Now a day we have various intelligent computing tools such as artificial neural network (ANN) and fuzzy logic approaches are proving to be dexterous when applied to a range of problems. In this paper we applied the ANFIS (Adaptive Neuro-Fuzzy Interface System) tool for detecting the normal and abnormal signal. Here the designed ANFIS model contained both approaches the neural network adaptive p...

In this study, an efficient method is introduced to predict the stability of soil-structure interaction (SSI) system subject to earthquake loads. In the procedure of the nonlinear dynamic analysis, a number of structures collapse and then lose their stability. The prediction of failure probability is considered as stability criterion. In order to achieve this purpose, a modified adaptive neuro ...

The methods of ordinary least-squares regression (OLSR), fuzzy regression (FR), and adaptive network fuzzy inference system (ANFIS) are compared in inferring operating rules for a reservoir operations problem. Dynamic programming (DP) is used to provide the input-output data set to be used by OLSR, FR, and ANFIS models. The coefficients of an FR model are found by solving a linear programming (...

Nonlinear system identification is becoming an important tool which can be used to improve control performance. This paper describes the application of adaptive neuro-fuzzy inference system (ANFIS) model for controlling a car. The vehicle must follow a predefined path by supervised learning. Backpropagation gradient descent method was performed to train the ANFIS system. The performance of the ...

Currently, manufacturing industries focus on intelligent manufacturing. Prediction and monitoring of tool wear are essential in any material removal process, implementation a condition system (TCMS) is necessary. This work presents the flank prediction during hard turning EN8 steel using deep learning (DL) algorithm. The operation conducted with three levels selected parameters. CNMG 120408 gra...

We present an overview over our graph partitioners KaFFPa (Karlsruhe Fast Flow Partitioner) and KaFFPaE (KaFFPa Evolutionary). KaFFPa is a multilevel graph partitioning algorithm which on the one hand uses novel local improvement algorithms based on max-flow and min-cut computations and more localized FM searches and on the other hand uses more sophisticated global search strategies transferred...

a r t i c l e i n f o a b s t r a c t Dynamic load balancing Wavelets Lifting scheme Second generation wavelets Adaptive grid Multiresolution Multilevel method Multigrid method Numerical method Partial differential equations Elliptic problem A parallel adaptive wavelet collocation method for solving a large class of Partial Differential Equations is presented. The parallelization is achieved by...

We classify clustering algorithms into sequence-based techniques|which transform the object net into a linear sequence|and partition-based clustering algorithms. Tsangaris and Naughton [TN91, TN92] have shown that the partition-based techniques are superior. However, their work is based on a single partitioning algorithm, the Kernighan and Lin heuristics, which is not applicable to realisticall...

The cost/performance ratio of networks of workstations has been constantly improving. This trend is expected to continue in the near future. The aggregate peak rate of such systems often matches or exceeds the peak rate offered by the fastest parallel computers. This has motivated research toward using a network of computers, interconnected via a fast network (cluster system) or a simple Local ...

We present an overview over our graph partitioners KaFFPa (Karlsruhe Fast Flow Partitioner) and KaFFPaE (KaFFPa Evolutionary). KaFFPa is a multilevel graph partitioning algorithm which on the one hand uses novel local improvement algorithms based on max-flow and min-cut computations and more localized FM searches and on the other hand uses more sophisticated global search strategies transferred...