@article{TakagiTaniKawamura2004,
  author    = {Takagi, Kousuke and Tani, Akinori and Kawamura, Hiroshi},
  title     = {Research on Intelligent Fuzzy Optimal Active and Hybrid Control Systems of Building Structures - Verification of Optimization Method on Switching Rules of Control Forces},
  doi       = {10.25643/bauhaus-universitaet.223},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20111215-2238},
  year      = {2004},
  abstract  = {Recently, many reseraches on active control systems of building structures are preformed based on modern control theory and are installed real buildings. The authors have already proposed intelligent fuzzy optimal active control (IFOAC) systems. IFOAC systems imitate intelligent activities of human brains such as prediction, adaptation, decision-kaking and so on. In IFOAC systems, objective and subjective judgements on the active control can be taken into account. However, IFOAC systems are considered to be suitable for far-field erathquake and control effect becomes small in case of near-field earthqaukes which include a few velosity pules with large amplitudes. To improve control effect in case of near-souece earthquakes, the authors have also proposed hybrid control (HC) systems, in which IFOAC systems and fuzzy control system are combined. In HC systems, the fuzzy control systems are introduced as a reflective fuzzy active control (RFAC) system and imitates spinal reflection of human. In HC systems, active control forces are activated to buildings in accordance with switching rules on active control forces. In this paper, optimizations on fuzzy control rules in RFAC system and switching rules of active control forces in HC system are performed by Parameter-Free Genetic Algorithms (PfGAs). Here, the optimization is performed by using different earthquake inputs. The results of digital simulations show that the HC system can reduce maximal response displacements under restrictions on strokes of the actuator effectively in case of a near-source earthquake and the effectiveness of the proposed HC system is discussed and clarified.},
  subject      = {Mehragentensystem},
  language  = {en}
}
@article{MoellerBeerGrafetal.1997,
  author    = {M{\"o}ller, B. and Beer, M. and Graf, W. and Hoffmann, Alfred},
  title     = {Sicherheitsbeurteilung von Tragwerken mit Fuzzy-Modellen},
  doi       = {10.25643/bauhaus-universitaet.462},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20111215-4625},
  year      = {1997},
  abstract  = {Die Sicherheit von Tragwerken h{\"a}ngt von der zuverl{\"a}ssigen Modellierung s{\"a}mtlicher Tragwerksparameter ab. {\"U}blicherweise werden diese Parameter als deterministische oder stochastische Gr{\"o}ßen beschrieben. Stochastische Gr{\"o}ßen sind Zufallsgr{\"o}ßen, die unscharfe Informationen {\"u}ber Tragwerksparameter mit Hilfe von Dichtefunktionen erfassen. Nicht alle unscharfen Tragwerksparameter lassen sich als Zufallsgr{\"o}ßen darstellen. Sie k{\"o}nnen jedoch als Fuzzy-Gr{\"o}ßen modelliert werden. Fuzzy-Gr{\"o}ßen beschreiben unscharfe Tragwerksparameter als unscharfe Menge mit Bewertungsfunktion (Zugeh{\"o}rigkeitsfunktion). Die Fuzzy-Modellierung im Bauingenieurwesen umfaßt die Fuzzifizierung, die Fuzzy-Analyse, die Defuzzifizierung und die Sicherheitsbeurteilung. Sie erlaubt es, Tragwerke mit nicht-stochastischen unscharfen Eingangsinformationen zu untersuchen. Nicht-stochastische Eingangsinformationen treten sowohl bei bestehenden als auch bei neuen Tragwerken auf. Die unscharfen Ergebnisse der Fuzzy-Modellierung gestatten es, das Systemverhalten zutreffender zu beurteilen; sie sind die Ausgangspunkte f{\"u}r eine neue Sicherheitsbeurteilung auf der Grundlage der M{\"o}glichkeitstheorie. Bei der Fuzzy-Analyse ist die alpha-Diskretisierung vorteilhaft einsetzbar. Bei fehlender Monotonie der deterministischen Berechnungen und unter Ber{\"u}cksichtigung der Nichtlinearit{\"a}t wird die Fuzzy-Analyse mit Optimierungsalgorithmen durchgef{\"u}hrt. Zwei Beispiele werden diskutiert: die L{\"o}sung eines transzendenten Eigenwertproblems und eines linearen Gleichungssystems. Die Systemantworten der Fuzzy-Analyse werden der Sicherheitsbeurteilung zugrunde gelegt. F{\"u}r ausgew{\"a}hlte physikalische Gr{\"o}ßen werden Versagensfunktionen definiert. Diese bewerten die M{\"o}glichkeit des Versagens. Mit Hilfe von Min-max-Operationen der Fuzzy-Set-Theorie erh{\"a}lt man aus Versagensfunktion und Fuzzy-Antwort die Versagensm{\"o}glichkeit bzw. die {\"U}berlebensm{\"o}glichkeit. Die ermittelte Versagensm{\"o}glichkeit repr{\"a}sentiert die subjektive Beurteilung der M{\"o}glichkeit, daß das Ereignis \&qout;Versagen\&qout; eintritt. Beispiele zeigen die Unterschiede zwischen der Sicherheitsbeurteilung mittels Fuzzy-Modells und mittels deterministischen Modells.},
  subject      = {Tragwerk},
  language  = {de}
}
@article{MotawaAnumbaElHamalawi2004,
  author    = {Motawa, Ibrahim and Anumba, Chimay and El-Hamalawi, A.},
  title     = {Development of a Fuzzy System for Change Prediction in Construction Projects},
  doi       = {10.25643/bauhaus-universitaet.218},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20111215-2180},
  year      = {2004},
