Computer Simulation Analysis Of Biological And Agricultural Systems

Computer Simulation Analysis of Biological and Agricultural Systems focuses on the integration of mathematical models and the dynamic simulation essential to system analysis, design, and synthesis. The book emphasizes the quantitative dynamic relationships between elements and system responses. Problems of various degrees of difficulty and complexity are discussed to illustrate methods of computer-aided design and analysis that can bridge the gap between theories and applications. These problems cover a wide variety of subjects in the biological and agricultural fields. Specific guidelines and practical methods for defining requirements, developing specifications, and integrating system modeling early in simulation development are included as well. Computer Simulation Analysis of Biological and Agricultural Systems is an excellent text and self-guide for agricultural engineers, agronomists, foresters, horticulturists, soil scientists, mechanical engineers, and computer simulators.

Computer Simulation Analysis of Biological and Agricultural Systems focuses on the integration of mathematical models and the dynamic simulation essential to system analysis, design, and synthesis. The book emphasizes the quantitative dynamic relationships between elements and system responses. Problems of various degrees of difficulty and complexity are discussed to illustrate methods of computer-aided design and analysis that can bridge the gap between theories and applications. These problems cover a wide variety of subjects in the biological and agricultural fields. Specific guidelines and practical methods for defining requirements, developing specifications, and integrating system modeling early in simulation development are included as well. Computer Simulation Analysis of Biological and Agricultural Systems is an excellent text and self-guide for agricultural engineers, agronomists, foresters, horticulturists, soil scientists, mechanical engineers, and computer simulators.

A fast-growing interest in the concepts and application of systems research has spawned a wide and general literature over the past decade. Most disciplinary areas have been touched, but commerce, engineering and military studies have, perhaps, been best served with outstanding texts. No provision has so far been made for a general book at introductory level of direct relevance to agricultural science, technology and management. General reviews are, of course, valuable to the agricultural-systems researcher but agricultural systems, with important biological components interacting with equally vital social and economic elements, embody particular characteristics which influence the approach to their study. This book is written in the belief that the concepts as well as the technology of the systems approach have a basic role in the rational advancement of the agricultural discipline and in the improvement of efficiency in agricultural research and practice. A basic and introductory text is an essential pre requisite to this role being realised. A reiteration of basic concepts is expressed in the introductory chapter while in the final chapter particular attention is given to the general problems of integrating systems concepts in research, extension and practice. The dialogue of these chapters is necessarily brief and in some respects speculative but it is supported by appropriate bibliography. The main body of the text is concerned with the methodology of systems research; the conception, construction, implementation, validation and exploitation of computer-based simulation models of agricultural systems.

Systems Analysis and Modeling in Food and Agriculture is a component of Encyclopedia of Food and Agricultural Sciences, Engineering and Technology Resources in the global Encyclopedia of Life Support Systems (EOLSS), which is an integrated compendium of twenty one Encyclopedias. Systems analysis and modeling is being used increasingly in understanding and solving problems in food and agriculture. The purpose of systems analysis is to support decisions by emphasizing the interactions of processes and components within a system. Frequently investigated systems level questions in agriculture and food are relevant to the 6 E's: Environment, Energy, Ecology, Economics, Education, and Efficiency. The theme on Systems Analysis and Modeling in Food and Agriculture with contributions from distinguished experts in the field provides information on key topics related to food and agricultural system. The coverage include an overview of food system; system level aspects related to energy, environment, and social/policy issues; knowledge bases and decision support; computer models for crops, food processing, water resources, and agricultural meteorology; collection and analysis methods for data from field experiments; use of models and information systems. This volume is aimed at the following a wide spectrum of audiences from the merely curious to those seeking in-depth knowledge: University and College students Educators, Professional practitioners, Research personnel and Policy analysts, managers, and decision makers and NGOs.

Offers a treatment of modern applications of modelling and simulation in crop, livestock, forage/livestock systems, and field operations. The book discusses methodologies from linear programming and neutral networks, to expert or decision support systems, as well as featuring models, such as SOYGRO, CROPGRO and GOSSYM/COMAX. It includes coverage on evaporation and evapotranspiration, the theory of simulation based on biological processes, and deficit irrigation scheduling.

This book provides a clear picture of the use of applied mathematics as a tool for improving the accuracy of agricultural research. For decades, statistics has been regarded as the fundamental tool of the scientific method. With new breakthroughs in computers and computer software, it has become feasible and necessary to improve the traditional approach in agricultural research by including additional mathematical modeling procedures. The difficulty with the use of mathematics for agricultural scientists is that most courses in applied mathematics have been designed for engineering students. This publication is written by a professional in animal science targeting professionals in the biological, namely agricultural and animal scientists and graduate students in agricultural and animal sciences. The only prerequisite for the reader to understand the topics of this book is an introduction to college algebra, calculus and statistics. This is a manual of procedures for the mathematical modeling of agricultural systems and for the design and analyses of experimental data and experimental tests. It is a step-by-step guide for mathematical modeling of agricultural systems, starting with the statement of the research problem and up to implementing the project and running system experiments.

The only book to present the synergy between modeling and simulation, systems engineering, and agent technologies expands the notion of agent-based simulation to also deal with agent simulation and agent-supported simulation. Accessible to both practitioners and managers, it systematically addresses designing and building agent systems from a systems engineering perspective.

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.

Agricultural systems are uniquely complex systems, given that agricultural systems are parts of natural and ecological systems. Those aspects bring in a substantial degree of uncertainty in system operation. Also, impact factors, such as weather factors, are critical in agricultural systems but these factors are uncontrollable in system management. Modern agriculture has been evolving through precision agriculture beginning in the late 1980s and biotechnological innovations in the early 2000s. Precision agriculture implements site-specific crop production management by integrating agricultural mechanization and information technology in geographic information system (GIS), global navigation satellite system (GNSS), and remote sensing. Now, precision agriculture is set to evolve into smart agriculture with advanced systematization, informatization, intelligence and automation. From precision agriculture to smart agriculture, there is a substantial amount of specific control and communication problems that have been investigated and will continue to be studied. In this book, the core ideas and methods from control problems in agricultural production systems are extracted, and a system view of agricultural production is formulated for the analysis and design of management strategies to control and optimize agricultural production systems while exploiting the intrinsic feedback information-exchanging mechanisms. On this basis, the theoretical framework of agricultural cybernetics is established to predict and control the behavior of agricultural production systems through control theory.