The prediction of elastic modulus is one of the fundamental facts of structural engineering studies. The performance of adaptive neuro-fuzzy inference system (ANFIS) for predicting the elastic modulus of normaland high-strength concrete was investigated. Results indicate that the proposed ANFIS modeling approach outperforms the other given models in terms of prediction capability. According to ...

Dissolved oxygen (DO) & COD is a parameter frequently used to evaluate the water quality on different rivers. The aim of the present study is to investigate applicability of artificial intelligence techniques such as ANFIS (Adaptive Neuro-Fuzzy Inference System) in water quality DO & COD prediction for the case study, Mahi river at Khanpur in Thasara Taluka of Kheda District in Gujarat State, I...

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 ...

One of the main problems in the management of large water supply and distribution systems is the forecasting of daily demand in order to schedule pumping effort and minimize costs. This paper examines a methodology for consumer demand modeling and prediction in a real-time environment of an irrigation water distribution system. The approach is based on Adaptive Neuro-Fuzzy Inferences System (AN...

The paper presents a methodology for developing adaptive speed controllers in a permanent-magnet brushless DC (BLDC) motor drive system. A proportional-integral controller is employed in order to obtain the controller parameters at each selected load. The resulting data from PI controller are used to train adaptive neuro-fuzzy inference systems (ANFIS) that could deduce the controller parameter...

Since liquid tank systems are commonly used in industrial applications, system-related requirements results in many modeling and control problems because of their interactive use with other process control elements. Modeling stage is one of the most noteworthy parts in the design of a control system. Although nonlinear tank problems have been widely addressed in classical system dynamics, when ...

The aim of this study is to design ANFIS model and Fuzzy Expert System for determination of concrete mix design and finally compare their results. The datasets which has been loaded into ANFIS contains 552 mix designs and has been based on ACI mix designs. Moreover, in this study, a Fuzzy Expert System has been designed. Input fields of fuzzy expert system are Slump, Maximum Size of Aggregate (...

This paper presents the architecture and learning procedure underlying ANFIS (Adaptive-Network-based Fuzzy Inference System), a fuzzy inference system implemented in the framework of adaptive networks. By using a hybrid learning procedure, the proposed ANFIS can construct an input-output mapping based on both human knowledge (in the form of fuzzy if-then rules) and stipulated input-output data ...

Hybrid algorithm is the hot issue in Computational Intelligence (CI) study. From in-depth discussion on Simulation Mechanism Based (SMB) classification method and composite patterns, this paper presents the Mamdani model based Adaptive Neural Fuzzy Inference System (M-ANFIS) and weight updating formula in consideration with qualitative representation of inference consequent parts in fuzzy neura...

An Enterprise resource Planning (ERP) system is packaged business software that integrates organizational process and functions into a unified system. Many researchers and practitioners agree that Enterprise Resource Planning (ERP) systems are the most important development in terms of corporate use of information technology (IT) in the 1990s. In this author predict a Comparative study of Anfis...