The Adaptive Network-Based Fuzzy Inference System (ANFIS) has been proven to be efficient for forecasting. To address this concern, this research develops a nonlinear combined forecasting system by ANFIS for predicting the demand of telecommu-nication technology. We investigate the weights assigned to the combined forecast using two linear methods (the Least squares analysis and the Logistic mo...

Though the hi-tech industry has focused on value innovation and improving the quality of the new product development (NPD) process to drive new product performance, new product success has not changed dramatically over the years. This study presents a novel approach based on structural equation modeling (SEM) and adaptive neuro-fuzzy inference system (ANFIS) to forecast value innovation and the...

This is the age of digital systems. Now a days, everything is being computerized. Peoples are using mobile phones, laptop, computer, camera, notebook, pdf reader etc digital systems too much than ever. Use of papers and pen, printed books are decreasing. Rather peoples are using digital means of communication, study, documentation. Optical character recognition is an application of these digita...

A chaos-ANFIS approach is presented for analysis of EEG signals fo r epileptic seizure recognition. The non-linear dynamics of the original EEGs are quantified in the form of the hurst exponent (H) and largest lyapunov exponent (λ). The process of EEG analysis consists of two phases, namely the qualitative and quantitative analysis. The classification ability of the H and λ measures is tested u...

The constant amplitude fatigue crack growth life is affected by load ratio which quantifies the influence of mean load. Several research works have been conducted to study the effect of load ratio on crack growth rate through deterministic approach. However, the application of artificial intelligence methods particularly adaptive neuro-fuzzy technique (ANFIS) is lacking. The current research pr...

This paper presents an approach to predict the operating conditions of machine based on classification and regression trees (CART) and adaptive neuro-fuzzy inference system (ANFIS) in association with direct prediction strategy for multi-step ahead prediction of time series techniques. In this study, the number of available observations and the number of predicted steps are initially determined...

Knowledge of the distinctive frequencies and amplitudes broken rotor bar (BRB) faults in induction motor (IM) is essential for most fault diagnosis methods. Fast Fourier transform (FFT) widely applied to diagnose within BRBs. However, this method does not provide satisfactory results if it directly stator current signal at low slip because a high-resolution spectrum required separate different ...

Now a days a manufacturing system is oriented towards higher production rate, quality, and reduced cost. Surface roughness is an index for determining the quality of machined products and is influenced by the cutting parameters. In die manufacturing industries Surface roughness of dies are considered as a vital quality characteristic. For the complex shapes of a die, three dimensional machining...

Present study investigates the capabilities of six distinct machine learning techniques such as ANFIS network with fuzzy c-means (ANFIS-FCM), grid partition (ANFIS-GP), subtractive clustering (ANFIS-SC), feed-forward neural (FNN), Elman (ENN), and long short-term memory (LSTM) in one-day ahead soil temperature (ST) forecasting. For this aim, daily ST data gathered at three different depths 5 cm...

An assessment of maximum scour depth downstream of grade control structure is essential for its proper planning, design and management. Most of the scour depth prediction formulae available in the literature have been developed based on the analysis of the laboratory/field data using the statistical method such as the regression method (RM). The alternative recent approaches such as artificial ...