Cutting forces prediction is very important for cutting tool’s design and process planning. This paper presents a fuzzy cutting force modelling method using subtractive clustering for learning evaluation. In this method, subtractive clustering, combined with the least-square algorithm, identifies the fuzzy prediction model directly from the information obtained from the sensors. In the micro-mi...

Support vector regression (SVR) is a learning method based on the support vector machine (SVM) that can be used for curve fitting and function estimation. In this paper, the ability of the nu-SVR to predict the catalytic activity of the Fischer-Tropsch (FT) reaction is evaluated and the result is compared with two other prediction techniques including: multilayer perceptron (MLP) and subtractiv...

It is crucial to detect disease complications caused by metabolic syndromes early. High cholesterol, high glucose, and blood pressure are indicators of syndrome. The aim this study use adaptive neuro fuzzy inference system (ANFIS) predict potential compare its performance other classifiers, namely random forest (RF), C4.5, naïve Bayesian classification (NBC) algorithms. Fuzzy subtractive cluste...

Wind energy is increasing its participation as a main source of energy in power grids and electric utility systems around the world. One of the main difficulties of integrating large amounts of wind energy in power grids is the natural intermittency of its generated power [1, 2] due to the energy produced from the wind turbine being dependent on the availability of the wind, which is highly sto...

When a fault occurs during an industrial inspection, workmen have to manually find the location and type of the fault in order to remove it. It is often difficult to accurately find the location and type of fault. Hence, development of an offline intelligent fault diagnosis system for process control industry is of great importance since successful detection of fault is a precursor to fault iso...

In IaaS (infrastructure as a service) cloud environment, users are provisioned with virtual machines (VMs). To allocate resources for users dynamically and effectively, accurate resource demands predicting is essential. For this purpose, this paper proposes a self-adaptive prediction method using ensemble model and subtractive-fuzzy clustering based fuzzy neural network (ESFCFNN). We analyze th...

prediction, diagnosis, recovery and recurrence of the breast cancer among the patients are always one of the most important challenges for explorers and scientists. nowadays by using of the bioinformatics sciences, these challenges can be eliminated by using of the previous information of patients records. in this paper has been used adaptive nero fuzzy inference system and data mining techniqu...

Two-degree-of-freedom (2-DOF) compliant mechanism has some outstanding characteristics in accurate positioning systems. Studying the fatigue life for 2-DOF is a meaningful task to ensure long working. However, study prediction of this not been conducted so far. In article, method developed first time. This combining differential evolution algorithm and adaptive neuro-fuzzy inference system (ANF...

Typhoon intensity forecast is an important issue. The objective of this study to construct a 5-day 12-hourly typhoon model based on the adaptive neuro-fuzzy inference systems (ANFIS) improve in Northwest Pacific. It analyzed improvement ANFIS by comparing it with MLR when only atmospheric factor or both and oceanic factors are considered. This collected SHIPS (Statistical Hurricane Intensity Pr...