Издательство InTech, 2010, -352 pp.
As the quote above states, be willing to make decisions. This book by In-Tech publishing helps the reader understand the power of informed decision making by covering a broad range of DSS (Decision Support Systems) applications in the fields of medical, environmental, transport and business. The expertise of the chapter writers spans an equally extensive spectrum of researchers from around the globe including universities in Canada, Mexico, Brazil and the United States, to institutes and universities in Italy, Germany, Poland, France, United Kingdom, Romania, Turkey and Ireland to as far east as Malaysia and Singapore and as far north as Finland.
Decision Support Systems are not a new technology but they have evolved and developed with the ever demanding necessity to analyse a large number of options for decision makers (DM) for specific situations, where there is an increasing level of uncertainty about the problem at hand and where there is a high impact relative to the correct decisions to be made. DSS’s offer decision makers a more stable solution to solving the semi-structured and unstructured problem. This is exactly what the reader will see in this book.
As I read through the chapters it is soon evident that this book provides a wide resource of applications as to how one can design, develop and implement a DSS in the areas such as environmental science and engineering looking at such applications from determining spatial risk zones of the Popocatepetl volcano in Mexico, to developing a web based DSS to manage the growing of wheat crops for a less intensive and more sustainable method of farming in Italy. Other chapters include an ecohydrological and morphological DSS used in the North Rhine Westphalia (NRW) in Germany to help adhere to the EU Water Framework Directive. An online DSS to look and predict the hydrodynamic and water quality in Lake Constance in the Bodensee region in Germany is also presented.
A medical DSS developed in Poland and the USA describes the advances in computer based medical systems to improve the initial patient diagnosis and subsequent therapy to eliminate potential human error. A similar application in Germany looks at the tools of artificial intelligence (A.I.) in medicine to again, assist in the decision making of symptoms, tests disease and eventual treatment options. Chapters 8 and 10 discuss other medical DSS’s. The transport sector is also addressed in Turkey by looking into the vehicle routing problem (VRP) conceing the pick-up and distribution of goods through a mathematical and algorithimic programming approach - Vehicle Routing Problems with Pick-Up and Delivery (VRPPD). A similar typed application was developed in Ireland for optimally determining articulated trucking routes based on distance and cost per kilometre. Decision support for truck route modelling (D-TRM). Chapter 12 looks at the ever popular location selection problem, but this time using a fuzzy logic function deployment method developed in both Iran and Canada.
Tools for the business sector include developing a virtual collaborative decision environment (VCDE) in chapter 14 to simulate decision making regarding a virtual company. In Malaysia, a new era of Active or Intelligent DSS (iDSS) assists managers with intelligent techniques for the operations of HR management.
A Web-based Decision Support System for Managing Durum Wheat Crops
Development of an Open Source GIS Based Decision Support System for Locating Wind Farms in Wallonia (Southe Belgium)
Forecasting Rubber Production using Intelligent Time Series Analysis to Support Decision Makers
Fuzzy Spatial Data Warehouse: A Multidimensional Model
Rule-Based System for Morphological and Ecohydrological Decision Making
The Decision Support System BodenseeOnline for Hydrodynamics and Water Quality in Lake Constance
Action Rules Approach to Solving Diagnostic Problems in Clinical Medicine
Assessing the Possibility of Identifying Precancerous Cervical Lesions using Aceto-White Temporal Pattes
Clinical Decision Support with Guidelines and Bayesian Networks
Computerized Interpretation of Cardiovascular Physiological Signals
Decision Support System for Truck Route Modelling (D – TRM)
A Proposed Decision Support System for Location Selection using Fuzzy Quality Function Deployment
Simultaneous Pick-up and Delivery Decision Support Systems
Decision Mining and Modeling in a Virtual Collaborative Decision Environment
Decision Support Using Simulation for Customer-Driven Manufacturing System Design and Operations Planning
Intelligent Techniques for Decision Support System in Human Resource Management
Flexible Dialogues in Decision Support Systems
iWDSS-Tender: Intelligent Web-based Decision Support System for Tender Evaluation
Towards an Optimal Decision Support System
A Silvicultural Decision Support System to Compare Forest Management Scenarios for Larch Stands on a lticriteria Basis.
