Decision support system for the long-term city metabolism planning problem

A Decision Support System (DSS) tool for the assessment of intervention strategies (Alternatives) in an Urban Water System (UWS) with an integral simulation model called “WaterMet²” is presented. The DSS permits the user to identify one or more optimal Alternatives over a fixed long-term planning horizon using performance metrics mapped to the TRUST sustainability criteria (Alegre et al., 2012). The DSS exposes lists of in-built intervention options and system performance metrics for the user to compose new Alternatives. The quantitative metrics are calculated by the WaterMet² model and further qualitative or user-defined metrics may be specified by the user or by external tools feeding into the DSS. A Multi-Criteria Decision Analysis (MCDA) approach is employed within the DSS to compare the defined Alternatives and to rank them with respect to a pre-specified weighting scheme for different Scenarios. Two rich, interactive Graphical User Interfaces, one desktop and one web-based, are employed to assist with guiding the end user through the stages of defining the problem, evaluating and ranking Alternatives. This mechanism provides a useful tool for decision makers to compare different strategies for the planning of UWS with respect to multiple Scenarios. The efficacy of the DSS is demonstrated on a northern European case study inspired by a real-life urban water system for a mixture of quantitative and qualitative criteria. The results demonstrate how the DSS, integrated with an UWS modelling approach, can be used to assist planners in meeting their long-term, strategic level sustainability objectives

Deterministic-statistical model coupling in a DSS for river-basin management

This paper presents a method for appropriate coupling of deterministic and statistical models. In the decision-support system for the Elbe river, a conceptual rainfall-runoff model is used to obtain the discharge statistics and corresponding average number of flood days, which is a key input variable for a rule-based model for floodplain vegetation. The required quality of the discharge time series cannot be determined by a sensitivity analysis because a deterministic model is linked to a statistical model. To solve the problem, artificial discharge time series are generated that mimic the hypothetical output of rainfall-runoff models of different accuracy. The results indicate that a feasible calibration of the rainfall-runoff model is sufficient to obtain consistency with the vegetation model in view of its sensitivity to changes in the number of flood days in the floodplains

Integration of decision support systems to improve decision support performance

Decision support system (DSS) is a well-established research and development area. Traditional isolated, stand-alone DSS has been recently facing new challenges. In order to improve the performance of DSS to meet the challenges, research has been actively carried out to develop integrated decision support systems (IDSS). This paper reviews the current research efforts with regard to the development of IDSS. The focus of the paper is on the integration aspect for IDSS through multiple perspectives, and the technologies that support this integration. More than 100 papers and software systems are discussed. Current research efforts and the development status of IDSS are explained, compared and classified. In addition, future trends and challenges in integration are outlined. The paper concludes that by addressing integration, better support will be provided to decision makers, with the expectation of both better decisions and improved decision making processes

Integrating Knowledge for River Basin Management: Progress in Thailand

Resource /Energy Economics and Policy,

Evolutionary Robotics: a new scientific tool for studying cognition

We survey developments in Artificial Neural Networks, in Behaviour-based Robotics and Evolutionary Algorithms that set the stage for Evolutionary Robotics in the 1990s. We examine the motivations for using ER as a scientific tool for studying minimal models of cognition, with the advantage of being capable of generating integrated sensorimotor systems with minimal (or controllable) prejudices. These systems must act as a whole in close coupling with their environments which is an essential aspect of real cognition that is often either bypassed or modelled poorly in other disciplines. We demonstrate with three example studies: homeostasis under visual inversion; the origins of learning; and the ontogenetic acquisition of entrainment

Recruitment and selection processes through an effective GDSS

[[abstract]]This study proposes a group decision support system (GDSS), with multiple criteria to assist in recruitment and selection (R&S) processes of human resources. A two-phase decision-making procedure is first suggested; various techniques involving multiple criteria and group participation are then defined corresponding to each step in the procedure. A wide scope of personnel characteristics is evaluated, and the concept of consensus is enhanced. The procedure recommended herein is expected to be more effective than traditional approaches. In addition, the procedure is implemented on a network-based PC system with web interfaces to support the R&S activities. In the final stage, key personnel at a human resources department of a chemical company in southern Taiwan authenticated the feasibility of the illustrated example.[[notice]]補正完畢[[journaltype]]國內[[incitationindex]]SCI[[incitationindex]]E