Self-organizing linear output map (SOLO): An artificial neural network suitable for hydrologic modeling and analysis

Artificial neural networks (ANNs) can be useful in the prediction of hydrologic variables, such as streamflow, particularly when the underlying processes have complex nonlinear interrelationships. However, conventional ANN structures suffer from network training issues that significantly limit their widespread application. This paper presents a multivariate ANN procedure entitled self-organizing linear output map (SOLO), whose structure has been designed for rapid, precise, and inexpensive estimation of network structure/parameters and system outputs. More important, SOLO provides features that facilitate insight into the underlying processes, thereby extending its usefulness beyond forecast applications as a tool for scientific investigations. These characteristics are demonstrated using a classic rainfall-runoff forecasting problem. Various aspects of model performance are evaluated in comparison with other commonly used modeling approaches, including multilayer feedforward ANNs, linear time series modeling, and conceptual rainfall-runoff modeling

Graphic Thinking and Digital Processes: Three Built Case Studies of Digital Materiality

Think strategic link between computer programming; digital modeling; the data; matter and CNC manufacturing in the various stages of the architectural project is key to update our discipline with new technologies. Our proposal to articulate and digital graphic thought processes; developable folded geometries and compositions is rooted in an expanded graphic thinking through multiple conceptual tools that are already part of the operational structure of our discipline

Four facets of a process modeling facilitator

Business process modeling as a practice and research field has received great attention in recent years. However, while related artifacts such as models, tools or grammars have substantially matured, comparatively little is known about the activities that are conducted as part of the actual act of process modeling. Especially the key role of the modeling facilitator has not been researched to date. In this paper, we propose a new theory-grounded, conceptual framework describing four facets (the driving engineer, the driving artist, the catalyzing engineer, and the catalyzing artist) that can be used by a facilitator. These facets with behavioral styles have been empirically explored via in-depth interviews and additional questionnaires with experienced process analysts. We develop a proposal for an emerging theory for describing, investigating, and explaining different behaviors associated with Business Process Modeling Facilitation. This theory is an important sensitizing vehicle for examining processes and outcomes from process modeling endeavors

Stakeholder Experiences with Conceptual Modeling: An Empirical Investigation

During the design of an information system, a significant task that is sometimes undertaken is conceptual modeling. It involves designers building a representation called a conceptual schema that captures application domain features to be included in the information system. For five reasons, conceptual modeling has become increasingly important: (1) conceptual schemas help clarify different assumptions that stakeholders hold about the domain being modeled; (2) integrating conceptual schemas is critical to organizations effectively re-engineering their business processes; (3) the quality of conceptual schemas affects the quality of database schemas that can be generated automatically; (4) the quality of conceptual schemas affects the usability of databases; and (5) stakeholders working with distributed, heterogeneous databases cannot effectively transcend boundaries without high-quality conceptual schemas. While researchers have expended substantial effort on developing conceptual modeling methodologies, little empirical work has been done on stakeholder experiences with conceptual modeling. The meager results obtained suggest that organizations have found few benefits from conceptual modeling and that often it has fallen into disuse. Laboratory work indicates, however, that improved design outcomes occur when conceptual modeling is undertaken. For two reasons, we expect that stakeholders will experience problems with using conceptual modeling in practice. First, we believe that many designers approach conceptual modeling with a functionalist view of the world. We believe that a social relativist view more accurately describes how stakeholders conceive the world. Second, many conceptual modeling tools provide only incomplete representations of the application domain to be modeled. We are currently undertaking case-study research to document the conceptual modeling practices engaged in by a large public-sector organization. We are also seeking to identify the problems that stakeholders experi- ence when they participate in conceptual modeling exercises. Our goal is to provide a taxonomy of problems that the stakeholders face and ultimately to develop theory to account for why these problems occur

