The main aim of this work is the determination aromaticity in biochar from easier accessible parameters (e.g., elemental composition). To end, two machine learning models, including adaptive neurofuzzy inference system (ANFIS) and least-squares support vector (LSSVM), were used to predict constant form 98 dataset gathered earlier reported sources. outputs statistical showed that LSSVM model has...

This paper presents an investigation into the comparative performance of intelligent system identification and control algorithms within the framework of an active vibration control (AVC) system. Evolutionary Genetic algorithms (GAs) and Adaptive Neuro-Fuzzy Inference system (ANFIS) algorithms are used to develop mechanisms of an AVC system, where the controller is designed on the basis of opti...

-Now a day we have various types of intelligent computing tools such as artificial neural network (ANN) and fuzzy logic approaches are proving to be skillful when applied to a different kind of problems. This paper describes the application of adaptive neuro-fuzzy inference system (ANFIS) model for classification of electrocardiogram (ECG) signals. here we applied tool for detecting the two dif...

Abstract Improving the performance of machine learning (ML) algorithms is essential for accurately estimating water quality parameters (WQPs). For first time, a novel hybrid framework, namely adaptive neural fuzzy inference system–discrete wavelet transform–gradient-based optimization (ANFIS–DWT–GBO), estimation electrical conductivity (EC) and total dissolved solids (TDS), used. Before WQPs, A...

Now a day we have various intelligent computing tools such as artificial neural network (ANN) and fuzzy logic approaches are proving to be dexterous when applied to a range of problems. In this paper we applied the ANFIS (Adaptive Neuro-Fuzzy Interface System) tool for detecting the normal and abnormal signal. Here the designed ANFIS model contained both approaches the neural network adaptive p...

Water level forecasting is an essential topic in water management affecting reservoir operations and decision making. Recently, modern methods utilizing artificial intelligence, fuzzy logic, and combinations of these techniques have been used in hydrological applications because of their considerable ability to map an input-output pattern without requiring prior knowledge of the criteria influe...

A Correct diagnosis of tuberculosis (TB) can be only stated by applying a medical test to patient’s phlegm. The result of this test is obtained after a time period of about 45 days. The purpose of this study is to develop a data mining(DM) solution which makes diagnosis of tuberculosis as accurate as possible and helps deciding if it is reasonable to start tuberculosis treatment on suspected pa...

In the present study, a new modelling technique was developed for the modelling and analysis of hyperchaotic systems using an expert system based on wavelet decompositions and the Adaptive Neuro-Fuzzy Inference System (ANFIS). The success and superior properties of this new expert system were shown by applying the hyperchaotic Chen system which is a hyperchaotic system. The obtained expert syst...

Accurate solar radiation (SR) prediction is one of the essential prerequisites harvesting energy. The current study proposed a novel intelligence model through hybridization Adaptive Neuro-Fuzzy Inference System (ANFIS) with two metaheuristic optimization algorithms, Salp Swarm Algorithm (SSA) and Grasshopper Optimization (GOA) (ANFIS-muSG) for global SR at different locations North Dakota, USA...

A new speed control approach based on the Adaptive Neuro-Fuzzy Inference System (ANFIS) to a closed-loop, variable speed induction motor (IM) drive is proposed in this paper. ANFIS provides a nonlinear modeling of motor drive system and the motor speed can accurately track the reference signal. ANFIS has the advantages of employing expert knowledge from the fuzzy inference system and the learni...