Sentence examples for fuzzy influence from inspiring English sources

The former type will necessarily have an impact on gene regulation, as it will always result in a change the co-transcribed gene sets, whereas the second one may have a more fuzzy influence on gene transcription (e.g., the accessibility of the transcription machinery to the TU may change), without necessarily altering gene regulation (e.g., conserving the same promoter).

On other hand FTOPSIS enables decision maker to grasp the fuzzy logic influence of one critera over other.

For discrete-time T-S fuzzy system influenced by sensor faults and unknown disturbances, an (H_/H_{infty}) robust fault-detection observer was proposed in [20] by using descriptor approach and non-quadratic Lyapunov functions, whereas the T-S fuzzy systems with unmeasurable premise variables were considered in [21].

The communication protocols between the population space and the belief space are established through the modified fuzzy acceptance and influence functions.

Two years later, Aaliyah returned with the single "Try Again," which sounded nothing like "Are You That Somebody": Timbaland created a fuzzy, booming soundscape influenced by the dance genre known as acid house, and Aaliyah wrapped a serpentine vocal line around the beats.

ANFIS trains the influencing parameters of the fuzzy inference system through a learning algorithm deduced from neural network (Jang 1993).

The probabilistic analysis is supplemented with the fuzzy analysis of the influence of uncertainties on the failure probability.

For infinite valued systems with truth degree set the influence of fuzzy set theory since the mid-1980s initheted the study of a whole class of such systems of MVL.

Even for a deterministic fuzzy stress process, the influences of material statistical properties on reliability can be affected by the level α of fuzzy stress.

The choice of the constant distance also influences the fuzzy membership; if it is too small, then we cannot distinguish good clusters from outliers, and if it is too large, the result diverges from the basic FCM.

Then, the analysis applies two approaches to evaluating imprecise node probabilities in the influence diagram: "a fuzzy probability" and "an interval-valued subjective probability".