the classification and regression trees (cart) possess the advantage of being able to handlelarge data sets and yield readily interpretable models. in spite to these advantages, they are alsorecognized as highly unstable classifiers with respect to minor perturbations in the training data.in the other words methods present high variance. fuzzy logic brings in an improvement in theseaspects due ...

It is important for the design of a distributed quantum circuit (DQC) to minimize communication cost in k -way balanced partitioning. In this article, given an original (QC), partitioning number , maximum capacity δ inside each partition, and size tolerance γ between two partitions, new (δ, γ)-...

Fuzzy inference systems (FIS) are widely used for process simulation or control. They can be designed either from expert knowledge or from data. For complex systems, FIS based on expert knowledge only may suffer from a loss of accuracy. This is the main incentive for using fuzzy rules inferred from data. Designing a FIS from data can be decomposed into two main phases: automatic rule generation...

VLSI Cell Partitioning plays a substantial part in VLSI physical design. The task of designing integrated circuits is multifaceted, as modern circuits have a very huge number of modules. It is very much essential to split the circuit into a smaller and meeker logic blocks. In order to build a complex digital integrated circuit, the multi million transistors must be sub-divided into convenientnu...

We propose a fuzzy-based approach which provides a soft threshold to determine the module size for CMOS circuit partitioning in built-in current testing (BICT). Experimental results show that our design approach indeed provides a feasible way to exploit the design space of BICT partitioning in comparison with other approaches with a fixed threshold, and a better module size can thus be determin...

Market zonal partitioning is one of the most efficient methods for congestion management which is used in many power markets around the world. To improve the market performance it is very important to recognize the best zones of the system. While congestion is due to deficiencies in transmission network or generation, load pattern of the system is the most important variable which has impact on...

Three Neuro-Fuzzy Inference Systems (ANFIS) including Grid Partitioning (GP), Subtractive Clustering (SCM) and Fuzzy C-means clustering Methods (FCM) have been used to predict the groutability of granular soil samples with cement-based grouts. Laboratory data from related available in litterature was used for the tests. Several parameters were taken into account in the proposed models: water:ce...

Slope stability analysis is an enduring research topic in the engineering and academic sectors. Accurate prediction of the factor of safety (FOS) of slopes, their stability, and their performance is not an easy task. In this work, the adaptive neuro-fuzzy inference system (ANFIS) was utilized to build an estimation model for the prediction of FOS. Three ANFIS models were implemented including g...

cases. In the first case, our contribution consists of mapping the problem to the mincut problem. In the second case, our contributions is the fuzzy-logic approach. In addition to those two cases, we presented a PLA partitioning technique which considers not only the delay through each sub-PLA, but also the increased loading on the stage which is driving the sub-PLA's. The last method provides ...