Uncertainty and variability are inherent to pile design consequently, there have been considerable researches in quantifying the reliability or probability of failure structures. This paper aims at examining comparing applicability adaptability Minimax Probability Machine Regression (MPMR), Emotional Neural Network (ENN), Group Method Data Handling (GMDH), Adaptive Neuro-Fuzzy Inference System ...

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...

Forecasting rice production is a challenging problem in agricultural statistics. The inherent difficulty lies in demand and supply affected by many uncertain factors viz. economic policies, agricultural factors, credit measures, foreign trade etc. which interact in a complex manner. Since last few decades, Statistical techniques are used for developing predictive models to estimate required par...

This paper presents some algorithms for estimation of the state variables in distributed parameter systems of parabolic and hyperbolic types. These algorithms are expressed on regression using anterior values of adjacent state variables and on auto-regression using the anterior values of the same variable. The momentary values may be obtained using sensors from a network placed in the field of ...

Punching shear capacity is a key factor for governing the collapsed form of slabs. This fragile failure that occurs at the slab-column connection is called punching shear failure and has been of concern for the engineers. The most common practice in evaluating the punching strength of the concrete slabs is to use the empirical expressions available in different building design codes. The estima...

Production throughput measures the performance and behaviour of a production system. Production throughput modelling is complex because of uncertainties in the production line. This study examined the potential application of the adaptive neuro-fuzzy inference system (ANFIS) to modelling the throughput of production under five significant production uncertainties: scrap, setup time, break time,...

the purpose of this study is to investigate the accuracy of predictions of aniline removal efficiency in a moving bed biofilm reactor (mbbr) by various methods, namely by rbf, anfis, and fuzzy regression analysis. the reactor was operated in an aerobic batch and was filled by light expanded clay aggregate (leca) as a carrier for the treatment of aniline synthetic wastewater. exploratory data an...

This paper presents methodologies to select equities based on soft-computing models which focus on applying fundamental analysis for equities screening. This paper compares the performance of three soft-computing models, namely Multilayer Perceptrons (MLP), Adaptive Neuro-Fuzzy Inference Systems (ANFIS) and General Growing and Pruning Radial Basis Function (GGAP-RBF). It studies their computati...