This paper combines adaptive network fuzzy inference system (ANFIS) and finite element method (FEM) to study the die shape optimal design in sheet metal bending process. At first, the explicit dynamic FEM is used to simulate the sheet metal bending process. After the bending process, the springback is analyzed by using the implicit static FEM to establish the basic database for ANFIS. Then, the...

This paper presents an optimal load balancing algorithm based on both of the ANFIS (Adaptive Neuro-Fuzzy Inference System) modeling and the FIS (Fuzzy Inference System) for the local status of real servers. It also shows the substantial benefits such as the removal of loadscheduling overhead, QoS (Quality of Service) provisioning and providing highly available servers, provided by the suggested...

Sugiura, H. and T. Torii, A method for constructing generalized Runge-Kutta methods, Journal of Computational and Applied Mathematics 38 (1991) 399-410. In the implementation of an implicit Runge-Kutta formula, we need to solve systems of nonlinear equations. In this paper, we analyze the Newton iteration process and a modified Newton iteration process for solving these equations. Then we propo...

A set of validated numerical integration methods based on explicit and implicit Runge-Kutta schemes is presented to solve, in a guaranteed way, initial value problems of ordinary differential equations. Runge-Kutta methods are well-known to have strong stability properties, which make them appealing to be the basis of validated numerical integration methods. A new approach to bound the local tr...

The cubic spline interpolation method, the Runge–Kutta method, and the Newton–Raphson method are extended to dual versions (developed in the context of dual numbers). This extension allows the calculation of the derivatives of complicated compositions of functions which are not necessarily defined by a closed form expression. The code for the algorithms has been written in Fortran and some exam...

Landslide susceptibility analysis is beneficial information for a wide range of applications, including land use management plans. The present attempt has shed light on an efficient landslide mapping framework that involves adaptive neural-fuzzy inference system (ANFIS), which incorporates three metaheuristic methods grey wolf optimization (GWO), particle swarm (PSO), and shuffled frog leaping ...

In this paper, we employed both first and second laws of thermodynamics to analyze the flow and thermal decomposition in a variable viscosity Couette flow of a conducting fluid in a rotating system under the combined influence of magnetic field and Hall current. The non-linear governing differential equations are obtained and solved numerically using shooting method coupled with fourth order Ru...

This paper presents a new advanced methodology as a solution for the problem due to the current setting of Relay (21) when it is set to provide thermal backup protection for the generator during two common system disturbances, namely a system fault and a sudden application of a large system load. These investigations are carried out using Adaptive Neuro Fuzzy Inference System (ANFIS). The resul...

The accuracy of short-term wind speed prediction is very important for wind power generation. In this paper, a hybrid method combining ensemble empirical mode decomposition (EEMD), adaptive neural network based fuzzy inference system (ANFIS) and seasonal auto-regression integrated moving average (SARIMA) is presented for short-term wind speed forecasting. The original wind speed series is decom...

In a modeling process of a real world problem, there usually are a huge number of potential inputs involved. A large number of inputs may increase the complexity in computation and cause other problems related to running time, memory spaces, etc. In the case of modeling process with large input, the number of inputs should be reduced and the priority inputs should be determined by an optimal se...