Business Process Innovation using the Process Innovation Laboratory

Most organizations today are required not only to establish effective business processes but they are required to accommodate for changing business conditions at an increasing rate. Many business processes extend beyond the boundary of the enterprise into the supply chain and the information infrastructure therefore is critical. Today nearly every business relies on their Enterprise System (ES) for process integration and the future generations of enterprise systems will increasingly be driven by business process models. Consequently process modeling and improvement will become vital for business process innovation (BPI) in future organizations. There is a significant body of knowledge on various aspect of process innovation, e.g. on conceptual modeling, business processes, supply chains and enterprise systems. Still an overall comprehensive and consistent theoretical framework with guidelines for practical applications has not been identified. The aim of this paper is to establish a conceptual framework for business process innovation in the supply chain based on advanced enterprise systems. The main approach to business process innovation in this context is to create a new methodology for exploring process models and patterns of applications. The paper thus presents a new concept for business process innovation called the process innovation laboratory a.k.a. the Ð-Lab. The Ð-Lab is a comprehensive framework for BPI using advanced enterprise systems. The Ð-Lab is a collaborative workspace for experimenting with process models and an explorative approach to study integrated modeling in a controlled environment. The Ð-Lab facilitates innovation by using an integrated action learning approach to process modeling including contemporary technological, organizational and business perspectivesNo; keywords

A browser-based modeling tool for studying the learning of conceptual modeling based on a multi-modal data collection approach

How do we learn conceptual modeling? What are common learning difficulties? Which tool support assists learners in what respect? The paper at hand reports on the design and development of a browser-based modeling tool integrated with a learning observatory in support of learning conceptual modeling and of studying the learning of conceptual modeling. Implementing a multimodal data collection approach, the learning observatory tracks learner-tool interactions, records verbal data from learners and surveys learners about their learning processes to provide for analyses at the individual and aggregate learner levels in the quest for identifying patterns of learning processes, learning barriers and difficulties. We report on the current state of prototype development, discuss its software architecture and outline future development steps

Modeling Concept Combinations in a Quantum-theoretic Framework

We present modeling for conceptual combinations which uses the mathematical formalism of quantum theory. Our model faithfully describes a large amount of experimental data collected by different scholars on concept conjunctions and disjunctions. Furthermore, our approach sheds a new light on long standing drawbacks connected with vagueness, or fuzziness, of concepts, and puts forward a completely novel possible solution to the 'combination problem' in concept theory. Additionally, we introduce an explanation for the occurrence of quantum structures in the mechanisms and dynamics of concepts and, more generally, in cognitive and decision processes, according to which human thought is a well structured superposition of a 'logical thought' and a 'conceptual thought', and the latter usually prevails over the former, at variance with some widespread beliefsComment: 5 pages. arXiv admin note: substantial text overlap with arXiv:1311.605

A Conceptual Framework for Integration Development of GSFLOW Model: Concerns and Issues Identified and Addressed for Model Development Efficiency

In Coupled Groundwater and Surface-Water Flow (GSFLOW) model, the three-dimensional finite-difference groundwater model (MODFLOW) plays a critical role of groundwater flow simulation, together with which the Precipitation-Runoff Modeling System (PRMS) simulates the surface hydrologic processes. While the model development of each individual PRMS and MODFLOW model requires tremendous time and efforts, further integration development of these two models exerts additional concerns and issues due to different simulation realm, data communication, and computation algorithms. To address these concerns and issues in GSFLOW, the present paper proposes a conceptual framework from perspectives of: Model Conceptualization, Data Linkages and Transference, Model Calibration, and Sensitivity Analysis. As a demonstration, a MODFLOW groundwater flow system was developed and coupled with the PRMS model in the Lehman Creek watershed, eastern Nevada, resulting in a smooth and efficient integration as the hydrogeologic features were well captured and represented. The proposed conceptual integration framework with techniques and concerns identified substantially improves GSFLOW model development efficiency and help better model result interpretations. This may also find applications in other integrated hydrologic modelings