Membership function

About: Membership function is a research topic. Over the lifetime, 15795 publications have been published within this topic receiving 418366 citations.

Fuzzy logic applications to multisensor-multitarget correlation

Abstract: A consistent tactical picture requires data fusion technology to combine and propagate information received from diverse objects and usually vague situations. The information may be contained in two types of data; numerical data received from sensor measurements, and linguistic data obtained from human operators and domain experts. In real world situations, the numerical data may be noisy, inconsistent, and incomplete, and the linguistic information is imprecise and vague. To deal with these two types of data simultaneously, fuzzy sets and fuzzy logic provide a methodology to obtain an approximate but consistent tactical picture in a timely manner for very complex or ill-defined engineering problems. A functional paradigm for fuzzy data fusion is presented. It consists of four basic elements: (1) fuzzification of crisp elements, (2) fuzzy knowledge base derived from numerical input/output relations and humans, (3) fuzzy inference mechanism based on a class of fuzzy logic, (4) defuzzification of fuzzy outputs into crisp outputs for use by a plant. For real-time practical systems, the on-line determination of a fuzzy membership function from a given set of crisp inputs is vital. To this end, a methodology for estimating an optimal membership function from crisp input data has been implemented. This is based on the possibility/probability consistency principle as proposed by L.A. Zadeh. A relationship between the fuzzy membership function and the confidence level of statistical input data has been developed and it serves as a design parameter for fuzzification. This technique has been applied to a two-dimensional multisensor-multitarget tracking system. Fuzzy system performance evaluations have been presented. With simulated data in the laboratory environment, the simulation has been performed to evaluate the Mission Avionics Sensor Synergism (MASS) Systems. These results show better performance for the data correlation function using the fuzzy logic techniques.

The Theory of Fuzz Logic and its Application to Real Estate Valuation

Abstract: Fuzzy logic is based on the central idea that in fuzzy sets each element in the set can assume a value from 0 to 1, not just 0 or 1, as in classic set theory. Thus, qualitative characteristics and ...

An improved Dempster–Shafer approach to construction safety risk perception

Abstract: This paper proposes a novel hybrid approach that merges fuzzy matter element (FME), Monte Carlo (MC) simulation technique, and Dempster–Shafer (D–S) evidence theory to perceive the risk magnitude of tunnel-induced building damage at an early construction stage. The membership measurement in FME is used to construct basic probability assignments (BPAs) of influential factors within different risk states. An improved evidence fusion rule that integrates the Dempster’ rule and the weighted average rule is developed to synthesize multi-source conflicting evidence. A new defuzzification method, Centre of Distribution (COD), is proposed to achieve a crisp value that represents the final safety risk perception result. A confidence indicator, δ , is put forward to measure the reliability of the safety risk perception result. A comprehensive information fusion framework that incorporates 14 influential factors is proposed to perceive the risk magnitude of tunnel-induced building damage. Six existing buildings adjacent to the excavation of Wuhan Yangtze Metro Tunnel (WYMT), China, are utilized as a case study to verify the effectiveness and applicability of the proposed approach. Results indicate that the proposed approach is capable of (i) achieving a more accurate result for safety risk perception, and (ii) identifying global sensitivities of input factors throughout a series of MC simulation enabled iterations. A discussion on how to define a reasonable membership function for configuration of BPAs is further presented. The authors recommend that the constant coefficient λ that affects the shape of the defined correlation function in BPA (Basic Probability Assignment) constructs should have a value of three, and the risk perception result can thus reach up to the highest reliability level. This approach can enable a comprehensive preliminary safety risk perception during tunnel design phases, which can further substantially reduce the risk of building damage induced by tunneling excavation.