  abstract  = {Change management has been the focus of different IT systems. These IT systems were developed to represent design information, record design rationale, facilitate design coordination and changes. They are largely based on managing reactive changes, particularly design changes, in which changes are recorded and then propagated to the relevant project members. However, proactive changes are hardly dealt with in IT systems. Proactive changes require estimating the likelihood of occurrence of a change event as well as estimating the degree of change impacts on project parameters. Changes in construction projects often result from the uncertainty associated with the imprecise and vague knowledge of much project information at the early stages of projects. This is a major outcome of the case studies carried out as part of this research. Therefore, the proposed model considers that incomplete knowledge and certain project characteristics are always behind change causes. For proactive changes, predicting a change event is the main task for modelling. The prediction model should strive to integrate these main elements: 1) project characteristics that lead to change 2) causes of change, 3) the likelihood of change occurrence, and 4) the change consequences. It should also define the dependency relationships between these elements. However, limited data (documented) are only available from previous projects for change cases and many of the above elements can only be expressed in linguistic terms. This means that the model will simulate the uncertainty and subjectivity associated with these sets of elements. Therefore, a fuzzy model is proposed in this research to capture these elements. The model analyses the impact of each set of elements on the other by assigning fuzzy values for these elements that express the uncertainty and subjectivity of their impact. The main aim is to predict change events and evaluate change effects on project parameters. The fuzzy model described above was developed in an IT system for operational purposes and was designed as a Java package of components with their supporting classes, beans, and files. This paper describes the development and the architecture of the proposed IT system to achieve these requirements. The system is intended to help project teams in dealing with change causes and then the change consequences in construction projects.},
  subject      = {Mehragentensystem},
  language  = {en}
}
@article{MosaviQasemShokrietal.,
  author    = {Mosavi, Amir Hosein and Qasem, Sultan Noman and Shokri, Manouchehr and Band, Shahab S. and Mohammadzadeh, Ardashir},
  title     = {Fractional-Order Fuzzy Control Approach for Photovoltaic/Battery Systems under Unknown Dynamics, Variable Irradiation and Temperature},
  series = {Electronics},
  volume    = {2020},
  journal   = {Electronics},
  number    = {Volume 9, issue 9, article 1455},
  publisher = {MDPI},
  address   = {Basel},
  doi       = {10.3390/electronics9091455},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20210122-43381},
  pages     = {1 -- 19},
  abstract  = {For this paper, the problem of energy/voltage management in photovoltaic (PV)/battery systems was studied, and a new fractional-order control system on basis of type-3 (T3) fuzzy logic systems (FLSs) was developed. New fractional-order learning rules are derived for tuning of T3-FLSs such that the stability is ensured. In addition, using fractional-order calculus, the robustness was studied versus dynamic uncertainties, perturbation of irradiation, and temperature and abruptly faults in output loads, and, subsequently, new compensators were proposed. In several examinations under difficult operation conditions, such as random temperature, variable irradiation, and abrupt changes in output load, the capability of the schemed controller was verified. In addition, in comparison with other methods, such as proportional-derivative-integral (PID), sliding mode controller (SMC), passivity-based control systems (PBC), and linear quadratic regulator (LQR), the superiority of the suggested method was demonstrated.},
  subject      = {Fuzzy-Logik},
  language  = {en}
}
@article{HarirchianLahmer,
  author    = {Harirchian, Ehsan and Lahmer, Tom},
  title     = {Improved Rapid Visual Earthquake Hazard Safety Evaluation of Existing Buildings Using a Type-2 Fuzzy Logic Model},
  series = {Applied Sciences},
  volume    = {2020},
  journal   = {Applied Sciences},
  number    = {Volume 10, Issue 3, 2375},
  publisher = {MDPI},
  address   = {Basel},
  doi       = {10.3390/app10072375},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20200331-41161},
  pages     = {14},
  abstract  = {Rapid Visual Screening (RVS) is a procedure that estimates structural scores for buildings and prioritizes their retrofit and upgrade requirements. Despite the speed and simplicity of RVS, many of the collected parameters are non-commensurable and include subjectivity due to visual observations. This might cause uncertainties in the evaluation, which emphasizes the use of a fuzzy-based method. This study aims to propose a novel RVS methodology based on the interval type-2 fuzzy logic system (IT2FLS) to set the priority of vulnerable building to undergo detailed assessment while covering uncertainties and minimizing their effects during evaluation. The proposed method estimates the vulnerability of a building, in terms of Damage Index, considering the number of stories, age of building, plan irregularity, vertical irregularity, building quality, and peak ground velocity, as inputs with a single output variable. Applicability of the proposed method has been investigated using a post-earthquake damage database of reinforced concrete buildings from the Bing{\"o}l and D{\"u}zce earthquakes in Turkey.},
  subject      = {Fuzzy-Logik},
  language  = {en}
}