As the quote above states, be willing to make decisions. This book by In-Tech publishing helps the reader understand the power of informed decision making by covering a broad range of DSS (Decision Support Systems) applications in the fields of medical, environmental, transport and business. The expertise of the chapter writers spans an equally extensive spectrum of researchers from around the globe including universities in Canada, Mexico, Brazil and the United States, to institutes and universities in Italy, Germany, Poland, France, United Kingdom, Romania, Turkey and Ireland to as far east as Malaysia and Singapore and as far north as Finland.
Decision Support Systems are not a new technology but they have evolved and developed with the ever demanding necessity to analyse a large number of options for decision makers (DM) for specific situations, where there is an increasing level of uncertainty about the problem at hand and where there is a high impact relative to the correct decisions to be made. DSS’s offer decision makers a more stable solution to solving the semi-structured and unstructured problem. This is exactly what the reader will see in this book.
As I read through the chapters it is soon evident that this book provides a wide resource of applications as to how one can design, develop and implement a DSS in the areas such as environmental science and engineering looking at such applications from determining spatial risk zones of the Popocatepetl volcano in Mexico, to developing a web based DSS to manage the growing of wheat crops for a less intensive and more sustainable method of farming in Italy. Other chapters include an ecohydrological and morphological DSS used in the North Rhine Westphalia (NRW) in Germany to help adhere to the EU Water Framework Directive. An online DSS to look and predict the hydrodynamic and water quality in Lake Constance in the Bodensee region in Germany is also presented.
A medical DSS developed in Poland and the USA describes the advances in computer based medical systems to improve the initial patient diagnosis and subsequent therapy to eliminate potential human error. A similar application in Germany looks at the tools of artificial intelligence (A.I.) in medicine to again, assist in the decision making of symptoms, tests disease and eventual treatment options. Chapters 8 and 10 discuss other medical DSS’s. The transport sector is also addressed in Turkey by looking into the vehicle routing problem (VRP) conceing the pick-up and distribution of goods through a mathematical and algorithimic programming approach - Vehicle Routing Problems with Pick-Up and Delivery (VRPPD). A similar typed application was developed in Ireland for optimally determining articulated trucking routes based on distance and cost per kilometre. Decision support for truck route modelling (D-TRM). Chapter 12 looks at the ever popular location selection problem, but this time using a fuzzy logic function deployment method developed in both Iran and Canada.
Tools for the business sector include developing a virtual collaborative decision environment (VCDE) in chapter 14 to simulate decision making regarding a virtual company. In Malaysia, a new era of Active or Intelligent DSS (iDSS) assists managers with intelligent techniques for the operations of HR management.
A Web-based Decision Support System for Managing Durum Wheat Crops
Development of an Open Source GIS Based Decision Support System for Locating Wind Farms in Wallonia (Southe Belgium)
Forecasting Rubber Production using Intelligent Time Series Analysis to Support Decision Makers
Fuzzy Spatial Data Warehouse: A Multidimensional Model
Rule-Based System for Morphological and Ecohydrological Decision Making
The Decision Support System BodenseeOnline for Hydrodynamics and Water Quality in Lake Constance
Action Rules Approach to Solving Diagnostic Problems in Clinical Medicine
Assessing the Possibility of Identifying Precancerous Cervical Lesions using Aceto-White Temporal Pattes
Clinical Decision Support with Guidelines and Bayesian Networks
Computerized Interpretation of Cardiovascular Physiological Signals
Decision Support System for Truck Route Modelling (D – TRM)
A Proposed Decision Support System for Location Selection using Fuzzy Quality Function Deployment
Simultaneous Pick-up and Delivery Decision Support Systems
Decision Mining and Modeling in a Virtual Collaborative Decision Environment
Decision Support Using Simulation for Customer-Driven Manufacturing System Design and Operations Planning
Intelligent Techniques for Decision Support System in Human Resource Management
Flexible Dialogues in Decision Support Systems
iWDSS-Tender: Intelligent Web-based Decision Support System for Tender Evaluation
Towards an Optimal Decision Support System
A Silvicultural Decision Support System to Compare Forest Management Scenarios for Larch Stands on a lticriteria Basis.