	References	116
	How2QnD: Design and Construction of a Game-Style, Environmental Simulation Engine and Interface Using UML, XML, and Java	119
	1 Introduction	120
	1.4 Conceptual Background: Learning Through Games	120
	1.4 QnD: A Game-Style Simulation for Adaptive Learning and Decision Making	121
	2 QnD Design Overview: Designing from Ideas to a Playable Game	122
	2.1 GameView Design	122
	2.2 Simulation Engine Design	123
	2.3 QnD Use-Case Designs: Three Actors, Many Roles	127
	3 Questions and Decisions About Elephant-Vegetation Dynamics in the Kruger National Park, South Africa	129
	3.1 KNP Elephant Model Development Strategies	130
	3.2 Design2Game: Translating Systems Designs and Previous Modeling Efforts into QnD SimulationEngine and GameView Implementations	131
	3.2.1 QnDEleSim SimulationEngine: Setting Spatial and Temporal Execution	132
	3.2.2 QnDEleSim SimulationEngine: Setting Input Drivers and Scenarios	132
	3.2.3 QnDEleSim SimulationEngine: Setting CLocalComponents, DData, and PProcesses	132