Fuzzy graphs: Algebraic structure and syntactic recognition

© Springer Science+Business Media Dordrecht 2013. Directed fuzzy hypergraphs are introduced as a generalization of both crisp directed hypergraphs and directed fuzzy graphs. It is proved that the set of all directed fuzzy hypergraphs can be structured into a magmoid with operations graph composition and disjoint union. In this framework a notion of syntactic recognition inside magmoids is defined. The corresponding class is proved to be closed under boolean operations and inverse mor-phisms of magmoids. Moreover, the language of all strongly connected fuzzy graphs and the language that consists of all fuzzy graphs that have at least one directed path from the begin node to the end node through edges with membership grade 1 are recognizable. Additionally, a useful characterization of recognizability through left derivatives is also achieved

Business network commons and their fragilities: Emerging configurations of local organizational fields

This study introduces the concept of business network commons as valuable, fragile resources that are available for partnering firms' collective use but that also require users' engagement and collaboration to be protected and/or (re)generated. Building on the theory of commons and the literature on self-organizing networks and organizational fields, this study identifies organizational variables that shape the network's local organizational field and play a relevant role in protecting and developing business network commons. These variables are participatory architecture, organizational integration, and the presence of specific mechanisms for opportunism prevention and resolution. The fsQCA analysis suggests that specific combinations of these three organizational variables at network level enable high firm performance through the development and protection of business network commons. The boundary conditions under which different network-level organizational configurations can equifinally lead to high firm-level performance depend on the different possible levels of fragility of the business network commons at stake

Entwicklung eines auf Fuzzy-Regeln basierten Expertensystems zur Hochwasservorhersage im mesoskaligen Einzugsgebiet des Oberen Mains

People worldwide are faced with flood events of different magnitudes. A timely and reliable flood forecast is essential for the people to save goods and, more important, lives. The development of a fuzzy rule based flood forecast system considering extreme flood events within meso-scale catchments and with return periods of 100 years and more is the main objective of this work. Considering one river catchment extreme flood events are usually seldom. However, these data are essential for a reliable setup of warning systems. In this work the database is extended by simulations of possible flood events performing the hydrological model WaSiM-ETH (Water balance Simulation model ETH) driven by generated precipitation fields. The therefore required calibration of the hydrological model is performed applying the genetic optimization algorithm SCE (Shuffled Complex Evolution). Thereby, different SCE configuration setups are investigated and an optimization strategy for the Upper Main basin is developed in order to ensure reliable und satisfying calibration results. In this thesis the developed forecast system comprises different time horizons (3 days; 6, 12, and 48 hours) in order to ensure a reliable and continuous flood forecast at the three main gauges of the Upper Main river. Thereby, the focus of the different fuzzy inference systems lies on different discharge conditions, which together ensure a continuous flood forecast. In this work the performance of the two classical fuzzy inference systems, Mamdani and Takagi-Sugeno, is investigated considering all four forecast horizons. Thereby, a wide variety of different input features, among others Tukey data depth, is taken into consideration. For the training of the fuzzy inference systems the SA (Simulated Annealing) optimization algorithm is applied. A further performance comparison is carried out considering the 48 hour forecast behaviour of the two fuzzy inference systems and the hydrological model WaSiM-ETH. In this work the expert system ExpHo-HORIX is developed in order to combine the single, trained fuzzy inference systems to one overall flood warning system. This expert system ensures beside the fast forecast a quantification of uncertainties within a manageable, user-friendly, and transparent framework which can be easily implemented into an exiting environment.Menschen weltweit werden mit Hochwasserereignissen unterschiedlicher Stärke konfrontiert. Um Eigentum und, noch viel wichtiger, Leben zu retten, ist eine rechtzeitige und zuverlässige Hochwasserwarnung und folglich -vorhersage unerlässlich. Ziel dieser Arbeit ist es deshalb, ein auf Fuzzy-Regeln basiertes Hochwasserwarnsystem für mesoskalige Einzugsgebiete und die Vorhersage von extremen Hochwasserereignissen mit Wiederkehrperioden von 100 Jahren und mehr unter Berücksichtigung von Unsicherheiten zu entwickeln. Da extreme Hochwasserereignisse mit einer Jährlichkeit von 100 oder mehr Jahren in der Realität nicht in jedem Einzugsgebiet bereits beobachtet und aufgezeichnet wurden, ist eine Erweiterung der Datenbank auf Grund von Modellsimulationen zwingend notwendig. In dieser Arbeit werden hierzu das hydrologische Modell WaSiM-ETH (Wasserhaushalts-Simulations-Modell ETH) sowie von Bliefernicht et al. (2008) generierte Niederschlagsfelder verwendet. Die Kalibrierung des Modells erfolgt mit dem SCE (Shuffled Complex Evolution) Optimierungsalgorithmus. Um reproduzierbare Kalibrierungsergebnisse zu erzielen und die notwendige Kalibrierungszeit möglichst gering zu halten, werden unterschiedliche Optimierungskonfigurationen untersucht und eine Kalibrierungsstrategie für das mesoskalige Einzugsgebiet des Oberen Mains entwickelt. Um eine kontinuierliche und zuverlässige Vorhersage zu garantieren, ist die Idee entwickelt worden, Fuzzy-Regelsysteme für unterschiedliche Vorhersagehorizonte (3 Tage; 6, 12 und 48 Stunden) für die drei Hauptpegel des Oberen Mains aufzustellen, die im Zusammenspiel eine kontinuierliche Vorhersage sicher stellen. Der Fokus der 3-Tagesvorhersage liegt hierbei in der zuverlässigen Wiedergabe von geringen und mittleren Abflussbedingungen sowie der zuverlässigen und rechtzeitigen Vorhersage von Überschreitungen einer vordefinierten Meldestufe. Eine vorhergesagte Überschreitung der Meldestufe führt zu einem Wechsel der Vorhersagesysteme von der 3-Tages- zu der 6-, 12- und 48-Stundenvorhersage, deren Fokus auf der Vorhersage der Hochwasserganglinie liegt. In diesem Zusammenhang wird die Effizienz der beiden klassischen Regelsysteme,Mamdani und Takagi-Sugeno, sowie die Kombination unterschiedlicher Eingangsgrößen, unter anderem Tukey Tiefenfunktion, näher untersucht. Ein weiterer Effizienzvergleich wird zwischen den Mamdani Regelsystemen der 48-Stundenvorhersage und dem hydrologischen ModellWaSiM-ETH durchgeführt. Für das Training der beiden Regelsysteme wird der SA (Simulated Annealing) Optimierungsalgorithmus verwendet. Die einzelnen Fuzzy-Regelsysteme werden schließlich in dem entwickelten Hochwasserwarnsystem ExpHo-HORIX (Expertensystem Hochwasser - HORIX) zusammengefügt. Standardmäßig wird für jede Vorhersage die Niederschlagsunsicherheit auf Grund von Ensemble-Vorhersagen innerhalb ExpHo-HORIX analysiert und ausgewiesen. Im Hochwasserfall können für die stündlichen Fuzzy-RegelsystemeModellunsicherheiten des hydrologischenModells, das für die Generierung der Datenbank von Extremereignissen verwendet wurde, zusätzlich ausgewiesen werden. Hierzu müssen zusätzlich Ergebnisse der SCEM Analyse (Grundmann, 2009) vorliegen

