Journal of Intelligent & Fuzzy Systems - Volume 20, issue 6

Authors: Liu, Chin-Hung

Article Type: Research Article

Abstract: Quality function deployment (QFD) is a process for determining customer requirements and translating them into the target design. A rich understanding of the customer requirements is captured from a group of customers, while the relationship between customer requirements and technical measures is defined through the project team. Ordinarily, a group decision-making process is filled with fuzziness and lack of preciseness because of diverse and/or even subjective views. Apparently, the importance weight of each customer requirement and the relationship between customer requirements and technical measures are evaluated by a group of people with imprecision and fuzziness. Furthermore, different people tend …to reflect diverse risk-taking attitudes, such as optimistic, neutral, and conservative attitudes, in making decisions. Under the conditions, a fuzzy group decision-making model with risk-taking attitudes can be used in QFD to manage and resolve a group decision-making process when the information is ambiguous and vague. Besides, an example is presented as well as the algorithm steps to illustrate this fuzzy group decision-making model with risk-taking attitudes can be effectively applied in QFD including customer requirements at the two-level hierarchy to accurately and convincingly make decisions and determine the importance of each technical measure with various risk-taking attitudes of the decision-makers. Show more

Keywords: Quality function deployment, house of quality, risk-taking attitudes, fuzzy group decision-making, fuzzy suitability indices

DOI: 10.3233/IFS-2009-0429

Citation: Journal of Intelligent & Fuzzy Systems, vol. 20, no. 6, pp. 211-224, 2009

Authors: Burgin, M. | Duman, O.

Article Type: Research Article

Abstract: Approximately continuous functions were first introduced in connection with problems of differentiation and integration. The main idea of the approximate continuity of a function f is that the continuity conditions are true not necessarily everywhere but only almost everywhere with respect to some measure, e.g., Borel measure or Lebesgue measure. At the same time, it is known that functions that come from real life sources, such as measurement and computation, do not allow, in a general case, to test whether they are continuous or even approximately continuous in the strict mathematical sense. To overcome these limitations, fuzzy approximate continuity of …functions is introduced and studied in this paper. Show more

Keywords: Approximate continuity, fuzzy convergence, density, fuzzy approximate continuity, continuity defect

DOI: 10.3233/IFS-2009-0445

Citation: Journal of Intelligent & Fuzzy Systems, vol. 20, no. 6, pp. 225-233, 2009

Authors: Yakut, O. | Alli, H.

Article Type: Research Article

Abstract: In this study, neural based fuzzy sliding mode control algorithm is designed by putting advantageous specifications of sliding mode control and artificial intelligence techniques and applied to 8 storey sample building with active tendon. Performance of the designed controller is examined by applying acceleration data belonging to 6 earthquakes, each having different characteristics, as the external driving force. MATLAB software is used for numerical solutions, and the obtained results are compared in graphical form and presented in tables. Genetic algorithm is used for optimization process. Parametric uncertainities and time delay effects are considered. It is observed that performance of the …controller is quite high and control force can be used practically. The obtained results also show that the controller provides quite successful control under earthquake effects having different characteristics. Show more

Keywords: Seismic isolation, Fuzzy logic, Artificial neural networks, Moving sliding surface, Sliding-mode control, Genetic algorithm

DOI: 10.3233/IFS-2009-0444

Citation: Journal of Intelligent & Fuzzy Systems, vol. 20, no. 6, pp. 235-256, 2009