More recently Turkey has witnessed fast housing development and real estate sector growth because of the mortgage preparations. With this development, property location quality has been considered important for selecting and paying them. This study uses a data set of new single family housing units in Kocaeli University Campus Area. By using 4 location quality criteria, 27 single family housing...

Former fault diagnosis algorithms for the transmission systems usually employ FFT and deterministic thresholds. These bring simplicity along with lots of manual works and inaccuracy to the applications. This paper proposes a new adaptive fault diagnosis scheme, which hardly need any interference from users. It utilizes the Wavelet Packets Transformation Analysis (WPTA) as a preliminary feature ...

In this paper we present and evaluate a Radial-basis-function neural network detector for Distributed-Denial-of-Service (DDoS) attacks in public networks based on statistical features estimated in short-time window analysis of the incoming data packets. A small number of statistical descriptors were used to describe the DDoS attacks behaviour, and an accurate classification is achieved using th...

Motor fault detection and diagnosis involves processing a large amount of information of the motor system. With the combined synergy of fuzzy logic and neural networks, a better understanding of the heuristics underlying the motor fault detection/diagnosis process and successful fault detection/diagnosis schemes can be achieved. This paper presents two neural fuzzy (NN/FZ) inference systems, na...

The conceptual high-level design of a low cost neural network (NN) based autonomous vehicle is presented. Focus is on the domain of indoor as well as small outdoor applications such as mail delivery system among neighboring organizations. The design is based on four independent neural networks attached with ultrasonic rangefinders; Inertial Measuring Unit (IMU) and GPS receiver. The NN model is...

We present a hybrid and parallel system based on artificial neural networks for a face invariant classifier and general pattern recognition problems. A set of face features is extracted by using the eigenpaxel method, which is based on principal component analysis (PCA) of a group of pixel, that is called a paxel. To classify subjects, multi-layer perceptron neural network (NN)s are trained for...

Adaptive critic (AC) based controllers are typically discrete and/or yield a uniformly ultimately bounded stability result because of the presence of disturbances and unknown approximation errors. A continuous-time AC controller is developed that yields asymptotic tracking of a class of uncertain nonlinear systems with bounded disturbances. The proposed AC-based controller consists of two neura...

Web page classification provides an efficient information search to internet users. However, presently most of the web directories are still being classified manually or semiautomatically. This paper analyses the concept of the statistical analysis methods known as Principal Component Analysis (PCA) and Independent Component Analysis (ICA). The main purpose for using integration of PCA and ICA ...

Prosody modeling has become the backbone of TTS synthesis systems. Amongst all the prosodic modeling approaches, phonetic methods aiming to predict duration and F0 contour are being very praised, thanks to the development of regression tools, such as neural networks (NN). Besides, parametric representations like Fujisaki model for F0 contour generation help to reduce the problem into the approx...

This paper presents a novel control method for a general class of nonlinear systems using neural networks (NNs). Firstly, under the conditions of the system output and its time derivatives being available for feedback, an adaptive state feedback NN controller is developed. When only the output is measurable, by using a high-gain observer to estimate the derivatives of the system output, an adap...