Supply chain risk analysis

A new decision support system is proposed and developed that will help sustaining business in a high-risk business environment. The system is developed as a web application to better integrate the supply chain entities and to provide a common platform for performing risk analysis in a supply chain. The system performs a risk analysis and calculates risk factor with each activity in the supply considering its interrelationship with other activities. Bayesian networks along with fault tree structures are embedded in the system and logical rules are used to perform a qualitative fault tree analysis, as the data required to calculate the frequency of occurrence is rarely available. The developed system guides the risk assessment process: from asset identification to consequence analysis before estimating the risk factor associated with each activity in the supply chain. The system is tested with a sample case study on a highly explosive product. Results show that the system is capable of identifying high-risk threats. The system further needs to be developed to add a safeguard analysis module and to enable automatic data extraction from the enterprise resource planning and legacy databases. It is expected that the system on complete development and induction will help supply chain managers to manage business risks and operations more efficiently and effectively by providing a complete picture of the risk environment and safeguards required to reduce the risk level

Particle swarm optimization in multi-agents cooperation applications

Master'sMASTER OF ENGINEERIN

Fuzzy Logic

The capability of Fuzzy Logic in the development of emerging technologies is introduced in this book. The book consists of sixteen chapters showing various applications in the field of Bioinformatics, Health, Security, Communications, Transportations, Financial Management, Energy and Environment Systems. This book is a major reference source for all those concerned with applied intelligent systems. The intended readers are researchers, engineers, medical practitioners, and graduate students interested in fuzzy logic systems

Different models of automata with fuzzy states

In this paper we provide a general definition of automata with fuzzy stateswhich includes as its special cases automata used by Lin et al. [29], Liu and Qiu [30,31,42]and Xing et al. [56] in the study of fuzzy discrete event systems, as well as various typesof automata constructed in [14,15,18,32] for the purpose of the determinization of fuzzyautomata. We explain the relationships between these differentmodels of automata withfuzzy states and showthat every crisp-deterministic fuzzy automaton can be transformedinto a language-equivalent automaton with fuzzy states, and vice versa