For photographs taken in outdoor environments, the air medium causes light attenuation, which reduces image quality; this effect is particularly obvious in hazy environments. To eliminate the hazy effect in images and improve the image quality, the present study proposes an efficient hybrid method. The proposed fuzzy estimator was adopted to estimate variations in light attenuation, and morphol...

Flood forecasting is always a challenge in Taiwan, which has a subtropical climate and high mountains. This paper develops a fuzzy clustering neural network (FCNN), and implements this novel structure and reasoning process for flood forecasting. The FCNN has a hybrid learning scheme; the unsupervised learning scheme employs fuzzy min-max clustering to extract information from the input data. Th...

Usually neuro-fuzzy networks are trained by using mean squared error (MSE) as cost function. This approach may lead to some problems when the network is used to classify patterns. In this paper, we propose a new empirical risk functional that is particularly suitable for classification tasks, when neuro-fuzzy learning is based on a gradient descent strategy. This functional has the properties o...

This paper discusses a model reference adaptive sliding-mode control of the sensorless vector controlled induction motor drive in a wide speed range. The adaptive speed controller uses on-line trained fuzzy neural network, which enables very fast tracking of the changing speed reference signal. This adaptive sliding-mode neuro-fuzzy controller (ASNFC) is used as a speed controller in the direct...

The increasing technology of high-resolution image airborne sensors, including those on board Unmanned Aerial Vehicles, demands automatic solutions for processing, either on-line or off-line, the huge amountds of image data sensed during the flights. The classification of natural spectral signatures in images is one potential application. The actual tendency in classification is oriented toward...

This paper examines the very long-run relationship between income and emissions of enteric methane in New Zealand, over the period 1895 to 1996. Controlling the emissions of this particular greenhouse gas is of crucial importance if that country is to meet its obligations as a signatory to the Kyoto Protocol. We use standard parametric regression, nonparametric regression, and a new nonlinear r...

We propose a method for DDoS detection by constructing a fuzzy estimator on the mean packet inter arrival times. We divided the problem into two challenges, the first being the actual detection of the DDoS event taking place and the second being the identification of the offending IP addresses. We have imposed strict real time constraints for the first challenge and more relaxed constraints for...

The paper analyses issues leading to errors in graphic object classifiers. Thedistance measures suggested in literature and used as a basis in traditional, fuzzy, andNeuro-Fuzzy classifiers are found to be not suitable for classification of non-stylized orfuzzy objects in which the features of classes are much more difficult to recognize becauseof significant uncertainties in their location and...

Salah satu hal penting dalam analisis statistik adalah prosedur estimasi suatu fungsi padat peluang yang biasa disebut densitas. Ada dua metode pendekatan biasanya digunakan, yaitu parameter terkait dengan asumsi distribusi tertentu dan densitas secara non parametrik. Metode parametrik sering kita jumpai histogram.
 Beberapa kelemahan histogram menjadi acuan untuk dikembangkannya lain kern...

Abstract This research concerns the estimation of latent linear or polychoric correlations from fuzzy frequency tables. Fuzzy counts are particular interest to many disciplines including social and behavioral sciences especially relevant when observed data classified using categories—as for socioeconomic studies, clinical evaluations, content analysis, inter-rater reliability analysis—or imprec...