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 ...

Tourism in Greece plays a major role in the country’s economy and an accurate forecasting model for tourism demand is a useful tool, which could affect decision making and planning for the future. This paper answers some questions such as: how did the forecasting techniques evolve over the years, how precise can they be, and in what way can they be used in assessing the demand for tourism? An A...

Using a genetic algorithm owing to high nonlinearity of constraints, this paper first works on the optimal design of two-span continuous singly reinforced concrete beams. Given conditions are the span, dead and live loads, compressive strength of concrete and yield strength of steel; design variables are the width and effective depth of the continuous beam and steel ratios for positive and nega...

Despite of acquiring popularity among researchers, the implementations of ANFIS-based models face problems when the number of rules surge dramatically and increase the network complexity, which consequently adds computational cost. Essentially, not all the rules in ANFIS knowledge-base are the potential ones. They contain those rules which have either minor or no contribution to overall decisio...